%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59591 %T Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study %A Lewis,Claire %A Groarke,Jenny %A Graham-Wisener,Lisa %A James,Jacqueline %+ School of Medicine Dentistry and Biomedical Sciences, Queen's University Belfast, University Road, Belfast, BT7 1NN, United Kingdom, 44 2890972804, claire.lewis@qub.ac.uk %K artificial intelligence %K AI %K public opinion %K pathology %K health care %K public awareness %K survey %D 2025 %7 2.4.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One of the most promising areas of research that has potential clinical utility is the use of AI in pathology to aid cancer diagnosis and management. While the value of using AI to improve the efficiency and accuracy of diagnosis cannot be underestimated, there are challenges in the development and implementation of such technologies. Notably, questions remain about public support for the use of AI to assist in pathological diagnosis and for the use of health care data, including data obtained from tissue samples, to train algorithms. Objective: This study aimed to investigate public awareness of and attitudes toward AI in pathology research and practice. Methods: A nationally representative, cross-sectional, web-based mixed methods survey (N=1518) was conducted to assess the UK public’s awareness of and views on the use of AI in pathology research and practice. Respondents were recruited via Prolific, an online research platform. To be eligible for the study, participants had to be aged >18 years, be UK residents, and have the capacity to express their own opinion. Respondents answered 30 closed-ended questions and 2 open-ended questions. Sociodemographic information and previous experience with cancer were collected. Descriptive and inferential statistics were used to analyze quantitative data; qualitative data were analyzed thematically. Results: Awareness was low, with only 23.19% (352/1518) of the respondents somewhat or moderately aware of AI being developed for use in pathology. Most did not support a diagnosis of cancer (908/1518, 59.82%) or a diagnosis based on biomarkers (694/1518, 45.72%) being made using AI only. However, most (1478/1518, 97.36%) supported diagnoses made by pathologists with AI assistance. The adjusted odds ratio (aOR) for supporting AI in cancer diagnosis and management was higher for men (aOR 1.34, 95% CI 1.02-1.75). Greater awareness (aOR 1.25, 95% CI 1.10-1.42), greater trust in data security and privacy protocols (aOR 1.04, 95% CI 1.01-1.07), and more positive beliefs (aOR 1.27, 95% CI 1.20-1.36) also increased support, whereas identifying more risks reduced the likelihood of support (aOR 0.80, 95% CI 0.73-0.89). In total, 3 main themes emerged from the qualitative data: bringing the public along, the human in the loop, and more hard evidence needed, indicating conditional support for AI in pathology with human decision-making oversight, robust measures for data handling and protection, and evidence for AI benefit and effectiveness. Conclusions: Awareness of AI’s potential use in pathology was low, but attitudes were positive, with high but conditional support. Challenges remain, particularly among women, regarding AI use in cancer diagnosis and management. Apprehension persists about the access to and use of health care data by private organizations. %M 40173441 %R 10.2196/59591 %U https://www.jmir.org/2025/1/e59591 %U https://doi.org/10.2196/59591 %U http://www.ncbi.nlm.nih.gov/pubmed/40173441 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e54516 %T Mechanism Assessment of Physician Discourse Strategies and Patient Consultation Behaviors on Online Health Platforms: Mixed Methods Study %A Kong,Menglei %A Wang,Yu %A Li,Meixuan %A Yao,Zhong %+ School of Economics and Management, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing, 100083, China, 86 13811013409, 05723@buaa.edu.cn %K online health consultation %K physician discourse strategies %K online physician-patient trust %K shared decision-making %K patient consultation behavior %D 2025 %7 19.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Online health platforms are currently experiencing significant growth. Patients can conveniently seek medical consulting services on such platforms. Against the backdrop of the thriving development of digital health care, the patterns of physician-patient communication are undergoing profound changes. It is imperative to focus on physician discourse strategies during online physician-patient interactions, which will improve the efficiency of physician-patient communication and achieve better management of the physician-patient relationship. Objective: This study aims to explore the influencing mechanism between physician discourse strategies and patient consultation behavior on online health platforms. Additionally, we explore the crucial mediating role of online physician-patient trust and the moderating role of shared decision-making in the online physician-patient communication process. Methods: We used a mixed research approach to explore the influencing mechanism. Data on physician basic attributes and physician-patient communication text records were collected from the Chunyu Doctor website using a web spider. The study obtained a total of 8628 interaction texts from January 2022 to July 2023. Physician discourse strategies (capacity-oriented strategy, quality-oriented strategy, and goodwill-oriented strategy), online physician-patient trust, and shared decision-making were captured through text mining and a random forest model. First, we employed text mining to extract the speech acts, modal resources, and special linguistic resources of each record. Then, using a well-trained random forest model, we captured the specific discourse strategy of each interaction text based on the learned features and patterns. The study generated 863 groups of physician samples with 17 data fields. The hypotheses were tested using an “ordinary least squares” model, and a stability test was conducted by replacing the dependent variable. Results: The capacity-oriented strategy, goodwill-oriented strategy, and quality-oriented strategy had significant effects on patient consultation behavior (β=.151, P=.007; β=.154, P<.001; and β=.17, P<.001, respectively). It should be noted that the anticipated strong effect of the capacity-oriented strategy on patient consultation behavior was not observed. Instead, the effects of the quality-oriented strategy and goodwill-oriented strategy were more prominent. Physician notification adequacy from shared decision-making moderated the effect between the goodwill-oriented strategy and patient consultation behavior (β=.172; P<.001). Additionally, patient expression adequacy from shared decision-making moderated the effect between the capacity-oriented strategy and patient consultation behavior (β=.124; P<.001), and between the goodwill-oriented strategy and patient consultation behavior (β=.104; P=.003). Online physician-patient trust played a significant mediating role between physician discourse strategies and patient consultation behavior. Conclusions: The study findings suggest significant implications for stimulating patient consultation behavior on online health platforms by providing guidance on effective discourse strategies for physicians, thus constructing a trustworthy physician image, improving the physician-patient relationship, and increasing platform traffic. %M 40106798 %R 10.2196/54516 %U https://www.jmir.org/2025/1/e54516 %U https://doi.org/10.2196/54516 %U http://www.ncbi.nlm.nih.gov/pubmed/40106798 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e66344 %T Revealing Patient Dissatisfaction With Health Care Resource Allocation in Multiple Dimensions Using Large Language Models and the International Classification of Diseases 11th Revision: Aspect-Based Sentiment Analysis %A Li,Jiaxuan %A Yang,Yunchu %A Mao,Chao %A Pang,Patrick Cheong-Iao %A Zhu,Quanjing %A Xu,Dejian %A Wang,Yapeng %+ Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, Macao, 853 85996886, mail@patrickpang.net %K ICD-11 %K International Classification of Diseases 11th Revision %K disease classification %K patient reviews %K patient satisfaction %K ChatGPT %K Sustainable Development Goals %K chain of thought %K large language model %D 2025 %7 17.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Accurately measuring the health care needs of patients with different diseases remains a public health challenge for health care management worldwide. There is a need for new computational methods to be able to assess the health care resources required by patients with different diseases to avoid wasting resources. Objective: This study aimed to assessing dissatisfaction with allocation of health care resources from the perspective of patients with different diseases that can help optimize resource allocation and better achieve several of the Sustainable Development Goals (SDGs), such as SDG 3 (“Good Health and Well-being”). Our goal was to show the effectiveness and practicality of large language models (LLMs) in assessing the distribution of health care resources. Methods: We used aspect-based sentiment analysis (ABSA), which can divide textual data into several aspects for sentiment analysis. In this study, we used Chat Generative Pretrained Transformer (ChatGPT) to perform ABSA of patient reviews based on 3 aspects (patient experience, physician skills and efficiency, and infrastructure and administration)00 in which we embedded chain-of-thought (CoT) prompting and compared the performance of Chinese and English LLMs on a Chinese dataset. Additionally, we used the International Classification of Diseases 11th Revision (ICD-11) application programming interface (API) to classify the sentiment analysis results into different disease categories. Results: We evaluated the performance of the models by comparing predicted sentiments (either positive or negative) with the labels judged by human evaluators in terms of the aforementioned 3 aspects. The results showed that ChatGPT 3.5 is superior in a combination of stability, expense, and runtime considerations compared to ChatGPT-4o and Qwen-7b. The weighted total precision of our method based on the ABSA of patient reviews was 0.907, while the average accuracy of all 3 sampling methods was 0.893. Both values suggested that the model was able to achieve our objective. Using our approach, we identified that dissatisfaction is highest for sex-related diseases and lowest for circulatory diseases and that the need for better infrastructure and administration is much higher for blood-related diseases than for other diseases in China. Conclusions: The results prove that our method with LLMs can use patient reviews and the ICD-11 classification to assess the health care needs of patients with different diseases, which can assist with resource allocation rationally. %M 40096682 %R 10.2196/66344 %U https://www.jmir.org/2025/1/e66344 %U https://doi.org/10.2196/66344 %U http://www.ncbi.nlm.nih.gov/pubmed/40096682 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e67452 %T Using an Interactive Voice Response Survey to Assess Patient Satisfaction in Ethiopia: Development and Feasibility Study %A Shamebo,Dessalegn %A Derseh Mebratie,Anagaw %A Arsenault,Catherine %+ Department of Global Health, Milken Institute School of Public Health, The George Washington University, 950 New Hampshire Avenue, Washington, DC, 20052, United States, 1 2029941011, catherine.arsenault@gwu.edu %K mobile phone surveys %K patient satisfaction %K interactive voice response %K global health %K surveys %K Ethiopia %K IVR %K Africa %D 2025 %7 13.2.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Patient satisfaction surveys can offer crucial information on the quality of care but are rarely conducted in low-income settings. In contrast with in-person exit interviews, phone-based interactive voice response (IVR) surveys may offer benefits including standardization, patient privacy, reduced social desirability bias, and cost and time efficiency. IVR surveys have rarely been tested in low-income settings, particularly for patient satisfaction surveys. Objective: In this study, we tested the feasibility of using an IVR system to assess patient satisfaction with primary care services in Addis Ababa, Ethiopia. We described the methodology, response rates, and survey costs and identified factors associated with survey participation, completion, and duration. Methods: Patients were recruited in person from 18 public and private health facilities in Addis Ababa. Patients’ sex, age, education, reasons for seeking care, and mobile phone numbers were collected. The survey included 15 questions that respondents answered using their phone keypad. We used a Heckman probit regression model to identify factors influencing the likelihood of IVR survey participation (picking up and answering at least 1 question) and completion (answering all survey questions) and a Weibull regression model to identify factors influencing the survey completion time. Results: A total of 3403 individuals were approached across 18 health facilities. Nearly all eligible patients approached (2985/3167, 94.3%) had a functioning mobile phone, and 89.9% (2415/2685) of those eligible agreed to be enrolled in the study. Overall, 92.6% (2236/2415) picked up the call, 65.6% (1584/2415) answered at least 1 survey question, and 42.9% (1037/2415) completed the full survey. The average survey completion time was 8.1 (SD 1.7) minutes for 15 Likert-scale questions. We found that those aged 40-49 years and those aged 50+ years were substantially less likely to participate in (odds ratio 0.63, 95% CI 0.53-0.74) and complete the IVR survey (odds ratio 0.77, 95% CI 0.65-0.90) compared to those aged 18-30 years. Higher education levels were also strongly associated with survey participation and completion. In adjusted models, those enrolled in private facilities were less likely to participate and complete the survey compared to those in public health centers. Being male, younger, speaking Amharic, using a private hospital, and being called after 8 PM were associated with a shorter survey duration. The average survey costs were US $7.90 per completed survey. Conclusions: Our findings reveal that an IVR survey is a feasible, low-cost, and rapid solution to assess patient satisfaction in an urban context in Ethiopia. However, survey implementation must be carefully planned and tailored to local challenges. Governments and health facilities should consider IVR to routinely collect patient satisfaction data to inform quality improvement strategies. %R 10.2196/67452 %U https://formative.jmir.org/2025/1/e67452 %U https://doi.org/10.2196/67452 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e68619 %T Users’ Perspectives of Direct-to-Consumer Telemedicine Services: Survey Study %A Churruca,Kate %A Foo,Darran %A Turner,Andrew %A Crameri,Emily %A Saba,Maree %A Spanos,Samantha %A Vickers,Matthew %A Braithwaite,Jeffrey %A Ellis,Louise A %K telemedicine %K digital health technology %K direct-to-consumer %K digital tools %K telehealth %K consumer experience %D 2025 %7 3.2.2025 %9 %J JMIR Form Res %G English %X Background: Commercially run direct-to-consumer (DTC) telemedicine services are on the rise in countries such as Australia and the United States. These include DTC services that are web-based, largely asynchronous, and offer targeted treatment pathways for specific health issues (eg, weight loss or sexual function). It has been argued that DTC telemedicine improves access to health care and promotes patient empowerment. Despite research examining quality and safety issues, little is known about users’ reasons for accessing DTC telemedicine services or their perceptions of them. Objective: In this study, we aimed to examine the perspectives of Australian users accessing DTC telemedicine services, including the reasons for use, perceived benefits, and concerns, in addition to their usage and interaction with traditional general practice services. Methods: A web-based cross-sectional survey including questions on demographics, published and validated scales, and author-developed closed- and open-response questions was administered via REDCap in 2023 to Australian adults accessing DTC telemedicine services. Results: Among the 151 respondents, most (136/151, 90.1%) had seen a general practitioner (GP) in the previous 12 months and were somewhat or very satisfied (118/136, 86.8%) with the care, just over half found it easy to get an appointment with their GP (76/151, 50.3%), and a quarter found it difficult (38/151, 25.2%). Among the 136 respondents who had seen a GP, more than half either “never” (55/136, 40.4%) or “rarely” (23/136, 16.9%) discussed the information and treatment received from DTC telemedicine service with their GP. The majority of respondents were using a DTC telemedicine service offering prescription skin care (92/151, 60.9%), had received treatment in the previous 6 months (123/151, 81.5%), and had self-initiated care (128/151, 84.8%). The most frequently cited reasons for using DTC telemedicine were related to convenience (97/121, 80.2%) and flexibility (71/121, 58.7%), while approximately a third of the sample selected that it was difficult to see traditional health care provider in their preferred time frame (44/121, 36.4%) and that the use of DTC telemedicine allowed them to gain access to services otherwise unavailable through traditional health care (39/121, 32.2%). Most participants felt “more in control” (106/128, 82.9%) and “in charge” of their health concern (102/130, 78.5%) when using DTC telemedicine services, in addition to having “more correct knowledge” (92/128, 71.9%) and “feeling better informed as a patient” (94/131, 71.8%). “Costs of services” (40/115, 34.8%) and “privacy” (31/115, 27%) were the most frequently reported concerns with using digital health care technologies such as DTC telemedicine. Conclusions: We report that most users perceive DTC telemedicine services as offering ease of access and convenience, and that their use contributes to a greater sense of empowerment over their health. Concerns were related to data privacy and the costs of utilizing the services. Responses suggest that DTC telemedicine may be tapping into a previously unmet need, rather than complementing traditional health care provided by a GP. %R 10.2196/68619 %U https://formative.jmir.org/2025/1/e68619 %U https://doi.org/10.2196/68619 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e55721 %T An Intelligent System for Classifying Patient Complaints Using Machine Learning and Natural Language Processing: Development and Validation Study %A Li,Xiadong %A Shu,Qiang %A Kong,Canhong %A Wang,Jinhu %A Li,Gang %A Fang,Xin %A Lou,Xiaomin %A Yu,Gang %+ Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center For Child Health, No. 3333, Binsheng Road, Binjiang District, Hangzhou, Hang Zhou, 310020, China, 86 13588773370, yugbme@zju.edu.cn %K complaint analysis %K text classification %K natural language processing %K NLP %K machine learning %K ML %K patient complaints %D 2025 %7 8.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Accurate classification of patient complaints is crucial for enhancing patient satisfaction management in health care settings. Traditional manual methods for categorizing complaints often lack efficiency and precision. Thus, there is a growing demand for advanced and automated approaches to streamline the classification process. Objective: This study aimed to develop and validate an intelligent system for automatically classifying patient complaints using machine learning (ML) and natural language processing (NLP) techniques. Methods: An ML-based NLP technology was proposed to extract frequently occurring dissatisfactory words related to departments, staff, and key treatment procedures. A dataset containing 1465 complaint records from 2019 to 2023 was used for training and validation, with an additional 376 complaints from Hangzhou Cancer Hospital serving as an external test set. Complaints were categorized into 4 types—communication problems, diagnosis and treatment issues, management problems, and sense of responsibility concerns. The imbalanced data were balanced using the Synthetic Minority Oversampling Technique (SMOTE) algorithm to ensure equal representation across all categories. A total of 3 ML algorithms (Multifactor Logistic Regression, Multinomial Naive Bayes, and Support Vector Machines [SVM]) were used for model training and validation. The best-performing model was tested using a 5-fold cross-validation on external data. Results: The original dataset consisted of 719, 376, 260, and 86 records for communication problems, diagnosis and treatment issues, management problems, and sense of responsibility concerns, respectively. The Multifactor Logistic Regression and SVM models achieved weighted average accuracies of 0.89 and 0.93 in the training set, and 0.83 and 0.87 in the internal test set, respectively. Ngram-level term frequency–inverse document frequency did not significantly improve classification performance, with only a marginal 1% increase in precision, recall, and F1-score when implementing Ngram-level term frequency–inverse document frequency (n=2) from 0.91 to 0.92. The SVM algorithm performed best in prediction, achieving an average accuracy of 0.91 on the external test set with a 95% CI of 0.87-0.97. Conclusions: The NLP-driven SVM algorithm demonstrates effective classification performance in automatically categorizing patient complaint texts. It showed superior performance in both internal and external test sets for communication and management problems. However, caution is advised when using it for classifying sense of responsibility complaints. This approach holds promises for implementation in medical institutions with high complaint volumes and limited resources for addressing patient feedback. %M 39778195 %R 10.2196/55721 %U https://www.jmir.org/2025/1/e55721 %U https://doi.org/10.2196/55721 %U http://www.ncbi.nlm.nih.gov/pubmed/39778195 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e57884 %T Visualizing Empathy in Patient-Practitioner Interactions Using Eye-Tracking Technology: Proof-of-Concept Study %A Park,Yuyi %A ­Kim,Hyungsin %A Kim,Hakkyun %K clinical empathy %K eye tracking %K medical communication %K nonverbal behavior %K doctor-patient encounters %D 2024 %7 11.12.2024 %9 %J JMIR Form Res %G English %X Background: Communication between medical practitioners and patients in health care settings is essential for positive patient health outcomes. Nonetheless, researchers have paid scant attention to the significance of clinical empathy in these interactions as a practical skill. Objective: This study aims to understand clinical empathy during practitioner-patient encounters by examining practitioners’ and patients’ verbal and nonverbal behaviors. Using eye-tracking techniques, we focused on the relationship between traditionally assessed clinical empathy and practitioners’ actual gaze behavior. Methods: We used mixed methods to understand clinical encounters by comparing 3 quantitative measures: eye-tracking data, scores from the Korean version of the Jefferson Scale of Empathy–Health Professional, and Consultation and Relational Empathy survey scores. We also conducted qualitative interviews with patients regarding their encounters. Results: One practitioner and 6 patients were involved in the experiment. Perceived empathy on the part of the practitioner was notably higher when the practitioner focused on a patient’s mouth area during the consultation, as indicated by gaze patterns that focused on a patient’s face. Furthermore, an analysis of areas of interest revealed different patterns in interactions with new as opposed to returning patients. Postconsultation interviews suggested that task-oriented and socially oriented empathy are critical in aligning with patients’ expectations of empathetic communication. Conclusions: This proof-of-concept study advocates a multidimensional approach to clinical empathy, revealing that a combination of verbal and nonverbal behaviors significantly reinforces perceived empathy from health care workers. This evolved paradigm of empathy underscores the profound consequences for medical education and the quality of health care delivery. %R 10.2196/57884 %U https://formative.jmir.org/2024/1/e57884 %U https://doi.org/10.2196/57884 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55140 %T Service Quality and Patient Satisfaction of Internet Hospitals in China: Cross-Sectional Evaluation With the Service Quality Questionnaire %A Han,Tao %A Wei,Qinpeng %A Wang,Ruike %A Cai,Yijin %A Zhu,Hongyi %A Chen,Jiani %A Zhang,Zhiruo %A Li,Sisi %+ School of Public Health, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China, 86 02163846590 ext 776145, lisi8318@gmail.com %K service quality %K SERVQUAL %K Service Quality Questionnaire %K internet hospital %K e-hospital %K digital medical care %K health care professionals %K Chinese digital health care %D 2024 %7 8.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Internet hospitals, which refer to service platforms that integrate consultation, prescription, payment, and drug delivery based on hospital entities, have been developing at a rapid pace in China since 2014. However, assessments regarding their service quality and patient satisfaction have not been well developed. There is an urgent need to comprehensively evaluate and improve the service quality of internet hospitals. Objective: This study aims to investigate the current status of patients’ use of internet hospitals, as well as familiarity and willingness to use internet hospitals, to evaluate patients’ expected and perceived service qualities of internet hospitals using the Chinese version of the Service Quality Questionnaire (SERVQUAL-C) with a national representative sample, and to explore the association between service quality of internet hospitals and patients’ overall satisfaction toward associated medical platforms. Methods: This cross-sectional survey was conducted through face-to-face or digital interviews from June to September 2022. A total of 1481 outpatient participants (635 men and 846 women; mean age 33.22, SD 13.22). Participants reported their use of internet hospitals, and then rated their expectations and perceptions of service quality toward internet hospitals via the SERVQUAL-C, along with their demographic information. Results: Among the surveyed participants, 51.2% (n=758) of participants had used internet hospital service or services. Use varied across age, education level, and annual income. Although the majority of them (n=826, 55.8%) did not know internet hospital services well, 68.1% (n=1009) of participants expressed the willingness to adopt this service. Service quality evaluation revealed that the perceived service quality did not match with the expectation, especially the responsiveness dimension. Important-performance analysis results further alerted that reliable diagnosis, prompt response, clear feedback pathway, and active feedback handling were typically the services awaiting substantial improvement. More importantly, multiple linear regressions revealed that familiarity and willingness to use internet hospital services were significant predictors of satisfaction, above and over tangibles, reliability, and empathy service perspectives, and demographic characteristics such as gender, age, education level, and annual income. Conclusions: In the future, internet hospitals should focus more on how to narrow the gaps between the expected and perceived service quality. Promotion of internet hospitals should also be facilitated to increase patients’ familiarity with and willingness to use these services. %M 39514849 %R 10.2196/55140 %U https://www.jmir.org/2024/1/e55140 %U https://doi.org/10.2196/55140 %U http://www.ncbi.nlm.nih.gov/pubmed/39514849 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50236 %T Classification of Patients’ Judgments of Their Physicians in Web-Based Written Reviews Using Natural Language Processing: Algorithm Development and Validation %A Madanay,Farrah %A Tu,Karissa %A Campagna,Ada %A Davis,J Kelly %A Doerstling,Steven S %A Chen,Felicia %A Ubel,Peter A %+ Center for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, 2800 Plymouth Rd, Bldg 14, G016, Ann Arbor, MI, 48109, United States, 1 8083524196, madanafl@med.umich.edu %K web-based physician reviews %K patient judgments %K RoBERTa %K natural language processing %K text classification %K machine learning %K patient experience %K patient-authored reviews %K healthcare quality %K patient care %K psychology %D 2024 %7 1.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients increasingly rely on web-based physician reviews to choose a physician and share their experiences. However, the unstructured text of these written reviews presents a challenge for researchers seeking to make inferences about patients’ judgments. Methods previously used to identify patient judgments within reviews, such as hand-coding and dictionary-based approaches, have posed limitations to sample size and classification accuracy. Advanced natural language processing methods can help overcome these limitations and promote further analysis of physician reviews on these popular platforms. Objective: This study aims to train, test, and validate an advanced natural language processing algorithm for classifying the presence and valence of 2 dimensions of patient judgments in web-based physician reviews: interpersonal manner and technical competence. Methods: We sampled 345,053 reviews for 167,150 physicians across the United States from Healthgrades.com, a commercial web-based physician rating and review website. We hand-coded 2000 written reviews and used those reviews to train and test a transformer classification algorithm called the Robustly Optimized BERT (Bidirectional Encoder Representations from Transformers) Pretraining Approach (RoBERTa). The 2 fine-tuned models coded the reviews for the presence and positive or negative valence of patients’ interpersonal manner or technical competence judgments of their physicians. We evaluated the performance of the 2 models against 200 hand-coded reviews and validated the models using the full sample of 345,053 RoBERTa-coded reviews. Results: The interpersonal manner model was 90% accurate with precision of 0.89, recall of 0.90, and weighted F1-score of 0.89. The technical competence model was 90% accurate with precision of 0.91, recall of 0.90, and weighted F1-score of 0.90. Positive-valence judgments were associated with higher review star ratings whereas negative-valence judgments were associated with lower star ratings. Analysis of the data by review rating and physician gender corresponded with findings in prior literature. Conclusions: Our 2 classification models coded interpersonal manner and technical competence judgments with high precision, recall, and accuracy. These models were validated using review star ratings and results from previous research. RoBERTa can accurately classify unstructured, web-based review text at scale. Future work could explore the use of this algorithm with other textual data, such as social media posts and electronic health records. %M 39088259 %R 10.2196/50236 %U https://www.jmir.org/2024/1/e50236 %U https://doi.org/10.2196/50236 %U http://www.ncbi.nlm.nih.gov/pubmed/39088259 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e51672 %T Examining the Role of Physician Characteristics in Web-Based Verified Primary Care Physician Reviews: Observational Study %A Sehgal,Neil K R %A Rader,Benjamin %A Brownstein,John S %+ Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut St, Philadelphia, PA, 19104, United States, 1 215 898 9672, neilsehgal99@gmail.com %K patient review websites %K patient online review %K telemedicine %K internet %K online review %K online reviews %K rating %K physician review %K physician reviews %K doctor review %K doctor reviews %D 2024 %7 29.7.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Doctor review websites have become increasingly popular as a source of information for patients looking to select a primary care provider. Zocdoc is one such platform that allows patients to not only rate and review their experiences with doctors but also directly schedule appointments. This study examines how several physician characteristics including gender, age, race, languages spoken in a physician’s office, education, and facial attractiveness impact the average numerical rating of primary care doctors on Zocdoc. Objective: The aim of this study was to investigate the association between physician characteristics and patient satisfaction ratings on Zocdoc. Methods: A data set of 1455 primary care doctor profiles across 30 cities was scraped from Zocdoc. The profiles contained information on the physician’s gender, education, and languages spoken in their office. Age, facial attractiveness, and race were imputed from profile pictures using commercial facial analysis software. Each doctor profile listed an average overall satisfaction rating, bedside manner rating, and wait time rating from verified patients. Descriptive statistics, the Wilcoxon rank sum test, and multivariate logistic regression were used to analyze the data. Results: The average overall rating on Zocdoc was highly positive, with older age, lower facial attractiveness, foreign degrees, allopathic degrees, and speaking more languages negatively associated with the average rating. However, the effect sizes of these factors were relatively small. For example, graduates of Latin American medical schools had a mean overall rating of 4.63 compared to a 4.77 rating for US graduates (P<.001), a difference roughly equivalent to a 2.8% decrease in appointments. On multivariate analysis, being Asian and having a doctor of osteopathic medicine degree were positively associated with higher overall ratings, while attending a South Asian medical school and speaking more European and Middle Eastern languages in the office were negatively associated with higher overall ratings. Conclusions: Overall, the findings suggest that age, facial attractiveness, education, and multilingualism do have some impact on web-based doctor reviews, but the numerical effect is small. Notably, bias may play out in many forms. For example, a physician's appearance or accent may impact a patient's trust, confidence, or satisfaction with their physician, which could in turn influence their take-up of preventative services and lead to either better or worse health outcomes. The study highlights the need for further research in how physician characteristics influence patient ratings of care. %M 39074363 %R 10.2196/51672 %U https://www.jmir.org/2024/1/e51672 %U https://doi.org/10.2196/51672 %U http://www.ncbi.nlm.nih.gov/pubmed/39074363 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56687 %T The Relationship Between Static Characteristics of Physicians and Patient Consultation Volume in Internet Hospitals: Quantitative Analysis %A Wang,Ye %A Shi,Changjing %A Wang,Xinyun %A Meng,Hua %A Chen,Junqiang %+ Department of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, No 6 Shuangyong Road, Qingxiu District, Nanning, 530021, China, 86 07715347234, chenjunqiang@gxmu.edu.cn %K static characteristics of physicians %K internet hospitals %K telemedicine %K statistical analysis %K online consultation %K web-based consultation %K teleconsultation %K physician %K patient %D 2024 %7 17.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Internet medical treatment, also known as telemedicine, represents a paradigm shift in health care delivery. This contactless model allows patients to seek medical advice remotely, often before they physically visit a doctor’s clinic. Herein, physicians are in a relatively passive position, as patients browse and choose their health care providers. Although a wealth of experience is undoubtedly a draw for many patients, it remains unclear which specific facets of a doctor’s credentials and accomplishments patients prioritize during their selection process. Objective: Our primary aim is to delve deeper into the correlation between physicians’ static characteristics—such as their qualifications, experiences, and profiles on the internet—and the number of patient visits they receive. We seek to achieve this by analyzing comprehensive internet hospital data from public hospitals. Furthermore, we aim to offer insights into how doctors can present themselves more effectively on web-based platforms, thereby attracting more patients and improving overall patient satisfaction. Methods: We retrospectively gathered web-based diagnosis and treatment data from the First Affiliated Hospital of Guangxi Medical University in 2023. These data underwent rigorous analysis, encompassing basic descriptive statistics, correlation analyses between key factors in doctors’ internet-based introductions, and the number of patient consultation visits. Additionally, we conducted subgroup analyses to ascertain the independence of these vital factors. To further distill the essence from these data, we used nonnegative matrix factorization to identify crucial demographic characteristics that significantly impact patient choice. Results: The statistical results suggested that there were significant differences in the distribution of consultation volume (P<.001), and the correlation analysis results suggested that there was a strong correlation between the two groups of data (ρ=0.93; P<.001). There was a correlation between the richness of a profile and popularity (P<.001). Patients were more interested in physicians with advanced titles, doctoral degrees, social activities, and scientific achievements (P<.001) as well as other institutional visit experiences (P=.003). More prosperous social activities, scientific achievements, experiences of other institutional visits, and awards were more common among people with advanced professional titles. Doctoral degrees remained attractive to patients when data were limited to senior physicians (P<.001). Patients trusted the medical staff with advanced titles, social activities, scientific achievements, and doctoral degrees (P<.001). Conclusions: Patient preferences for choosing a health care provider differed significantly between free and paid consultations. Notably, patients tended to trust doctors with advanced professional titles more and were more likely to seek out those with doctoral qualifications over other professional ranks. Additionally, physicians who actively participated in social events and scientific endeavors often had an advantage in attracting new patients. Given these insights, doctors who invest in enhancing their personal and professional experiences within these domains are likely to see increased popularity and patient satisfaction. %M 38885498 %R 10.2196/56687 %U https://formative.jmir.org/2024/1/e56687 %U https://doi.org/10.2196/56687 %U http://www.ncbi.nlm.nih.gov/pubmed/38885498 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e46551 %T Influence of Physical Attractiveness and Gender on Patient Preferences in Digital Doctor Consultations: Experimental Study %A Wei,Xia %A Yu,Shubin %A Li,Changxu (Victor) %+ Department of Communication and Culture, BI Norwegian Business School, Nydalsveien 37, Oslo, 0484, Norway, 47 41228055, shubin.yu@bi.no %K digital doctor consultations %K health care providers %K gender stereotype %K physical attractiveness %K qualification information %K experimental %K telemedicine %K digital consultation %K disease severity %K sex %K gender %K gender stereotypes %K digital health %D 2024 %7 30.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The rise of digital health services, particularly digital doctor consultations, has created a new paradigm in health care choice. While patients traditionally rely on digital reviews or referrals to select health care providers, the digital context often lacks such information, leading to reliance on visual cues such as profile pictures. Previous research has explored the impact of physical attractiveness in general service settings but is scant in the context of digital health care. Objective: This study aims to fill the research gap by investigating how a health care provider’s physical attractiveness influences patient preferences in a digital consultation setting. We also examine the moderating effects of disease severity and the availability of information on health care providers’ qualifications. The study uses signal theory and the sexual attribution bias framework to understand these dynamics. Methods: Three experimental studies were conducted to examine the influence of health care providers’ physical attractiveness and gender on patient preferences in digital consultations. Study 1 (n=282) used a 2×2 between-subjects factorial design, manipulating doctor attractiveness and gender. Study 2 (n=158) focused on women doctors and manipulated disease severity and participant gender. Study 3 (n=150) replicated study 2 but added information about the providers’ abilities. Results: This research found that patients tend to choose attractive doctors of the opposite gender but are less likely to choose attractive doctors of the same gender. In addition, our studies revealed that such an effect is more prominent when the disease severity is high. Furthermore, the influence of gender stereotypes is mitigated in both the high and low disease severity conditions when service providers’ qualification information is present. Conclusions: This research contributes to the literature on medical information systems research and sheds light on what information should be displayed on digital doctor consultation platforms. To counteract stereotype-based attractiveness biases, health care platforms should consider providing comprehensive qualification information alongside profile pictures. %M 38814690 %R 10.2196/46551 %U https://www.jmir.org/2024/1/e46551 %U https://doi.org/10.2196/46551 %U http://www.ncbi.nlm.nih.gov/pubmed/38814690 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e52646 %T Effect of Prosocial Behaviors on e-Consultations in a Web-Based Health Care Community: Panel Data Analysis %A Liu,Xiaoxiao %A Guo,Huijing %A Wang,Le %A Hu,Mingye %A Wei,Yichan %A Liu,Fei %A Wang,Xifu %+ Healthcare Simulation Center, Guangzhou First People’s Hospital, 1 Pan Fu Road, Yuexiu District, Guangzhou, 510180, China, 86 13560055951, wangxifu.simulation@gmail.com %K prosocial behaviors %K proactive behaviors %K reactive behaviors %K reputations %K e-consultation volume %K live streaming %D 2024 %7 25.4.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients using web-based health care communities for e-consultation services have the option to choose their service providers from an extensive digital market. To stand out in this crowded field, doctors in web-based health care communities often engage in prosocial behaviors, such as proactive and reactive actions, to attract more users. However, the effect of these behaviors on the volume of e-consultations remains unclear and warrants further exploration. Objective: This study investigates the impact of various prosocial behaviors on doctors’ e-consultation volume in web-based health care communities and the moderating effects of doctors’ digital and offline reputations. Methods: A panel data set containing information on 2880 doctors over a 22-month period was obtained from one of the largest web-based health care communities in China. Data analysis was conducted using a 2-way fixed effects model with robust clustered SEs. A series of robustness checks were also performed, including alternative measurements of independent variables and estimation methods. Results: Results indicated that both types of doctors’ prosocial behaviors, namely, proactive and reactive actions, positively impacted their e-consultation volume. In terms of the moderating effects of external reputation, doctors’ offline professional titles were found to negatively moderate the relationship between their proactive behaviors and their e-consultation volume. However, these titles did not significantly affect the relationship between doctors’ reactive behaviors and their e-consultation volume (P=.45). Additionally, doctors’ digital recommendations from patients negatively moderated both the relationship between doctors’ proactive behaviors and e-consultation volume and the relationship between doctors’ reactive behaviors and e-consultation volume. Conclusions: Drawing upon functional motives theory and social exchange theory, this study categorizes doctors’ prosocial behaviors into proactive and reactive actions. It provides empirical evidence that prosocial behaviors can lead to an increase in e-consultation volume. This study also illuminates the moderating roles doctors’ digital and offline reputations play in the relationships between prosocial behaviors and e-consultation volume. %M 38663006 %R 10.2196/52646 %U https://www.jmir.org/2024/1/e52646 %U https://doi.org/10.2196/52646 %U http://www.ncbi.nlm.nih.gov/pubmed/38663006 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e55199 %T Mining User Reviews From Hypertension Management Mobile Health Apps to Explore Factors Influencing User Satisfaction and Their Asymmetry: Comparative Study %A He,Yunfan %A Zhu,Wei %A Wang,Tong %A Chen,Han %A Xin,Junyi %A Liu,Yongcheng %A Lei,Jianbo %A Liang,Jun %+ Department of AI and IT, Second Affiliated Hospital, School of Medicine, Zhejiang University, 88 Jiefang Road, Shangcheng District, Hangzhou, 310000, China, 86 571 87783942, junl@zju.edu.cn %K hypertension management %K mobile health %K topic modeling %K satisfaction %K 2-factor model %K comparative study %D 2024 %7 28.3.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Hypertension significantly impacts the well-being and health of individuals globally. Hypertension management apps (HMAs) have been shown to assist patients in controlling blood pressure (BP), with their efficacy validated in clinical trials. However, the utilization of HMAs continues to be suboptimal. Presently, there is a dearth of real-world research based on big data and exploratory mining that compares Chinese and American HMAs. Objective: This study aims to systematically gather HMAs and their user reviews from both China and the United States. Subsequently, using data mining techniques, the study aims to compare the user experience, satisfaction levels, influencing factors, and asymmetry between Chinese and American users of HMAs. In addition, the study seeks to assess the disparities in satisfaction and its determinants while delving into the asymmetry of these factors. Methods: The study sourced HMAs and user reviews from 10 prominent Chinese and American app stores globally. Using the latent Dirichlet allocation (LDA) topic model, the research identified various topics within user reviews. Subsequently, the Tobit model was used to investigate the impact and distinctions of each topic on user satisfaction. The Wald test was applied to analyze differences in effects across various factors. Results: We examined a total of 261 HMAs along with their associated user reviews, amounting to 116,686 reviews in total. In terms of quantity and overall satisfaction levels, Chinese HMAs (n=91) and corresponding reviews (n=16,561) were notably fewer compared with their American counterparts (n=220 HMAs and n=100,125 reviews). The overall satisfaction rate among HMA users was 75.22% (87,773/116,686), with Chinese HMAs demonstrating a higher satisfaction rate (13,866/16,561, 83.73%) compared with that for American HMAs (73,907/100,125, 73.81%). Chinese users primarily focus on reliability (2165/16,561, 13.07%) and measurement accuracy (2091/16,561, 12.63%) when considering HMAs, whereas American users prioritize BP tracking (17,285/100,125, 17.26%) and data synchronization (12,837/100,125, 12.82%). Seven factors (easy to use: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; heart rate detection function: P=.02; blood pressure tracking function: P<.001; and interface design: P=.01) significantly influenced the positive deviation (PD) of Chinese HMA user satisfaction, while 8 factors (easy to use: P<.001; reliability: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; interface design: P<.001; real-time: P<.001; and data privacy: P=.001) affected the negative deviation (ND). Notably, BP tracking had the greatest effect on PD (β=.354, P<.001), while cost had the most significant impact on ND (β=3.703, P<.001). All 12 factors (easy to use: P<.001; blood pressure tracking function: P<.001; data synchronization: P<.001; blood pressure management effect: P<.001; heart rate detection function: P<.001; data sharing: P<.001; reliability: P<.001; compatibility: P<.001; interface design: P<.001; advertisement distribution: P<.001; measurement accuracy: P<.001; and cost: P<.001) significantly influenced the PD and ND of American HMA user satisfaction. Notably, BP tracking had the greatest effect on PD (β=0.312, P<.001), while data synchronization had the most significant impact on ND (β=2.662, P<.001). In addition, the influencing factors of PD and ND in user satisfaction of HMA in China and the United States are different. Conclusions: User satisfaction factors varied significantly between different countries, showing considerable asymmetry. For Chinese HMA users, ease of use and interface design emerged as motivational factors, while factors such as cost, measurement accuracy, and compatibility primarily contributed to user dissatisfaction. For American HMA users, motivational factors were ease of use, BP tracking, BP management effect, interface design, measurement accuracy, and cost. Moreover, users expect features such as data sharing, synchronization, software reliability, compatibility, heart rate detection, and nonintrusive advertisement distribution. Tailored experience plans should be devised for different user groups in various countries to address these diverse preferences and requirements. %M 38547475 %R 10.2196/55199 %U https://mhealth.jmir.org/2024/1/e55199 %U https://doi.org/10.2196/55199 %U http://www.ncbi.nlm.nih.gov/pubmed/38547475 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e45855 %T Youth is Prized in Medicine, Old Age is Valued in Law: Analysis of Media Narratives Over 200 Years %A Ng,Reuben %A Indran,Nicole %+ Lee Kuan Yew School of Public Policy, National University of Singapore, 469C Bukit Timah Road, Singapore, 259772, Singapore, 65 66013967, spprng@nus.edu.sg %K older professionals %K ageism %K media %K historical analysis %K reframe aging %K learned professions %K psychomics %D 2024 %7 26.3.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: This is the first study to explore how age has influenced depictions of doctors and lawyers in the media over the course of 210 years, from 1810 to 2019. The media represents a significant platform for examining age stereotypes and possesses tremendous power to shape public opinion. Insights could be used to improve depictions of older professionals in the media. Objective: This study aims to understand how age shapes the portrayals of doctors and lawyers. Specifically, it compares the difference in sentiments toward younger and older doctors as well as younger and older lawyers in the media over 210 years. Methods: Leveraging a 600-million-word corpus of American media publications spanning 210 years, we compiled top descriptors (N=478,452) of nouns related to youth × occupation (eg, younger doctor or physician) and old age × occupation (eg, older lawyer or attorney). These descriptors were selected using well-established criteria including co-occurrence frequency and context relevance, and were rated on a Likert scale from 1 (very negative) to 5 (very positive). Sentiment scores were generated for “doctor/physician,” “young(er) doctor/physician,” “old(er) doctor/physician,” “lawyer/attorney,” “young(er) lawyer/attorney,” and “old(er) lawyer/attorney.” The scores were calculated per decade for 21 decades from 1810 to 2019. Topic modeling was conducted on the descriptors of each occupation in both the 1800s and 1900s using latent Dirichlet allocation. Results: As hypothesized, the media placed a premium on youth in the medical profession, with portrayals of younger doctors becoming 10% more positive over 210 years, and those of older doctors becoming 1.4% more negative. Meanwhile, a premium was placed on old age in law. Positive portrayals of older lawyers increased by 22.6% over time, while those of younger lawyers experienced a 4.3% decrease. In the 1800s, narratives on younger doctors revolved around their participation in rural health care. In the 1900s, the focus shifted to their mastery of new medical technologies. There was no marked change in narratives surrounding older doctors from the 1800s to the 1900s, though less attention was paid to their skills in the 1900s. Narratives on younger lawyers in the 1800s referenced their limited experience. In the 1900s, there was more focus on courtroom affairs. In both the 1800s and 1900s, narratives on older lawyers emphasized their prestige, especially in the 1900s. Conclusions: Depending on the occupation, one’s age may either be seen as an asset or a liability. Efforts must be expended to ensure that older professionals are recognized for their wealth of knowledge and skills. Failing to capitalize on the merits of an older workforce could ultimately be a grave disservice not only to older adults but to society in general. %M 38530338 %R 10.2196/45855 %U https://www.jmir.org/2024/1/e45855 %U https://doi.org/10.2196/45855 %U http://www.ncbi.nlm.nih.gov/pubmed/38530338 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e46713 %T Effect of Negative Online Reviews and Physician Responses on Health Consumers’ Choice: Experimental Study %A Han,Xi %A Lin,Yongxi %A Han,Wenting %A Liao,Ke %A Mei,Kefu %+ School of Management Science and Engineering, Shandong University of Finance and Economics, 7366 Erhuan East Road, Yifu Building 5th FL., Jinan, 250014, China, 86 15951933930, hwt_2023@126.com %K negative review %K proportion %K claim type %K attribution theory %K physician-rating websites %K consumer %K physician response %D 2024 %7 12.3.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The COVID-19 pandemic has highlighted the importance of online medical services. Although some researchers have investigated how numerical ratings affect consumer choice, limited studies have focused on the effect of negative reviews that most concern physicians. Objective: This study aimed to investigate how negative review features, including proportion (low/high), claim type (evaluative/factual), and physician response (absence/presence), influence consumers’ physician evaluation process under conditions in which a physician’s overall rating is high. Methods: Using a 2×2×2 between-subject decision-controlled experiment, this study examined participants’ judgment on physicians with different textual reviews. Collected data were analyzed using the t test and partial least squares–structural equation modeling. Results: Negative reviews decreased consumers’ physician selection intention. The negative review proportion (β=–0.371, P<.001) and claim type (β=–0.343, P<.001) had a greater effect on consumers’ physician selection intention compared to the physician response (β=0.194, P<.001). A high negative review proportion, factual negative reviews, and the absence of a physician response significantly reduced consumers’ physician selection intention compared to their counterparts. Consumers’ locus attributions on the negative reviews affected their evaluation process. Physician attribution mediated the effects of review proportion (β=–0.150, P<.001), review claim type (β=–0.068, P=.01), and physician response (β=0.167, P<.001) on consumer choice. Reviewer attribution also mediated the effects of review proportion (β=–0.071, P<.001), review claim type (β=–0.025, P=.01), and physician response (β=0.096, P<.001) on consumer choice. The moderating effects of the physician response on the relationship between review proportion and physician attribution (β=–0.185, P<.001), review proportion and reviewer attribution (β=–0.110, P<.001), claim type and physician attribution (β=–0.123, P=.003), and claim type and reviewer attribution (β=–0.074, P=.04) were all significant. Conclusions: Negative review features and the physician response significantly influence consumer choice through the causal attribution to physicians and reviewers. Physician attribution has a greater effect on consumers’ physician selection intention than reviewer attribution does. The presence of a physician response decreases the influence of negative reviews through direct and moderating effects. We propose some practical implications for physicians, health care providers, and online medical service platforms. %M 38470465 %R 10.2196/46713 %U https://www.jmir.org/2024/1/e46713 %U https://doi.org/10.2196/46713 %U http://www.ncbi.nlm.nih.gov/pubmed/38470465 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e50152 %T Identification of Emotional Spectrums of Patients Taking an Erectile Dysfunction Medication: Ontology-Based Emotion Analysis of Patient Medication Reviews on Social Media %A Noh,Youran %A Kim,Maryanne %A Hong,Song Hee %+ College of Pharmacy, Seoul National University, Suite 20-322, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea, 82 2 880 1547, songhhong@snu.ac.kr %K erectile dysfunction %K PDE5 inhibitor %K social media %K emotion analysis %K sentiment analysis %K emotions %K patient medication experience %K tailored patient medication %K patient-centered care %K men's health %K medications %K drugs %D 2023 %7 29.11.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient medication reviews on social networking sites provide valuable insights into the experiences and sentiments of individuals taking specific medications. Understanding the emotional spectrum expressed by patients can shed light on their overall satisfaction with medication treatment. This study aims to explore the emotions expressed by patients taking phosphodiesterase type 5 (PDE5) inhibitors and their impact on sentiment. Objective: This study aimed to (1) identify the distribution of 6 Parrot emotions in patient medication reviews across different patient characteristics and PDE5 inhibitors, (2) determine the relative impact of each emotion on the overall sentiment derived from the language expressed in each patient medication review while controlling for different patient characteristics and PDE5 inhibitors, and (3) assess the predictive power of the overall sentiment in explaining patient satisfaction with medication treatment. Methods: A data set of patient medication reviews for sildenafil, vardenafil, and tadalafil was collected from 3 popular social networking sites such as WebMD, Ask-a-Patient, and Drugs.com. The Parrot emotion model, which categorizes emotions into 6 primary classes (surprise, anger, love, joy, sadness, and fear), was used to analyze the emotional content of the reviews. Logistic regression and sentiment analysis techniques were used to examine the distribution of emotions across different patient characteristics and PDE5 inhibitors and to quantify their contribution to sentiment. Results: The analysis included 3070 patient medication reviews. The most prevalent emotions expressed were joy and sadness, with joy being the most prevalent among positive emotions and sadness being the most prevalent among negative emotions. Emotion distributions varied across patient characteristics and PDE5 inhibitors. Regression analysis revealed that joy had the strongest positive impact on sentiment, while sadness had the most negative impact. The sentiment score derived from patient reviews significantly predicted patient satisfaction with medication treatment, explaining 19% of the variance (increase in R2) when controlling for patient characteristics and PDE5 inhibitors. Conclusions: This study provides valuable insights into the emotional experiences of patients taking PDE5 inhibitors. The findings highlight the importance of emotions in shaping patient sentiment and satisfaction with medication treatment. Understanding these emotional dynamics can aid health care providers in better addressing patient needs and improving overall patient care. %M 38019570 %R 10.2196/50152 %U https://www.jmir.org/2023/1/e50152 %U https://doi.org/10.2196/50152 %U http://www.ncbi.nlm.nih.gov/pubmed/38019570 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e52877 %T Authors’ Reply: “The Problem of Investigating Causal Relationships Between Cognitive and Evaluative Variables” %A Guetz,Bernhard %A Bidmon,Sonja %+ Carinthia University of Applied Sciences, Europastraße 4, Villach & Klagenfurt, 9524, Austria, 43 5905002453, guetz@fh-kaernten.at %K social influence %K physician rating websites %K patient satisfaction %K eHealth literacy %D 2023 %7 22.11.2023 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 37991815 %R 10.2196/52877 %U https://www.jmir.org/2023/1/e52877 %U https://doi.org/10.2196/52877 %U http://www.ncbi.nlm.nih.gov/pubmed/37991815 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e45570 %T The Problem of Investigating Causal Relationships Between Cognitive and Evaluative Variables %A Konerding,Uwe %+ Trimberg Research Academy, University of Bamberg, Otto-Friedrich-Universität Bamberg, Bamberg, D-96045, Germany, 49 951 863 3098, uwe.konerding@uni-bamberg.de %K social influence %K physician rating websites %K patient satisfaction %K eHealth literacy %D 2023 %7 22.11.2023 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 37991832 %R 10.2196/45570 %U https://www.jmir.org/2023/1/e45570 %U https://doi.org/10.2196/45570 %U http://www.ncbi.nlm.nih.gov/pubmed/37991832 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e38306 %T The Impact of Ambivalent Attitudes on the Helpfulness of Web-Based Reviews: Secondary Analysis of Data From a Large Physician Review Website %A Dong,Wei %A Liu,Yongmei %A Zhu,Zhangxiang %A Cao,Xianye %+ Business School, Central South University, Xiaoxiang Middle Road, Jiangwan Building, new campus of Central South University, Changsha, 410083, China, 86 13974834821, liuyongmeicn@163.com %K web-based review helpfulness %K ambivalent attitudes %K risk reduction %K the tripartite model of attitudes %K mobile phone %D 2023 %7 29.5.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Previously, most studies used 5-star and 1-star ratings to represent reviewers’ positive and negative attitudes, respectively. However, this premise is not always true because individuals’ attitudes have more than one dimension. In particular, given the credence traits of medical service, to build durable physician-patient relationships, patients may rate their physicians with high scores to avoid lowering their physicians’ web-based ratings and help build their physicians’ web-based reputations. Some patients may express complaints only in review texts, resulting in ambivalence, such as conflicting feelings, beliefs, and reactions toward physicians. Thus, web-based rating platforms for medical services may face more ambivalence than platforms for search or experience goods. Objective: On the basis of the tripartite model of attitudes and uncertainty reduction theory, this study aims to consider both the numerical rating and sentiment of each web-based review to explore whether there is ambivalence and how ambivalent attitudes influence the helpfulness of web-based reviews. Methods: This study collected 114,378 reviews of 3906 physicians on a large physician review website. Then, based on existing literature, we operationalized numerical ratings as the cognitive dimension of attitudes and sentiment in review texts as the affective dimension of attitudes. Several econometric models, including the ordinary least squares model, logistic regression model, and Tobit model, were used to test our research model. Results: First, this study confirmed the existence of ambivalence in each web-based review. Then, by measuring ambivalence through the inconsistency between the numerical rating and sentiment for each review, this study found that the ambivalence in different web-based reviews has a different impact on the helpfulness of the reviews. Specifically, for reviews with positive emotional valence, the higher the degree of inconsistency between the numerical rating and sentiment, the greater the helpfulness is (βpositive 1=.046; P<.001). For reviews with negative and neutral emotional valence, the impact is opposite, that is, the higher the degree of inconsistency between the numerical rating and sentiment, the lesser the helpfulness is (βnegative 1=−.059, P<.001; βneutral 1=−.030, P=.22). Considering the traits of the data, the results were also verified using the logistic regression model (θpositive 1=0.056, P=.005; θnegative 1=−0.080, P<.001; θneutral 1=−0.060, P=.03) and Tobit model. Conclusions: This study confirmed the existence of ambivalence between the cognitive and affective dimensions in single reviews and found that for reviews with positive emotional valence, the ambivalent attitudes lead to more helpfulness, but for reviews with negative and neutral emotion valence, the ambivalence attitudes lead to less helpfulness. The results contribute to the web-based review literature and inspire a better design for rating mechanisms in review websites to enhance the helpfulness of reviews. %M 37247213 %R 10.2196/38306 %U https://www.jmir.org/2023/1/e38306 %U https://doi.org/10.2196/38306 %U http://www.ncbi.nlm.nih.gov/pubmed/37247213 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e39857 %T The Use of Web-Based Patient Reviews to Assess Medical Oncologists’ Competency: Mixed Methods Sequential Explanatory Study %A Morena,Nina %A Zelt,Nicholas %A Nguyen,Diana %A Dionne,Emilie %A Rentschler,Carrie A %A Greyson,Devon %A Meguerditchian,Ari N %+ Art History and Communication Studies, McGill University, 853 Sherbrooke St W, Montreal, QC, H3A 2A7, Canada, 1 514 345 3511 ext 5060, nina.morena@mail.mcgill.ca %K web-based patient reviews %K medical oncology %K cancer care %K CanMEDS %K RateMDs %K web-based physician rating %K physician rating websites %D 2023 %7 4.5.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Patients increasingly use web-based evaluation tools to assess their physicians, health care teams, and overall medical experience. Objective: This study aimed to evaluate the extent to which the standardized physician competencies of the CanMEDS Framework are present in web-based patient reviews (WPRs) and to identify patients’ perception of important physician qualities in the context of quality cancer care. Methods: The WPRs of all university-affiliated medical oncologists in midsized cities with medical schools in the province of Ontario (Canada) were collected. Two reviewers (1 communication studies researcher and 1 health care professional) independently assessed the WPRs according to the CanMEDS Framework and identified common themes. Comment scores were then evaluated to identify κ agreement rates between the reviewers, and a descriptive quantitative analysis of the cohort was completed. Following the quantitative analysis, an inductive thematic analysis was performed. Results: This study identified 49 actively practicing university-affiliated medical oncologists in midsized urban areas in Ontario. A total of 473 WPRs reviewing these 49 physicians were identified. Among the CanMEDS competencies, those defining the roles of medical experts, communicators, and professionals were the most prevalent (303/473, 64%; 182/473, 38%; and 129/473, 27%, respectively). Common themes in WPRs include medical skill and knowledge, interpersonal skills, and answering questions (from the patient to the physician). Detailed WPRs tend to include the following elements: experience and connection; discussion and evaluation of the physician’s knowledge, professionalism, interpersonal skills, and punctuality; in positive reviews, the expression of feelings of gratitude and a recommendation; and in negative reviews, discouragement from seeking the physician’s care. Patients’ perception of medical skills is less specific than their perception of interpersonal qualities, although medical skills are the most commented-on element of care in WPRs. Patients’ perception of interpersonal skills (listening, compassion, and overall caring demeanor) and other experiential phenomena, such as feeling rushed during appointments, is often specific and detailed. Details about a physician’s interpersonal skills or “bedside manner” are highly perceived, valued, and shareable in an WPR context. A small number of WPRs reflected a distinction between the value of medical skills and that of interpersonal skills. The authors of these WPRs claimed that for them, a physician’s medical skills and competence are more important than their interpersonal skills. Conclusions: CanMEDS roles and competencies that are explicitly patient facing (ie, those directly experienced by patients in their interactions with physicians and through the care that physicians provide) are the most likely to be present and reported on in WPRs. The findings demonstrate the opportunity to learn from WPRs, not simply to discern physicians’ popularity but to grasp what patients may expect from their physicians. In this context, WPRs can represent a method for the measurement and assessment of patient-facing physician competency. %M 37140959 %R 10.2196/39857 %U https://formative.jmir.org/2023/1/e39857 %U https://doi.org/10.2196/39857 %U http://www.ncbi.nlm.nih.gov/pubmed/37140959 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 10 %N %P e39512 %T SARS-CoV-2–Related Adaptation Mechanisms of Rehabilitation Clinics Affecting Patient-Centered Care: Qualitative Study of Online Patient Reports %A Kühn,Lukas %A Lindert,Lara %A Kuper,Paulina %A Choi,Kyung-Eun Anna %+ Center for Health Services Research, Brandenburg Medical School, Seebad 82/83, Rüdersdorf bei Berlin, 15562, Germany, 49 015783035009, Lukas.Kuehn@mhb-fontane.de %K patient-led care %K patient autonomy %K patient report %K satisfaction %K pandemic %K coronavirus %K inpatient %K health care delivery %K service delivery %K rehabilitation %K internet %K web-based %K reviews %K complaint %K rating %K COVID-19 %D 2023 %7 13.4.2023 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: The SARS-CoV-2 pandemic impacted access to inpatient rehabilitation services. At the current state of research, it is unclear to what extent the adaptation of rehabilitation services to infection-protective standards affected patient-centered care in Germany. Objective: The aim of this study was to determine the most relevant aspects of patient-centered care for patients in inpatient rehabilitation clinics under early phase pandemic conditions. Methods: A deductive-inductive framework analysis of online patient reports posted on a leading German hospital rating website, Klinikbewertungen (Clinic Reviews), was performed. This website is a third-party, patient-centered commercial platform that operates independently of governmental entities. Following a theoretical sampling approach, online reports of rehabilitation stays in two federal states of Germany (Brandenburg and Saarland) uploaded between March 2020 and September 2021 were included. Independent of medical specialty groups, all reports were included. Keywords addressing framework domains were analyzed descriptively. Results: In total, 649 online reports reflecting inpatient rehabilitation services of 31 clinics (Brandenburg, n=23; Saarland, n=8) were analyzed. Keywords addressing the care environment were most frequently reported (59.9%), followed by staff prerequisites (33.0%), patient-centered processes (4.5%), and expected outcomes (2.6%). Qualitative in-depth analysis revealed SARS-CoV-2–related reports to be associated with domains of patient-centered processes and staff prerequisites. Discontinuous communication of infection protection standards was perceived to threaten patient autonomy. This was amplified by a tangible gratification crisis of medical staff. Established and emotional supportive relationships to clinicians and peer groups offered the potential to mitigate the adverse effects of infection protection standards. Conclusions: Patients predominantly reported feedback associated with the care environment. SARS-CoV-2–related reports were strongly affected by increased staff workloads as well as patient-centered processes addressing discontinuous communication and organizationally demanding implementation of infection protection standards, which were perceived to threaten patient autonomy. Peer relationships formed during inpatient rehabilitation had the potential to mitigate these mechanisms. %M 36947585 %R 10.2196/39512 %U https://rehab.jmir.org/2023/1/e39512 %U https://doi.org/10.2196/39512 %U http://www.ncbi.nlm.nih.gov/pubmed/36947585 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e39259 %T The Influence of Paid Memberships on Physician Rating Websites With the Example of the German Portal Jameda: Descriptive Cross-sectional Study %A Armbruster,Friedrich Aaron David %A Brüggmann,Dörthe %A Groneberg,David Alexander %A Bendels,Michael %+ Institute of Occupational, Social and Environmental Medicine, Goethe University, Theodor-Stern-Kai 7, Frankfurt, 60590, Germany, 49 6963016650, s3357030@stud.uni-frankfurt.de %K physician rating websites %K physician rating portals %K paid influence %K Germany %D 2023 %7 4.4.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The majority of Germans see a deficit in information availability for choosing a physician. An increasing number of people use physician rating websites and decide upon the information provided. In Germany, the most popular physician rating website is Jameda.de, which offers monthly paid membership plans. The platform operator states that paid memberships have no influence on the rating indicators or list placement. Objective: The goal of this study was to investigate whether a physician’s membership status might be related to his or her quantitative evaluation factors and to possibly quantify these effects. Methods: Physician profiles were retrieved through the search mask on Jameda.de website. Physicians from 8 disciplines in Germany’s 12 most populous cities were specified as search criteria. Data Analysis and visualization were done with Matlab. Significance testing was conducted using a single factor ANOVA test followed by a multiple comparison test (Tukey Test). For analysis, the profiles were grouped according to member status (nonpaying, Gold, and Platinum) and analyzed according to the target variables—physician rating score, individual patient’s ratings, number of evaluations, recommendation quota, number of colleague recommendations, and profile views. Results: A total of 21,837 nonpaying profiles, 2904 Gold, and 808 Platinum member profiles were acquired. Statistically significant differences were found between paying (Gold and Platinum) and nonpaying profiles in all parameters we examined. The distribution of patient reviews differed also by membership status. Paying profiles had more ratings, a better overall physician rating, a higher recommendation quota, and more colleague recommendations, and they were visited more frequently than nonpaying physicians’ profiles. Statistically significant differences were found in most evaluation parameters within the paid membership packages in the sample analyzed. Conclusions: Paid physician profiles could be interpreted to be optimized for decision-making criteria of potential patients. With our data, it is not possible to draw any conclusions of mechanisms that alter physicians’ ratings. Further research is needed to investigate the causes for the observed effects. %M 37014690 %R 10.2196/39259 %U https://www.jmir.org/2023/1/e39259 %U https://doi.org/10.2196/39259 %U http://www.ncbi.nlm.nih.gov/pubmed/37014690 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e38932 %T Web-Based Public Ratings of General Practitioners in Norway: Validation Study %A Bjertnæs,Øyvind %A Iversen,Hilde Hestad %A Norman,Rebecka %A Valderas,Jose M %+ Norwegian Institute of Public Health, Sandakerveien 24c, Bygg D, Oslo, 0473, Norway, 47 91176045, oyvindandresen.bjertnaes@fhi.no %K web-based rating %K questionnaire %K psychometric %K patient-reported experiences and satisfaction %K survey %K health care %K practitioner %K doctor rating %K physician rating %K patient provider %K patient experience %K patient satisfaction %D 2023 %7 17.3.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Understanding the complex relationships among multiple strategies for gathering users’ perspectives in the evaluation of the performance of services is crucial for the interpretation of user-reported measures. Objective: The main objectives were to (1) evaluate the psychometric performance of an 11-item web-based questionnaire of ratings of general practitioners (GPs) currently used in Norway (Legelisten.no) and (2) assess the association between web-based and survey-based patient experience indicators. Methods: We included all published ratings on GPs and practices on Legelisten.no in the period of May 5, 2012, to December 15, 2021 (N=76,521). The questionnaire consists of 1 mandatory item and 10 voluntary items with 5 response categories (1 to 5 stars), alongside an open-ended review question and background variables. Questionnaire dimensionality and internal consistency were assessed with Cronbach α, exploratory factor, and item response theory analyses, and a priori hypotheses were developed for assessing construct validity (chi-square analysis). We calculated Spearman correlations between web-based ratings and reference patient experience indicators based on survey data using the patient experiences with the GP questionnaire (n=5623 respondents for a random sample of 50 GPs). Results: Web-based raters were predominantly women (n=32,074, 64.0%), in the age range of 20-50 years (n=35,113, 74.6%), and reporting 5 or fewer consultations with the GP each year (n=28,798, 64.5%). Ratings were missing for 18.9% (n=14,500) to 27.4% (n=20,960) of nonmandatory items. A total of 4 of 11 rating items showed a U-shaped distribution, with >60% reporting 5 stars. Factor analysis and internal consistency testing identified 2 rating scales: “GP” (5 items; α=.98) and “practice” (6 items; α=.85). Some associations were not consistent with a priori hypotheses and allowed only partial confirmation of the construct validity of ratings. Item response theory analysis results were adequate for the “practice” scale but not for the “GP” scale, with items with inflated discrimination (>5) distributed over a narrow interval of the scale. The correlations between the web-based ratings GP scale and GP reference indicators ranged from 0.34 (P=.021) to 0.44 (P=.002), while the correlation between the web-based ratings practice scale and reference indicators ranged from 0.17 (not significant) to 0.49 (P<.001). The strongest correlations between web-based and survey scores were found for items measuring practice-related experiences: phone availability (ρ=0.51), waiting time in the office (ρ=0.62), other staff (ρ=0.54-0.58; P<.001). Conclusions: The practice scale of the web-based ratings has adequate psychometric performance, while the GP suffers from important limitations. The associations with survey-based patient experience indicators were accordingly mostly weak to modest. Our study underlines the importance of interpreting web-based ratings with caution and the need to further develop rating sites. %M 36930207 %R 10.2196/38932 %U https://formative.jmir.org/2023/1/e38932 %U https://doi.org/10.2196/38932 %U http://www.ncbi.nlm.nih.gov/pubmed/36930207 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e42231 %T Safety Concerns in Mobility-Assistive Products for Older Adults: Content Analysis of Online Reviews %A Mali,Namrata %A Restrepo,Felipe %A Abrahams,Alan %A Sands,Laura %A Goldberg,David M %A Gruss,Richard %A Zaman,Nohel %A Shields,Wendy %A Omaki,Elise %A Ehsani,Johnathon %A Ractham,Peter %A Kaewkitipong,Laddawan %+ Center of Excellence in Operations and Information Management, Thammasat Business School, Thammasat University, 2 Prachan Rd., Pranakorn, Bangkok, 10200, Thailand, 66 26132200, laddawan@tbs.tu.ac.th %K injury prevention %K consumer-reported injuries %K older adults %K online reviews %K mobility-assistive devices %K product failures %D 2023 %7 2.3.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Older adults who have difficulty moving around are commonly advised to adopt mobility-assistive devices to prevent injuries. However, limited evidence exists on the safety of these devices. Existing data sources such as the National Electronic Injury Surveillance System tend to focus on injury description rather than the underlying context, thus providing little to no actionable information regarding the safety of these devices. Although online reviews are often used by consumers to assess the safety of products, prior studies have not explored consumer-reported injuries and safety concerns within online reviews of mobility-assistive devices. Objective: This study aimed to investigate injury types and contexts stemming from the use of mobility-assistive devices, as reported by older adults or their caregivers in online reviews. It not only identified injury severities and mobility-assistive device failure pathways but also shed light on the development of safety information and protocols for these products. Methods: Reviews concerning assistive devices were extracted from the “assistive aid” categories, which are typically intended for older adult use, on Amazon’s US website. The extracted reviews were filtered so that only those pertaining to mobility-assistive devices (canes, gait or transfer belts, ramps, walkers or rollators, and wheelchairs or transport chairs) were retained. We conducted large-scale content analysis of these 48,886 retained reviews by coding them according to injury type (no injury, potential future injury, minor injury, and major injury) and injury pathway (device critical component breakage or decoupling; unintended movement; instability; poor, uneven surface handling; and trip hazards). Coding efforts were carried out across 2 separate phases in which the team manually verified all instances coded as minor injury, major injury, or potential future injury and established interrater reliability to validate coding efforts. Results: The content analysis provided a better understanding of the contexts and conditions leading to user injury, as well as the severity of injuries associated with these mobility-assistive devices. Injury pathways—device critical component failures; unintended device movement; poor, uneven surface handling; instability; and trip hazards—were identified for 5 product types (canes, gait and transfer belts, ramps, walkers and rollators, and wheelchairs and transport chairs). Outcomes were normalized per 10,000 posting counts (online reviews) mentioning minor injury, major injury, or potential future injury by product category. Overall, per 10,000 reviews, 240 (2.4%) described mobility-assistive equipment–related user injuries, whereas 2318 (23.18%) revealed potential future injuries. Conclusions: This study highlights mobility-assistive device injury contexts and severities, suggesting that consumers who posted online reviews attribute most serious injuries to a defective item, rather than user misuse. It implies that many mobility-assistive device injuries may be preventable through patient and caregiver education on how to evaluate new and existing equipment for risk of potential future injury. %M 36862459 %R 10.2196/42231 %U https://www.jmir.org/2023/1/e42231 %U https://doi.org/10.2196/42231 %U http://www.ncbi.nlm.nih.gov/pubmed/36862459 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e39034 %T User Experience Regarding Digital Primary Health Care in Santarém, Amazon: Evaluation of Patient Satisfaction and Doctor’s Feedback %A Bin,Kaio Jia %A Santana Alves,Patrícia Gabriela %A Costa,Raquel %A Eiras,Paula Cruz %A Nader de Araujo,Luciano %A Pereira,Antonio José Rodrigues %A Carvalho,Carlos %A Malik,Ana Maria %+ Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, R. Dr. Ovídio Pires de Campos, 225 - 3º andar, São Paulo, 05403-110, Brazil, 55 1126616208, kaiobin@gmail.com %K telemedicine %K primary health care %K user’s experience %K Amazon %K digital health %K pilot %K patient %K pilot model %K pandemic %K medical care %K assist %K urban %K community %K Brazil %K technology %K consultation %K physician %K survey %D 2023 %7 11.1.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: With the arrival of the pandemic, telemedicine has been widely used to provide medical care and can be used to assist patients in regions far from urban centers that are difficult to access, such as riverside communities in the Brazilian Amazon region. A telemedicine project connecting São Paulo, a mega-metropolis, to Paysandú, a riverside district in the Amazon, was built to serve the local population where access to the nearest medical care is 6 hours away by speedboat. Objective: This study aims to assess the feedback from patients and doctors regarding the use of telemedicine in outpatient care at Paysandú, a riverside district in the Amazon. Methods: This is a single-center study following the guidelines “Evaluating digital health products” from Public Health England, with local adaptations for the project and the Brazilian reality, that was conducted between São Paulo and Santarém in Brazil. A survey was carried out with patients who were treated by a doctor in the city of São Paulo, about 2500 km from the local basic health unit, between September 27 to December 15, 2021. At the end of each teleconsultation, the attending physician answered an administrative survey form, and the patient answered a satisfaction survey. Results: A total of 111 patients completed the satisfaction survey from a total of 220 consultations carried out during the period (95% CI margin error 0.22%). According to the survey, more than 95% of patients were satisfied with the service, 87.4% (n=97) had previous experience with videoconferencing, and 76.6% (n=85) reported that their demand was fully solved. Additionally, according to the hired doctor’s feedback, the average duration of the consultations was between 15 and 20 minutes. Of the 220 teleconsultations performed, 90.9% (n=200) of the demands were solved with support from the local health team, and 99.1% (n=218) of the appointments had a problem with audio or video. Conclusions: This teleconsultation project between São Paulo and Paysandú showed that it is possible to offer medical care from more developed locations to communities far from urban centers, as is the case with Paysandú District. Beyond the feasibility of the infrastructure, acceptance and satisfaction among patients were high. This health care supply model has proven to be functional and should be expanded nationally or perhaps internationally to regions lacking medical assistance. Escalation of the project does not seem too difficult once infrastructure issues are solved. %M 36630164 %R 10.2196/39034 %U https://formative.jmir.org/2023/1/e39034 %U https://doi.org/10.2196/39034 %U http://www.ncbi.nlm.nih.gov/pubmed/36630164 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 11 %P e37505 %T The Impact of Social Influence on the Intention to Use Physician Rating Websites: Moderated Mediation Analysis Using a Mixed Methods Approach %A Guetz,Bernhard %A Bidmon,Sonja %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 6508611182, beguetz@edu.aau.at %K social influence %K eHealth literacy %K patient satisfaction %K physician rating websites %D 2022 %7 14.11.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRWs) have become increasingly important in the cross-section between health and digitalization. Social influence plays a crucial role in human behavior in many domains of life, as can be demonstrated by the increase in high-profile influential individuals such as social media influencers (SMIs). Particularly in the health-specific environment, the opinion of family and friends has a significant influence on health-related decisions. However, so far, there has been little discussion about the role of social influence as an antecedent of behavioral intention to use PRWs. Objective: On the basis of theories of social psychology and technology acceptance and theories from the economic perspective, this study aimed to evaluate the impact of social influence on the behavioral intention to use PRWs. Methods: We conducted 2 studies by applying a mixed methods approach including a total of 712 participants from the Austrian population. The impact of social influence on the behavioral intention to use PRWs was investigated through linear regression and mediation and moderated mediation analysis using the PROCESS macro 4.0 in SPSS 27 (IBM Corp). Results: The 2 studies show similar results. In study 1, an experiment, no direct effect of social influence on the behavioral intention to use PRWs could be detected. However, an indirect effect of social influence on the behavioral intention to use PRWs via credibility (b=0.572; P=.005) and performance expectancy (b=0.340; P<.001) could be confirmed. The results of study 2, a cross-sectional study, demonstrate that social influence seems to have a direct impact on the behavioral intention to use PRWs (b=0.410; P<.001). However, when calculating the proposed mediation model, it becomes clear that this impact may partly be explained through the 2 mediator variables—credibility (b=0.208; P<.001) and performance expectancy (b=0.312; P<.001). In contrast to the observed direct and indirect effect, neither demographic nor psychographic variables have a significant moderating impact on the influencing chain in study 2. Conclusions: This study provides an indication that social influence has at least an indirect impact on the behavioral intention to use PRWs. It was observed that this impact is exerted through credibility and performance expectancy. According to the findings of both studies, social influence has the potential to boost the use of PRWs. As a result, these web-based networks might be a promising future interface between health care and digitalization, allowing health care practitioners to gain a beneficial external impact while also learning from feedback. Social influence nowadays is not just limited to friends and family but can also be exerted by SMIs in the domain of PRW use. Thus, from a marketing perspective, PRW providers could think of collaborating with SMIs, and our results could contribute to stimulating discussion in this vein. %M 36374547 %R 10.2196/37505 %U https://www.jmir.org/2022/11/e37505 %U https://doi.org/10.2196/37505 %U http://www.ncbi.nlm.nih.gov/pubmed/36374547 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 9 %P e34902 %T Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study %A Barnett,Julia %A Bjarnadóttir,Margrét Vilborg %A Anderson,David %A Chen,Chong %+ Technology and Social Behavior, Northwestern University, 2240 Campus Drive, Room 2-168 (Attention: Dept of Comm Studies), Evanston, IL, 60208, United States, 1 847 491 7530, JuliaBarnett@u.northwestern.edu %K gender %K natural language processing %K web-based reviews %K physician ratings by customer %K text mining %D 2022 %7 8.9.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Previous studies have highlighted gender differences in web-based physician reviews; however, so far, no study has linked web-based ratings with quality of care. Objective: We compared a consumer-generated measure of physician quality (web-based ratings) with a clinical quality outcome (sanctions for malpractice or improper behavior) to understand how patients’ perceptions and evaluations of physicians differ based on the physician’s gender. Methods: We used data from a large web-based physician review website and the Federation of State Medical Boards. We implemented paragraph vector methods to identify words that are specific to and indicative of separate groups of physicians. Then, we enriched these findings by using the National Research Council Canada word-emotion association lexicon to assign emotional scores to reviews for different subpopulations according to gender, gender and sanction, and gender and rating. Results: We found statistically significant differences in the sentiment and emotion of reviews between male and female physicians. Numerical ratings are lower and sentiment in text reviews is more negative for women who will be sanctioned than for men who will be sanctioned; sanctioned male physicians are still associated with positive reviews. Conclusions: Given the growing impact of web-based reviews on demand for physician services, understanding the different dynamics of reviews for male and female physicians is important for consumers and platform architects who may revisit their platform design. %M 36074543 %R 10.2196/34902 %U https://formative.jmir.org/2022/9/e34902 %U https://doi.org/10.2196/34902 %U http://www.ncbi.nlm.nih.gov/pubmed/36074543 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 7 %P e34030 %T Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings %A Ramasubramanian,Hari %A Joshi,Satish %A Krishnan,Ranjani %+ Accounting Department, Frankfurt School of Finance and Management, 32-34 Adickesallee, Frankfurt am Main, 60320, Germany, 49 69154008823, h.ramasubramanian@fs.de %K hospital quality %K web-based rating %K online ratings %K Hospital Compare %K star ratings %D 2022 %7 26.7.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Popular web-based portals provide free and convenient access to user-generated hospital quality reviews. The Centers for Medicare & Medicaid Services (CMS) also publishes Hospital Compare Star Ratings (HCSR), a comprehensive expert rating of US hospital quality that aggregates multiple measures of quality. CMS revised the HCSR methods in 2021. It is important to analyze the degree to which web-based ratings reflect expert measures of hospital quality because easily accessible, crowdsourced hospital ratings influence consumers’ hospital choices. Objective: This study aims to assess the association between web-based, Google hospital quality ratings that reflect the opinions of the crowd and HCSR representing the wisdom of the experts, as well as the changes in these associations following the 2021 revision of the CMS rating system. Methods: We extracted Google star ratings using the Application Programming Interface in June 2020. The HCSR data of April 2020 (before the revision of HCSR methodology) and April 2021 (after the revision of HCSR methodology) were obtained from the CMS Hospital Compare website. We also extracted scores for the individual components of hospital quality for each of the hospitals in our sample using the code provided by Hospital Compare. Fractional response models were used to estimate the association between Google star ratings and HCSR as well as individual components of quality (n=2619). Results: The Google star ratings are statistically associated with HCSR (P<.001) after controlling for hospital-level effects; however, they are not associated with clinical components of HCSR that require medical expertise for evaluation such as safety of care (P=.30) or readmission (P=.52). The revised CMS rating system ameliorates previous partial inconsistencies in the association between Google star ratings and quality component scores of HCSR. Conclusions: Crowdsourced Google star hospital ratings are informative regarding expert CMS overall hospital quality ratings and individual quality components that are easier for patients to evaluate. Improvements in hospital quality metrics that require expertise to assess, such as safety of care and readmission, may not lead to improved Google star ratings. Hospitals can benefit from using crowdsourced ratings as timely and easily available indicators of their quality performance while recognizing their limitations and biases. %M 35881418 %R 10.2196/34030 %U https://www.jmir.org/2022/7/e34030 %U https://doi.org/10.2196/34030 %U http://www.ncbi.nlm.nih.gov/pubmed/35881418 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 4 %P e31659 %T Physician Gender, Patient Risk, and Web-Based Reviews: Longitudinal Study of the Relationship Between Physicians’ Gender and Their Web-Based Reviews %A Saifee,Danish Hasnain %A Hudnall,Matthew %A Raja,Uzma %+ Department of Information Systems, Statistics, and Management Science, The University of Alabama, 801 University Blvd, Tuscaloosa, AL, 35487-0290, United States, 1 205 348 0856, matthew.hudnall@ua.edu %K web-based physician reviews %K gender %K gender bias %K patient perception %K Alabama %K patient risk %D 2022 %7 8.4.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Web-based reviews of physicians have become exceedingly popular among health care consumers since the early 2010s. A factor that can potentially influence these reviews is the gender of the physician, because the physician’s gender has been found to influence patient-physician communication. Our study is among the first to conduct a rigorous longitudinal analysis to study the effects of the gender of physicians on their reviews, after accounting for several important clinical factors, including patient risk, physician specialty, and temporal factors, using time fixed effects. In addition, this study is among the first to study the possible gender bias in web-based reviews using statewide data from Alabama, a predominantly rural state with high Medicaid and Medicare use. Objective: This study conducts a longitudinal empirical investigation of the relationship between physician gender and their web-based reviews using data across the state of Alabama, after accounting for patient risk and temporal effects. Methods: We created a unique data set by combining data from web-based physician reviews from the popular physician review website, RateMDs, and clinical data from the Center for Medicare and Medicaid Services for the state of Alabama. We used longitudinal econometric specifications to conduct an econometric analysis, while controlling for several important clinical and review characteristics across four rating dimensions (helpfulness, knowledge, staff, and punctuality). The overall rating and these four rating dimensions from RateMDs were used as the dependent variables, and physician gender was the key explanatory variable in our panel regression models. Results: The panel used to conduct the main econometric analysis included 1093 physicians. After controlling for several clinical and review factors, the physician random effects specifications showed that male physicians receive better web-based ratings than female physicians. Coefficients and corresponding SEs and P values of the binary variable GenderFemale (1 for female physicians and 0 otherwise) with different rating variables as outcomes were as follows: OverallRating (coefficient –0.194, SE 0.060; P=.001), HelpfulnessRating (coefficient –0.221, SE 0.069; P=.001), KnowledgeRating (coefficient –0.230, SE 0.065; P<.001), StaffRating (coefficient –0.123, SE 0.062; P=.049), and PunctualityRating (coefficient –0.200, SE 0.067; P=.003). The negative coefficients indicate a bias toward male physicians versus female physicians for aforementioned rating variables. Conclusions: This study found that female physicians receive lower web-based ratings than male physicians even after accounting for several clinical characteristics associated with the physicians and temporal effects. Although the magnitude of the coefficients of GenderFemale was relatively small, they were statistically significant. This study provides support to the findings on gender bias in the existing health care literature. We contribute to the existing literature by conducting a study using data across the state of Alabama and using a longitudinal econometric analysis, along with incorporating important clinical and review controls associated with the physicians. %M 35394435 %R 10.2196/31659 %U https://www.jmir.org/2022/4/e31659 %U https://doi.org/10.2196/31659 %U http://www.ncbi.nlm.nih.gov/pubmed/35394435 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e28379 %T Patient Experience and Satisfaction in Online Reviews of Obstetric Care: Observational Study %A Seltzer,Emily K %A Guntuku,Sharath Chandra %A Lanza,Amy L %A Tufts,Christopher %A Srinivas,Sindhu K %A Klinger,Elissa V %A Asch,David A %A Fausti,Nick %A Ungar,Lyle H %A Merchant,Raina M %+ Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut St, Philadelphia, PA, 19103, United States, 1 215 615 3211, sharathg@seas.upenn.edu %K patient satisfaction %K Yelp %K online reviews %K labor and delivery %K ob-gyn %K quality improvement %K machine learning %K labor %K delivery %K natural language processing %K maternal health %K ML %K patients %K obstetrics %D 2022 %7 31.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The quality of care in labor and delivery is traditionally measured through the Hospital Consumer Assessment of Healthcare Providers and Systems but less is known about the experiences of care reported by patients and caregivers on online sites that are more easily accessed by the public. Objective: The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp. Methods: We identified all Yelp reviews of US hospitals posted online from May 2005 to March 2017. We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson r to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. Results: A total of 1569 hospitals listed in the American Hospital Association directory had at least one Yelp posting, contributing a total of 41,095 Yelp reviews. Among those hospitals, 919 (59%) had at least one Yelp rating for labor and delivery services (median of 9 reviews), contributing a total of 6523 labor and delivery reviews. Reviews concentrated among 5-star (n=2643, 41%) and 1-star reviews (n=1934, 30%). Themes strongly associated with favorable ratings included the following: top-notch care (r=0.45, P<.001), describing staff as comforting (r=0.52, P<.001), the delivery experience (r=0.46, P<.001), modern and clean facilities (r=0.44, P<.001), and hospital food (r=0.38, P<.001). Themes strongly correlated with 1-star labor and delivery reviews included complaints to management (r=0.30, P<.001), a lack of agency among patients (r=0.47, P<.001), and issues with discharging from the hospital (r=0.32, P<.001). Conclusions: Online review content about labor and delivery can provide meaningful information about patient satisfaction and experiences. Narratives from these reviews that are not otherwise captured in traditional surveys can direct efforts to improve the experience of obstetrical care. %M 35357310 %R 10.2196/28379 %U https://formative.jmir.org/2022/3/e28379 %U https://doi.org/10.2196/28379 %U http://www.ncbi.nlm.nih.gov/pubmed/35357310 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e25275 %T The Mediating Role of Patients’ Trust Between Web-Based Health Information Seeking and Patients’ Uncertainty in China: Cross-sectional Web-Based Survey %A Dong,Wei %A Lei,Xiangxi %A Liu,Yongmei %+ School of Business, Central South University, 932 Lushan South Road, Changsha, 410083, China, 86 13974834821, liuyongmeicn@163.com %K patient trust %K online health information quality %K online word-of-mouth %K patient uncertainty %K principal-agent theory %K physician-patient relationship %D 2022 %7 11.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: In the physician-patient relationship, patients’ uncertainty about diseases and the lack of trust in physicians not only hinder patients’ rehabilitation but also disrupt the harmony in this relationship. With the development of the web-based health industry, patients can easily access web-based information about health care and physicians, thus reducing patients’ uncertainty to some extent. However, it is not clear how patients’ web-based health information–seeking behaviors reduce their uncertainty. Objective: On the basis of the principal-agent theory and the perspective of uncertainty reduction, this study aims to investigate the mechanism of how web-based disease-related information and web-based physician-related information reduce patients’ uncertainty. Methods: A web-based survey involving 337 participants was conducted. In this study, we constructed a structural equation model and used SmartPLS (version 3.3.3; SmartPLS GmbH) software to test the reliability and validity of the measurement model. The path coefficients of the structural model were also calculated to test our hypotheses. Results: By classifying patients’ uncertainties into those concerning diseases and those concerning physicians, this study identified the different roles of the two types of patients’ uncertainty and revealed that web-based disease-related information quality and web-based physician-related information can act as uncertainty mitigators. The quality of disease-related information reduces patients’ perceived information scarcity about the disease (β=−.588; P<.001), and the higher the information scarcity perceived by patients, the higher their uncertainty toward the disease (β=.111; P=.02). As for physician-related information, web-based word-of-mouth information about physicians reduces patients’ perceived information scarcity about the physician (β=−.511; P<.001), mitigates patients’ fears about physician opportunism (β=−.268; P<.001), and facilitates patients’ trust (β=.318; P<.001). These factors further influence patients’ uncertainty about the physician. In addition, from the test of mediating effect, patients’ trust in the physician fully mediates the relationship between their perceived information scarcity about the physician’s medical service and their uncertainty about the physician. Patients’ trust also partially mediates the relationship between their fear of the physician’s opportunism and their uncertainty about the physician. As for the two different types of uncertainty, patients’ uncertainty about the physician also increases their uncertainty about the diseases (β=.587; P<.001). Conclusions: This study affirms the role of disease-related web-based information quality and physician-related web-based word-of-mouth information in reducing patients’ uncertainties. With regard to the traits of principal-agent relationships, this study describes the influence mechanism based on patients’ perceived information scarcity, fears of physicians’ opportunism, and patients’ trust. Moreover, information about physicians is effective in reducing patients’ uncertainties, but only if the information enhances patients’ trust in their physicians. This research generates new insights into understanding the impact of web-based health information on patients’ uncertainties. %M 35275074 %R 10.2196/25275 %U https://www.jmir.org/2022/3/e25275 %U https://doi.org/10.2196/25275 %U http://www.ncbi.nlm.nih.gov/pubmed/35275074 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 2 %P e23354 %T The Effect of Online Health Information Seeking on Physician-Patient Relationships: Systematic Review %A Luo,Aijing %A Qin,Lu %A Yuan,Yifeng %A Yang,Zhengzijin %A Liu,Fei %A Huang,Panhao %A Xie,Wenzhao %+ Key Laboratory of Medical Information Research, The Third Xiangya Hospital, Central South University, No.138 Tongzipo Road, Changsha, 410013, China, 86 0731 8861 8316, xie_wenzhao@126.com %K online health information %K search behavior %K physician-patient relationship %K physician-patient consultation. %D 2022 %7 10.2.2022 %9 Review %J J Med Internet Res %G English %X Background: The internet has now become part of human life and is constantly changing people's way of life. With the increasing popularity of online health information (OHI), it has been found that OHI can affect the physician-patient relationship by influencing patient behaviors. Objective: This study aims to systematically investigate the impact of OHI-seeking behavior on the physician-patient relationship. Methods: Literature retrieval was conducted on 4 databases (Web of Science, PubMed, China National Knowledge Infrastructure, SinoMed), and the time limit for literature publication was before August 1, 2021. Results: We selected 53 target papers (42 [79%] English papers and 11 [21%] Chinese papers) that met the inclusion criteria. Of these, 31 (58%) papers believe that patients’ OHI behavior can enable them to participate in their own medical care, improve patient compliance, and improve the physician-patient relationship. In addition, 14 (26%) papers maintain a neutral attitude, some believing that OHI behavior has no significant effect on doctors and patients and others believing that due to changes in the factors affecting OHI behavior, they will have a negative or a positive impact. Furthermore, 8 (15%) papers believe that OHI search behavior has a negative impact on doctors and patients, while 6 (11%) papers show that OHI reduces Chinese patients’ trust in doctors. Conclusions: Our main findings showed that (1) OHI-seeking behavior has an impact on patients' psychology, behavior, and evaluation of doctors; (2) whether patients choose to discuss OHI with doctors has different effects on the physician-patient relationship; and (3) the negative impact of OHI on China’s internet users is worthy of attention. Due to the low quality of OHI, poor health information literacy, short physician-patient communication time, and various types of negative news, patients' trust in doctors has declined, thus affecting the physician-patient relationship. Improvement of people's health information literacy and the quality of OHI are important factors that promote the positive impact of OHI on the physician-patient relationship. %M 35142620 %R 10.2196/23354 %U https://www.jmir.org/2022/2/e23354 %U https://doi.org/10.2196/23354 %U http://www.ncbi.nlm.nih.gov/pubmed/35142620 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 1 %P e22586 %T Patient Utilization of Online Information and its Influence on Orthopedic Surgeon Selection: Cross-sectional Survey of Patient Beliefs and Behaviors %A Hoang,Victor %A Parekh,Amit %A Sagers,Kevin %A Call,Trevor %A Howard,Shain %A Hoffman,Jason %A Lee,Daniel %+ Valley Hospital Medical Center, 620 Shadow Lane, Las Vegas, NV, 89106, United States, 1 7148374577, hoangorthopedics@gmail.com %K orthopedics %K practice management %K physician selection %K internet reviews %K patient decision %K practice %K patient online review %K social media %K physician perception %K patient choice %K health literacy %D 2022 %7 19.1.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Patient attitudes and behavior are critical to understand owing to the increasing role of patient choice. There is a paucity of investigation into the perceived credibility of online information and whether such information impacts how patients choose their surgeons. Objective: The purpose of this study was to explore the attitudes and behavior of patients regarding online information and orthopedic surgeon selection. Secondary purposes included gaining insight into the relative importance of provider selection factors, and their association with patient age and education level. Methods: This was a cross-sectional study involving five multispecialty orthopedic surgery groups. A total of 329 patients who sought treatment by six different orthopedic surgeons were asked to anonymously answer a questionnaire consisting of 25 questions. Four questions regarded demographic information, 10 questions asked patients to rate the importance of specific criteria regarding the selection of their orthopedic surgeon (on a 4-point Likert scale), and 6 questions were designed to determine patient attitude and behaviors related to online information. Results: Patient-reported referral sources included the emergency room (29/329, 8.8%), friend (42/329, 12.8%), insurance company (47/329, 14.3%), internet search/website (28/329, 8.5%), primary care physician (148/329, 45.0%), and other (34/329, 10.3%). Among the 329 patients, 130 (39.5%) reported that they searched the internet for information before their first visit. There was a trend of increased belief in online information to be accurate and complete in younger age groups (P=.02). There was an increased relative frequency in younger groups to perceive physician rating websites to be unbiased (P=.003), provide sufficient patient satisfaction information (P=.01), and information about physician education and training (P=.03). There was a significant trend for patients that found a surgeon’s website to be useful (P<.001), with the relative frequency increased in younger age groups. Conclusions: This study shows that insurance network, physician referrals, appointment availability, and office location are important to patients, whereas advertising and internet reviews by other patients were considered to be not as helpful in choosing an orthopedic surgeon. Future studies may seek to identify obstacles to patients in integrating online resources for decision-making and strategies to improve health-seeking behaviors. %M 35044319 %R 10.2196/22586 %U https://formative.jmir.org/2022/1/e22586 %U https://doi.org/10.2196/22586 %U http://www.ncbi.nlm.nih.gov/pubmed/35044319 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e28098 %T Comparing the Impact of Online Ratings and Report Cards on Patient Choice of Cardiac Surgeon: Large Observational Study %A Li,Xuan %A Chou,Shin-Yi %A Deily,Mary E %A Qian,Mengcen %+ School of Public Health, Fudan University, Key Laboratory of Health Technology Assessment, Ministry of Health, 130 Dong’an Road, Shanghai, 200032, China, 86 13524622077, qianmengcen@fudan.edu.cn %K online physician reviews %K report cards %K cardiac surgeons %K patient choice %D 2021 %7 28.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients may use two information sources about a health care provider’s quality: online physician reviews, which are written by patients to reflect their subjective experience, and report cards, which are based on objective health outcomes. Objective: The aim of this study was to examine the impact of online ratings on patient choice of cardiac surgeon compared to that of report cards. Methods: We obtained ratings from a leading physician review platform, Vitals; report card scores from Pennsylvania Cardiac Surgery Reports; and information about patients’ choices of surgeons from inpatient records on coronary artery bypass graft (CABG) surgeries done in Pennsylvania from 2008 to 2017. We scraped all reviews posted on Vitals for surgeons who performed CABG surgeries in Pennsylvania during our study period. We linked the average overall rating and the most recent report card score at the time of a patient’s surgery to the patient’s record based on the surgeon’s name, focusing on fee-for-service patients to avoid impacts of insurance networks on patient choices. We used random coefficient logit models with surgeon fixed effects to examine the impact of receiving a high online rating and a high report card score on patient choice of surgeon for CABG surgeries. Results: We found that a high online rating had positive and significant effects on patient utility, with limited variation in preferences across individuals, while the impact of a high report card score on patient choice was trivial and insignificant. About 70.13% of patients considered no information on Vitals better than a low rating; the corresponding figure was 26.66% for report card scores. The findings were robust to alternative choice set definitions and were not explained by surgeon attrition, referral effect, or admission status. Our results also show that the interaction effect of rating information and a time trend was positive and significant for online ratings, but small and insignificant for report cards. Conclusions: A patient’s choice of surgeon is affected by both types of rating information; however, over the past decade, online ratings have become more influential, while the effect of report cards has remained trivial. Our findings call for information provision strategies that incorporate the advantages of both online ratings and report cards. %M 34709192 %R 10.2196/28098 %U https://www.jmir.org/2021/10/e28098 %U https://doi.org/10.2196/28098 %U http://www.ncbi.nlm.nih.gov/pubmed/34709192 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e29406 %T Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares %A Hu,Dian %A Liu,Cindy Meng-Hsin %A Hamdy,Rana %A Cziner,Michael %A Fung,Melody %A Dobbs,Samuel %A Rogers,Laura %A Turner,Monique Mitchell %A Broniatowski,David André %+ Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, George Washington University, B1800, Science and Engineering Hall 2700, 800 22nd St NW, Washington, DC, 20052, United States, 1 2027251564, hudian@gwmail.gwu.edu %K urgent care %K doctor-patient communication %K doctor web-based review %K review websites %D 2021 %7 8.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Providers of on-demand care, such as those in urgent care centers, may prescribe antibiotics unnecessarily because they fear receiving negative reviews on web-based platforms from unsatisfied patients—the so-called Yelp effect. This effect is hypothesized to be a significant driver of inappropriate antibiotic prescribing, which exacerbates antibiotic resistance. Objective: In this study, we aimed to determine the frequency with which patients left negative reviews on web-based platforms after they expected to receive antibiotics in an urgent care setting but did not. Methods: We obtained a list of 8662 urgent care facilities from the Yelp application programming interface. By using this list, we automatically collected 481,825 web-based reviews from Google Maps between January 21 and February 10, 2019. We used machine learning algorithms to summarize the contents of these reviews. Additionally, 200 randomly sampled reviews were analyzed by 4 annotators to verify the types of messages present and whether they were consistent with the Yelp effect. Results: We collected 481,825 reviews, of which 1696 (95% CI 1240-2152) exhibited the Yelp effect. Negative reviews primarily identified operations issues regarding wait times, rude staff, billing, and communication. Conclusions: Urgent care patients rarely express expectations for antibiotics in negative web-based reviews. Thus, our findings do not support an association between a lack of antibiotic prescriptions and negative web-based reviews. Rather, patients’ dissatisfaction with urgent care was most strongly linked to operations issues that were not related to the clinical management plan. %M 34623316 %R 10.2196/29406 %U https://www.jmir.org/2021/10/e29406 %U https://doi.org/10.2196/29406 %U http://www.ncbi.nlm.nih.gov/pubmed/34623316 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e24229 %T One Decade of Online Patient Feedback: Longitudinal Analysis of Data From a German Physician Rating Website %A Emmert,Martin %A McLennan,Stuart %+ Institute for Healthcare Management & Health Sciences, University of Bayreuth, Prieserstraße 2, Bayreuth, 95444, Germany, 49 921 55 ext 4827, martin.emmert@uni-bayreuth.de %K physician rating websites %K patient satisfaction %K patient feedback %K online ratings %D 2021 %7 26.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Feedback from patients is an essential element of a patient-oriented health care system. Physician rating websites (PRWs) are a key way patients can provide feedback online. This study analyzes an entire decade of online ratings for all medical specialties on a German PRW. Objective: The aim of this study was to examine how ratings posted on a German PRW have developed over the past decade. In particular, it aimed to explore (1) the distribution of ratings according to time-related aspects (year, month, day of the week, and hour of the day) between 2010 and 2019, (2) the number of physicians with ratings, (3) the average number of ratings per physician, (4) the average rating, (5) whether differences exist between medical specialties, and (6) the characteristics of the patients rating physicians. Methods: All scaled-survey online ratings that were posted on the German PRW jameda between 2010 and 2019 were obtained. Results: In total, 1,906,146 ratings were posted on jameda between 2010 and 2019 for 127,921 physicians. The number of rated physicians increased constantly from 19,305 in 2010 to 82,511 in 2018. The average number of ratings per rated physicians increased from 1.65 (SD 1.56) in 2010 to 3.19 (SD 4.69) in 2019. Overall, 75.2% (1,432,624/1,906,146) of all ratings were in the best rating category of “very good,” and 5.7% (107,912/1,906,146) of the ratings were in the lowest category of “insufficient.” However, the mean of all ratings was 1.76 (SD 1.53) on the German school grade 6-point rating scale (1 being the best) with a relatively constant distribution over time. General practitioners, internists, and gynecologists received the highest number of ratings (343,242, 266,899, and 232,914, respectively). Male patients, those of higher age, and those covered by private health insurance gave significantly (P<.001) more favorable evaluations compared to their counterparts. Physicians with a lower number of ratings tended to receive ratings across the rating scale, while physicians with a higher number of ratings tended to have better ratings. Physicians with between 21 and 50 online ratings received the lowest ratings (mean 1.95, SD 0.84), while physicians with >100 ratings received the best ratings (mean 1.34, SD 0.47). Conclusions: This study is one of the most comprehensive analyses of PRW ratings to date. More than half of all German physicians have been rated on jameda each year since 2016, and the overall average number of ratings per rated physicians nearly doubled over the decade. Nevertheless, we could also observe a decline in the number of ratings over the last 2 years. Future studies should investigate the most recent development in the number of ratings on both other German and international PRWs as well as reasons for the heterogeneity in online ratings by medical specialty. %M 34309579 %R 10.2196/24229 %U https://www.jmir.org/2021/7/e24229 %U https://doi.org/10.2196/24229 %U http://www.ncbi.nlm.nih.gov/pubmed/34309579 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e17095 %T Rating Hospital Performance in China: Review of Publicly Available Measures and Development of a Ranking System %A Dong,Shengjie %A Millar,Ross %A Shi,Chenshu %A Dong,Minye %A Xiao,Yuyin %A Shen,Jie %A Li,Guohong %+ China Hospital Development Institute, Shanghai Jiao Tong University School of Medicine, 227 South Chong Qing Road, Shanghai, 200025, China, 86 21 63846590, guohongli@sjtu.edu.cn %K hospital ranking %K performance measurement %K health care quality %K China health care reform %D 2021 %7 17.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: In China, significant emphasis and investment in health care reform since 2009 has brought with it increasing scrutiny of its public hospitals. Calls for greater accountability in the quality of hospital care have led to increasing attention toward performance measurement and the development of hospital ratings. Despite such interest, there has yet to be a comprehensive analysis of what performance information is publicly available to understand the performance of hospitals in China. Objective: This study aims to review the publicly available performance information about hospitals in China to assess options for ranking hospital performance. Methods: A review was undertaken to identify performance measures based on publicly available data. Following several rounds of expert consultation regarding the utility of these measures, we clustered the available options into three key areas: research and development, academic reputation, and quality and safety. Following the identification and clustering of the available performance measures, we set out to translate these into a practical performance ranking system to assess variation in hospital performance. Results: A new hospital ranking system termed the China Hospital Development Index (CHDI) is thus presented. Furthermore, we used CHDI for ranking well-known tertiary hospitals in China. Conclusions: Despite notable limitations, our assessment of available measures and the development of a new ranking system break new ground in understanding hospital performance in China. In doing so, CHDI has the potential to contribute to wider discussions and debates about assessing hospital performance across global health care systems. %M 34137724 %R 10.2196/17095 %U https://www.jmir.org/2021/6/e17095 %U https://doi.org/10.2196/17095 %U http://www.ncbi.nlm.nih.gov/pubmed/34137724 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 10 %N 2 %P e22271 %T Cyberspace and Libel: A Dangerous Balance for Physicians %A Chiruvella,Varsha %A Guddati,Achuta Kumar %+ Medical College of Georgia, Augusta University, 1411 Laney Walker Blvd, CN Building, Room 5327, Augusta, GA, 30912, United States, 1 3124048928, aguddati@augusta.edu %K libel %K reputation %K physician %K law %K legal %K defamation %D 2021 %7 27.5.2021 %9 Viewpoint %J Interact J Med Res %G English %X Freedom of speech and expression is one of the core tenets of modern societies. It was deemed to be so fundamentally essential to early American life that it was inscribed as the First Amendment of the United States Constitution. Over the past century, the rise of modern life also marked the rise of the digital era and age of social media. Freedom of speech thus transitioned from print to electronic media. Access to such content is almost instantaneous and available to a vast audience. From social media to online rating websites, online defamation may cause irreparable damage to a physician’s reputation and practice. It is especially relevant in these times of political turbulence where the battle to separate facts from misinformation has started a debate about the responsibility of social media. The historical context of libel and its applicability in the age of increasing online presence is important for physicians since they are also bound by duty to protect the privacy of their patients. The use of public rating sites and social media will continue to be important for physicians, as online presence and incidents of defamation impact the practice of medicine. %M 34042594 %R 10.2196/22271 %U https://www.i-jmr.org/2021/2/e22271 %U https://doi.org/10.2196/22271 %U http://www.ncbi.nlm.nih.gov/pubmed/34042594 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 10 %N 1 %P e21640 %T Visibility Versus Privacy of Physicians in the Age of Social Media %A Patel,Sunny J %A Guddati,Achuta K %+ Medical College of Georgia, Augusta University, 1411 Laney Walker Blvd, Augusta, GA, 30912, United States, 1 3124048928, aguddati@augusta.edu %K social media %K privacy %K internet %D 2021 %7 8.3.2021 %9 Viewpoint %J Interact J Med Res %G English %X As access to the internet has grown over the years, social media has become an important resource in the health care sector. Third-party physician-rating websites in particular have gained popularity. However, there are ethical implications of such websites. These websites provide a platform for patients to evaluate and review physicians and likewise increase visibility and advertisement of physicians, but they also violate the rights to privacy that these doctors should have. This paper aims to study and assess the ethical implications of these websites on the visibility and privacy of physicians. After presenting the ethical dilemma associated with such websites, it provides guidelines that can be incorporated by both physicians and third-party sites to help maintain physician privacy while providing public service in the form of advertisement and visibility. %M 33683211 %R 10.2196/21640 %U https://www.i-jmr.org/2021/1/e21640 %U https://doi.org/10.2196/21640 %U http://www.ncbi.nlm.nih.gov/pubmed/33683211 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 1 %P e22975 %T Digital Footprint of Academic Vascular Surgeons in the Southern United States on Physician Rating Websites: Cross-sectional Evaluation Study %A Yan,Qi %A Jensen,Katherine J %A Thomas,Rose %A Field,Alyssa R %A Jiang,Zheng %A Goei,Christian %A Davies,Mark G %+ Division of Vascular Surgery, Department of Surgery, UT Health San Antonio, 7703 Floyd Curl Dr, MC7741, San Antonio, TX, 78229, United States, 1 210 567 5715, DaviesM@uthscsa.edu %K internet %K patient satisfaction %K quality of care %K physician rating sites %K patient experience %K professional reviews %K social media %D 2021 %7 24.2.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: The internet has become a popular platform for patients to obtain information and to review the health care providers they interact with. However, little is known about the digital footprint of vascular surgeons and their interactions with patients on social media. Objective: This study aims to understand the activity of academic vascular surgeons on physician rating websites. Methods: Information on attending vascular surgeons affiliated with vascular residency or with fellowships in the Southern Association for Vascular Surgery (SAVS) was collected from public sources. A listing of websites containing physician ratings was obtained via literature reviews and Google search. Open access websites with either qualitative or quantitative evaluations of vascular surgeons were included. Closed access websites were excluded. Ranking scores from each website were converted to a standard 5-point scale for comparison. Results: A total of 6238 quantitative and 967 qualitative reviews were written for 287 physicians (236 males, 82.2%) across 16 websites that met the inclusion criteria out of the 62 websites screened. The surgeons affiliated with the integrated vascular residency and vascular fellowship programs in SAVS had a median of 8 (IQR 7-10) profiles across 16 websites, with only 1 surgeon having no web presence in any of the websites. The median number of quantitative ratings for each physician was 17 (IQR 6-34, range 1-137) and the median number of narrative reviews was 3 (IQR 2-6, range 1-28). Vitals, WebMD, and Healthgrades were the only 3 websites where over a quarter of the physicians were rated, and those rated had more than 5 ratings on average. The median score for the quantitative reviews was 4.4 (IQR 4.0-4.9). Most narrative reviews (758/967, 78.4%) were positive, but 20.2% (195/967) were considered negative; only 1.4% (14/967) were considered equivocal. No statistical difference was found in the number of quantitative reviews or in the overall average score in the physician ratings between physicians with social media profiles and those without social media profiles (departmental social media profile: median 23 vs 15, respectively, P=.22; personal social media profile: median 19 vs 14, respectively, P=.08). Conclusions: The representation of vascular surgeons on physician rating websites is varied, with the majority of the vascular surgeons represented only in half of the physician rating websites The number of quantitative and qualitative reviews for academic vascular surgeons is low. No vascular surgeon responded to any of the reviews. The activity of vascular surgeons in this area of social media is low and reflects only a small digital footprint that patients can reach and review. %M 33625359 %R 10.2196/22975 %U https://cardio.jmir.org/2021/1/e22975 %U https://doi.org/10.2196/22975 %U http://www.ncbi.nlm.nih.gov/pubmed/33625359 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e16691 %T The Influence of Doctors’ Online Reputation on the Sharing of Outpatient Experiences: Empirical Study %A Wang,Yang %A Wu,Hong %A Lei,Xueqin %A Shen,Jingxuan %A Feng,Zhanchun %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Hubei Province, Wuhan, 430030, China, 86 13277942186, wuhong634214924@163.com %K online health communities %K individual reputation %K doctor reputation %K patient feedback %K organizational reputation %K disease severity %D 2020 %7 11.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The internet enables consumers to evaluate products before purchase based on feedback submitted by like-minded individuals. Displaying reviews allows customers to assess comparable experiences and encourages trust, increased sales, and brand positivity. Customers use reviews to inform decision making, whereas organizations use reviews to predict future sales. Prior studies have focused on manufactured products, with little attention being paid to health care services. In particular, whether patients prefer to use websites to discuss doctors’ reputation has so far remained unanswered. Objective: This study aims to investigate how patient propensity to post treatment experiences changes based on doctors’ online reputation (medical quality and service attitude) in delivering outpatient care services. Further, this study examines the moderating effects of hospitals’ (organizational) online reputation and disease severity. Methods: Fractional logistic regression was conducted on data collected from 7183 active doctors in a Chinese online health community to obtain empirical results. Results: Our findings show that patients prefer to share treatment experiences for doctors who have a higher medical quality and service attitude (βservice attitude=.233; P<.001 and βmedical quality=.052; P<.001) and who work in hospitals with a higher online reputation (β=.001; P<.001). Patients are more likely to share experiences of doctors who treat less severe diseases, as opposed to those treating severe diseases (β=−.004; P=.009). In addition, hospitals’ online reputation positively (negatively) moderates the relationship between medical quality (service attitude) and patient propensity to post treatment experiences, whereas the moderating effects of disease severity on doctors’ online reputation are negative. Conclusions: Our research contributes to both theory and practice by extending the current understanding of the impact of individual reputation on consumer behavior. We investigate the moderating effects of organizational reputation and consumer characteristics in online health communities. %M 33306028 %R 10.2196/16691 %U http://www.jmir.org/2020/12/e16691/ %U https://doi.org/10.2196/16691 %U http://www.ncbi.nlm.nih.gov/pubmed/33306028 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e22765 %T Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study %A Goyal,Dev %A Guttag,John %A Syed,Zeeshan %A Mehta,Rudra %A Elahi,Zahoor %A Saeed,Mohammed %+ Department of Internal Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, United States, 1 6176421280, msaeed@umich.edu %K machine learning %K hospital ratings %K precision delivery %K hospital %K surgery %K outcome %K perioperative %K internet %K reputation %K machine learning %D 2020 %7 1.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients’ choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital choices. Objective: This paper aims to compare differences in outcomes and costs between hospitals ranked using popular internet-based consumer ratings, quality stars, reputation rankings, average volumes, average outcomes, and precision machine learning–based rankings for hospital settings performing hip replacements in a large metropolitan area. Methods: Retrospective data from 4192 hip replacement surgeries among Medicare beneficiaries in 2018 in a the Chicago metropolitan area were analyzed for variations in outcomes (90-day postprocedure hospitalizations and emergency department visits) and costs (90-day total cost of care) between hospitals ranked through multiple approaches: internet-based consumer ratings, quality stars, reputation rankings, average yearly surgical volume, average outcome rates, and machine learning–based rankings. The average rates of outcomes and costs were compared between the patients who underwent surgery at a hospital using each ranking approach in unadjusted and propensity-based adjusted comparisons. Results: Only a minority of patients (1159/4192, 27.6% to 2078/4192, 49.6%) were found to be matched to higher-ranked hospitals for each of the different approaches. Of the approaches considered, hip replacements at hospitals that were more highly ranked by consumer ratings, quality stars, and machine learning were all consistently associated with improvements in outcomes and costs in both adjusted and unadjusted analyses. The improvement was greatest across all metrics and analyses for machine learning–based rankings. Conclusions: There may be a substantive opportunity to increase the number of patients matched to appropriate hospitals across a broad variety of ranking approaches. Elective hip replacement surgeries performed at hospitals where patients were matched based on patient-specific machine learning were associated with better outcomes and lower total costs of care. %M 33258459 %R 10.2196/22765 %U https://www.jmir.org/2020/12/e22765 %U https://doi.org/10.2196/22765 %U http://www.ncbi.nlm.nih.gov/pubmed/33258459 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e11258 %T Correlation of Online Physician Rating Subscores and Association With Overall Satisfaction: Observational Study of 212,933 Providers %A Zhao,Hanson Hanqing %A Luu,Michael %A Spiegel,Brennan %A Daskivich,Timothy John %+ Division of Urology, Cedars-Sinai Medical Center, 8635 West 3rd Street, Suite 1070W, Los Angeles, CA, United States, 1 310 423 4700, timothy.daskivich@csmc.edu %K online ratings %K Healthgrades %K physician ratings %D 2020 %7 27.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Online physician rating websites commonly ask consumers to rate providers across multiple physician-based (eg, spending sufficient time, listening) and office-based (eg, appointment scheduling, friendliness) subdimensions of care in addition to overall satisfaction. However, it is unclear if consumers can differentiate between the various rated subdimensions of physicians. It is also unclear how each subdimension is related to overall satisfaction. Objective: The objectives of our study were to determine the correlation of physician-based and office-based subdimensions of care and the association of each with overall satisfaction. Methods: We sampled 212,933 providers from the Healthgrades website and calculated average provider metrics for overall satisfaction (likelihood to recommend doctor), physician-based subdimensions (trust in physician, ability to explain, ability to listen and answer questions, and spending adequate time), and office-based subdimensions (ease of scheduling, office environment, staff friendliness, and wait time). We used Spearman rank correlation to assess correlation between subdimension ratings. Factor analysis was used to identify potential latent factors predicting overall satisfaction. Univariate and multivariable linear regression were performed to assess the effect of physician and office-based factors on overall satisfaction. Results: Physician-based metrics were highly correlated with each other (r=.95 to .98, P<.001), as were office-based metrics (r=.84 to .88, P<.001). Correlations between physician-based and office-based ratings were less robust (r=.79 to .81, P<.001). Factor analysis identified two factors, clearly distinguishing between physician-based metrics (factor loading = 0.84 to 0.88) and office-based metrics (factor loading = 0.76 to 0.84). In multivariable linear regression analysis, the composite factor representing physician-based metrics (0.65, 95% CI 0.65 to 0.65) was more strongly associated with overall satisfaction than the factor representing office-based metrics (0.42, 95% CI 0.42 to 0.42). These factors eclipsed other demographic variables in predicting overall satisfaction. Conclusions: Consumers do not differentiate between commonly assessed subdimensions of physician-based care or subdimensions of office-based care, but composite factors representing these broader categories are associated with overall satisfaction. These findings argue for a simpler ratings system based on two metrics: one addressing physician-based aspects of care and another addressing office-based aspects of care. %M 33107826 %R 10.2196/11258 %U http://www.jmir.org/2020/10/e11258/ %U https://doi.org/10.2196/11258 %U http://www.ncbi.nlm.nih.gov/pubmed/33107826 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e21057 %T Authors’ Reply to: Is a Ratio Scale Assumption for Physician Ratings Justified? Comment on “What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data” %A Bidmon,Sonja %A Elshiewy,Ossama %A Terlutter,Ralf %A Boztug,Yasemin %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 4048, sonja.bidmon@aau.at %K online physician ratings %K patient satisfaction %K multiattribute models %K health care management %D 2020 %7 26.10.2020 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 33104006 %R 10.2196/21057 %U https://www.jmir.org/2020/10/e21057 %U https://doi.org/10.2196/21057 %U http://www.ncbi.nlm.nih.gov/pubmed/33104006 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e18289 %T Is a Ratio Scale Assumption for Physician Ratings Justified? Comment on “What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data” %A Konerding,Uwe %+ Trimberg Research Academy, University of Bamberg, An der Weberei 5, Bamberg, D-96045, Germany, 49 951 863 3098, uwe.konerding@uni-bamberg.de %K patient satisfaction %K modeling %K method %K scale level %K measurement theory %D 2020 %7 26.10.2020 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 33104009 %R 10.2196/18289 %U http://www.jmir.org/2020/10/e18289/ %U https://doi.org/10.2196/18289 %U http://www.ncbi.nlm.nih.gov/pubmed/33104009 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e15916 %T Data Quality Issues With Physician-Rating Websites: Systematic Review %A Mulgund,Pavankumar %A Sharman,Raj %A Anand,Priya %A Shekhar,Shashank %A Karadi,Priya %+ School of Management, State University of New York Buffalo, 160 Jacobs Management Center, Buffalo, NY , United States, 1 7167481552, pmulgund@buffalo.edu %K physician-rating websites %K data quality issues %K doctor ratings %K reviews %K data quality framework %D 2020 %7 28.9.2020 %9 Review %J J Med Internet Res %G English %X Background: In recent years, online physician-rating websites have become prominent and exert considerable influence on patients’ decisions. However, the quality of these decisions depends on the quality of data that these systems collect. Thus, there is a need to examine the various data quality issues with physician-rating websites. Objective: This study’s objective was to identify and categorize the data quality issues afflicting physician-rating websites by reviewing the literature on online patient-reported physician ratings and reviews. Methods: We performed a systematic literature search in ACM Digital Library, EBSCO, Springer, PubMed, and Google Scholar. The search was limited to quantitative, qualitative, and mixed-method papers published in the English language from 2001 to 2020. Results: A total of 423 articles were screened. From these, 49 papers describing 18 unique data quality issues afflicting physician-rating websites were included. Using a data quality framework, we classified these issues into the following four categories: intrinsic, contextual, representational, and accessible. Among the papers, 53% (26/49) reported intrinsic data quality errors, 61% (30/49) highlighted contextual data quality issues, 8% (4/49) discussed representational data quality issues, and 27% (13/49) emphasized accessibility data quality. More than half the papers discussed multiple categories of data quality issues. Conclusions: The results from this review demonstrate the presence of a range of data quality issues. While intrinsic and contextual factors have been well-researched, accessibility and representational issues warrant more attention from researchers, as well as practitioners. In particular, representational factors, such as the impact of inline advertisements and the positioning of positive reviews on the first few pages, are usually deliberate and result from the business model of physician-rating websites. The impact of these factors on data quality has not been addressed adequately and requires further investigation. %M 32986000 %R 10.2196/15916 %U http://www.jmir.org/2020/9/e15916/ %U https://doi.org/10.2196/15916 %U http://www.ncbi.nlm.nih.gov/pubmed/32986000 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e20910 %T Exploring Types of Information Sources Used When Choosing Doctors: Observational Study in an Online Health Care Community %A Zhang,Shuang %A Wang,Jying-Nan %A Chiu,Ya-Ling %A Hsu,Yuan-Teng %+ Research Center of Finance, Shanghai Business School, No 2271 West Zhong Shan Rd, Shanghai, 200235, China, 86 21 64870020 ext 1404, yuanteng.hsu@gmail.com %K information source %K decision making %K online reviews %K online health care community %K doctor %K health information %D 2020 %7 16.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients attempt to make appropriate decisions based on their own knowledge when choosing a doctor. In this process, the first question usually faced is that of how to obtain useful and relevant information. This study investigated the types of information sources that are used widely by patients in choosing a doctor and identified ways in which the preferred sources differ in various situations. Objective: This study aims to address the following questions: (1) What is the proportion in which each of the various information sources is used? (2) How does the information source preferred by patients in choosing a doctor change when there is a difference in the difficulty of medical decision making, in the level of the hospital, or in a rural versus urban situation? (3) How do information sources used by patients differ when they choose doctors with different specialties? Methods: This study overcomes a major limitation in the use of the survey technique by employing data from the Good Doctor website, which is now China's leading online health care community, data which are objective and can be obtained relatively easily and frequently. Multinomial logistic regression models were applied to examine whether the proportion of use of these information sources changes in different situations. We then used visual analysis to explore the question of which type of information source patients prefer to use when they seek medical assistance from doctors with different specialties. Results: The 3 main information sources were online reviews (OR), family and friend recommendations (FR), and doctor recommendations (DR), with proportions of use of 32.93% (559,345/1,698,666), 23.68% (402,322/1,698,666), and 17.48% (296,912/1,698,666), respectively. Difficulty in medical decision making, the hospital level, and rural-urban differences were significantly associated with patients’ preferred information sources for choosing doctors. Further, the sources of information that patients prefer to use were found to vary when they looked for doctors with different medical specialties. Conclusions: Patients are less likely to use online reviews when medical decisions are more difficult or when the provider is not a tertiary hospital, the former situation leading to a greater use of online reviews and the latter to a greater use of family and friend recommendations. In addition, patients in large cities are more likely to use information from online reviews than family and friend recommendations. Among different medical specialties, for those in which personal privacy is a concern, online reviews are the most common source. For those related to children, patients are more likely to refer to family and friend recommendations, and for those related to surgery, they value doctor recommendations more highly. Our results can not only contribute to aiding government efforts to further promote the dissemination of health care information but may also help health care industry managers develop better marketing strategies. %M 32936080 %R 10.2196/20910 %U http://www.jmir.org/2020/9/e20910/ %U https://doi.org/10.2196/20910 %U http://www.ncbi.nlm.nih.gov/pubmed/32936080 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e18374 %T Rejected Online Feedback From a Swiss Physician Rating Website Between 2008 and 2017: Analysis of 2352 Ratings %A McLennan,Stuart %+ Institute of History and Ethics in Medicine, Technical University of Munich, Ismaninger Straße 22, Munich, 81675, Germany, 49 89 4140 4041, stuart.mclennan@tum.de %K physician rating websites %K patient satisfaction %K participatory medicine %K patient feedback %D 2020 %7 3.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Previous research internationally has only analyzed publicly available feedback on physician rating websites (PRWs). However, it appears that many PRWs are not publishing all the feedback they receive. Analysis of this rejected feedback could provide a better understanding of the types of feedback that are currently not published and whether this is appropriate. Objective: The aim of this study was to examine (1) the number of patient feedback rejected from the Swiss PRW Medicosearch, (2) the evaluation tendencies of the rejected patient feedback, and (3) the types of issues raised in the rejected narrative comments. Methods: The Swiss PRW Medicosearch provided all the feedback that had been rejected between September 16, 2008, and September 22, 2017. The feedback were analyzed and classified according to a theoretical categorization framework of physician-, staff-, and practice-related issues. Results: Between September 16, 2008, and September 22, 2017, Medicosearch rejected a total of 2352 patient feedback. The majority of feedback rejected (1754/2352, 74.6%) had narrative comments in the German language. However, 11.9% (279/2352) of the rejected feedback only provided a quantitative rating with no narrative comment. Overall, 25% (588/2352) of the rejected feedback were positive, 18.7% (440/2352) were neutral, and 56% (1316/2352) were negative. The average rating of the rejected feedback was 2.8 (SD 1.4). In total, 44 subcategories addressing the physician (n=20), staff (n=9), and practice (n=15) were identified. In total, 3804 distinct issues were identified within the 44 subcategories of the categorization framework; 75% (2854/3804) of the issues were related to the physician, 6.4% (242/3804) were related to the staff, and 18.6% (708/3804) were related to the practice. Frequently mentioned issues identified from the rejected feedback included (1) satisfaction with treatment (533/1903, 28%); (2) the overall assessment of the physician (392/1903, 20.6%); (3) recommending the physician (345/1903, 18.1%); (4) the physician’s communication (261/1903, 13.7%); (5) the physician’s caring attitude (220/1903, 11.6%); and (6) the physician’s friendliness (203/1903, 10.6%). Conclusions: It is unclear why the majority of the feedback were rejected. This is problematic and raises concerns that online patient feedback are being inappropriately manipulated. If online patient feedback is going to be collected, there needs to be clear policies and practices about how this is handled. It cannot be left to the whims of PRWs, who may have financial incentives to suppress negative feedback, to decide which feedback is or is not published online. Further research is needed to examine how many PRWs are using criteria for determining which feedback is published or not, what those criteria are, and what measures PRWs are using to address the manipulation of online patient feedback. %M 32687479 %R 10.2196/18374 %U https://www.jmir.org/2020/8/e18374 %U https://doi.org/10.2196/18374 %U http://www.ncbi.nlm.nih.gov/pubmed/32687479 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e14455 %T Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis %A Dunivin,Zackary %A Zadunayski,Lindsay %A Baskota,Ujjwal %A Siek,Katie %A Mankoff,Jennifer %+ University of Washington, Bill & Melinda Gates Center for Computer Science and Engineering, 3800 E Stevens Way NE, Seattle, WA, 98112, United States, 1 4125677720, jmankoff@acm.org %K reviews %K physician-patient relationship %K gender %K soft-skills %D 2020 %7 30.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Online physician reviews are an important source of information for prospective patients. In addition, they represent an untapped resource for studying the effects of gender on the doctor-patient relationship. Understanding gender differences in online reviews is important because it may impact the value of those reviews to patients. Documenting gender differences in patient experience may also help to improve the doctor-patient relationship. This is the first large-scale study of physician reviews to extensively investigate gender bias in online reviews or offer recommendations for improvements to online review systems to correct for gender bias and aid patients in selecting a physician. Objective: This study examines 154,305 reviews from across the United States for all medical specialties. Our analysis includes a qualitative and quantitative examination of review content and physician rating with regard to doctor and reviewer gender. Methods: A total of 154,305 reviews were sampled from Google Place reviews. Reviewer and doctor gender were inferred from names. Reviews were coded for overall patient experience (negative or positive) by collapsing a 5-star scale and coded for general categories (process, positive/negative soft skills), which were further subdivided into themes. Computational text processing methods were employed to apply this codebook to the entire data set, rendering it tractable to quantitative methods. Specifically, we estimated binary regression models to examine relationships between physician rating, patient experience themes, physician gender, and reviewer gender). Results: Female reviewers wrote 60% more reviews than men. Male reviewers were more likely to give negative reviews (odds ratio [OR] 1.15, 95% CI 1.10-1.19; P<.001). Reviews of female physicians were considerably more negative than those of male physicians (OR 1.99, 95% CI 1.94-2.14; P<.001). Soft skills were more likely to be mentioned in the reviews written by female reviewers and about female physicians. Negative reviews of female doctors were more likely to mention candor (OR 1.61, 95% CI 1.42-1.82; P<.001) and amicability (OR 1.63, 95% CI 1.47-1.90; P<.001). Disrespect was associated with both female physicians (OR 1.42, 95% CI 1.35-1.51; P<.001) and female reviewers (OR 1.27, 95% CI 1.19-1.35; P<.001). Female patients were less likely to report disrespect from female doctors than expected from the base ORs (OR 1.19, 95% CI 1.04-1.32; P=.008), but this effect overrode only the effect for female reviewers. Conclusions: This work reinforces findings in the extensive literature on gender differences and gender bias in patient-physician interaction. Its novel contribution lies in highlighting gender differences in online reviews. These reviews inform patients’ choice of doctor and thus affect both patients and physicians. The evidence of gender bias documented here suggests review sites may be improved by providing information about gender differences, controlling for gender when presenting composite ratings for physicians, and helping users write less biased reviews. %M 32729844 %R 10.2196/14455 %U https://www.jmir.org/2020/7/e14455 %U https://doi.org/10.2196/14455 %U http://www.ncbi.nlm.nih.gov/pubmed/32729844 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18527 %T Causal Effect of Honorary Titles on Physicians’ Service Volumes in Online Health Communities: Retrospective Study %A Yu,Haiyan %A Wang,Yali %A Wang,Jying-Nan %A Chiu,Ya-Ling %A Qiu,Hang %A Gao,Mingyue %+ Life Course Epidemiology and Biostatistics, Population, Policy, and Practice Programme, Great Ormond Street Institute of Child Health, University College London, Guilford Street, London, WC1N 1EH, United Kingdom, 44 07410372022, ming.gao.17@ucl.ac.uk %K causality %K health information systems %K organizational policy %K physician-patient relations %K remote consultation %D 2020 %7 9.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: An OHC online health community (OHC) is an interactive platform for virtual communication between patients and physicians. Patients can typically search, seek, and share their experience and rate physicians, who may be involved in giving advice. Some OHC providers provide incentives in form of honorary titles to encourage the web-based involvement of physicians, but it is unclear whether the award of honorary titles has an impact on their consultation volume in an OHC. Objective: This study is designed to identify the differential treatment effect of the incentive policy on the service volumes for the subgroups of treatment and control in an OHC. This study aims to answer the following questions: Does an honorary title for physicians impact their service volumes in an OHC? During the period of discontinuity, can we identify the sharp effect of the incentive award on the outcomes of physicians’ service volumes? Methods: We acquired the targeted samples based on treatment, namely, physicians with an honorary title or not and outcomes measured before and after the award of the 2 subgroups. A regression discontinuity design was applied to investigate the impact of the honorary titles incentive as a treatment in an OHC. There was a sharply discontinuous effect of treatment on physicians’ online health service performance. The experimental data set consisted of 346 physicians in the treatment group (with honorary titles). Applying the propensity score matching method, the same size of physicians (n=346) was matched and selected as the control group. Results: A sharp discontinuity was found at the time of the physician receiving the honorary title. The results showed that the parametric estimates of the coefficient were significantly positively (P<.001) associated with monthly home page views. The jump in the monthly volumes of home page views was much sharper than that of the monthly consultations. Conclusions: The changes in the volumes of monthly consultations and home page views reflect the differential treatment effect of honorary titles on physicians’ service volumes. The effect of the incentive policy with honorary titles is objectively estimated from both the perspective of online and offline medical services in an OHC. Being named with honorary titles significantly multiplied monthly home page views, yet it did not significantly impact monthly consultations. This may be because consultation capacity is limited by the physician's schedule for consultations. %M 32673232 %R 10.2196/18527 %U https://www.jmir.org/2020/7/e18527 %U https://doi.org/10.2196/18527 %U http://www.ncbi.nlm.nih.gov/pubmed/32673232 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18652 %T Assessing Patient Experience and Healthcare Quality of Dental Care Using Patient Online Reviews in the United States: Mixed Methods Study %A Lin,Ye %A Hong,Y Alicia %A Henson,Bradley S %A Stevenson,Robert D %A Hong,Simon %A Lyu,Tianchu %A Liang,Chen %+ Arnold School of Public Health, University of South Carolina, Suite 347, 915 Greene Street, Columbia, SC, 29208, United States, 1 803 777 8139, cliang@mailbox.sc.edu %K dental care %K healthcare quality %K consumer health informatics %K patient online reviews %K patient review websites %K natural language processing %D 2020 %7 7.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Over the last two decades, patient review websites have emerged as an essential online platform for doctor ratings and reviews. Recent studies suggested the significance of such websites as a data source for patients to choose doctors for healthcare providers to learn and improve from patient feedback and to foster a culture of trust and transparency between patients and healthcare providers. However, as compared to other medical specialties, studies of online patient reviews that focus on dentists in the United States remain absent. Objective: This study sought to understand to what extent online patient reviews can provide performance feedbacks that reflect dental care quality and patient experience. Methods: Using mixed informatics methods incorporating statistics, natural language processing, and domain expert evaluation, we analyzed the online patient reviews of 204,751 dentists extracted from HealthGrades with two specific aims. First, we examined the associations between patient ratings and a variety of dentist characteristics. Second, we identified topics from patient reviews that can be mapped to the national assessment of dental patient experience measured by the Patient Experience Measures from the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Dental Plan Survey. Results: Higher ratings were associated with female dentists (t71881=2.45, P<.01, g=0.01), dentists at a younger age (F7, 107128=246.97, P<.001, g=0.11), and those whose patients experienced a short wait time (F4, 150055=10417.77, P<0.001, g=0.18). We also identified several topics that corresponded to CAHPS measures, including discomfort (eg, painful/painless root canal or deep cleaning), and ethics (eg, high-pressure sales, and unnecessary dental work). Conclusions: These findings suggest that online patient reviews could be used as a data source for understanding the patient experience and healthcare quality in dentistry. %M 32673240 %R 10.2196/18652 %U https://www.jmir.org/2020/7/e18652 %U https://doi.org/10.2196/18652 %U http://www.ncbi.nlm.nih.gov/pubmed/32673240 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 6 %P e14417 %T Factors Associated With the Actual Behavior and Intention of Rating Physicians on Physician Rating Websites: Cross-Sectional Study %A Han,Xi %A Li,Bei %A Zhang,Tingting %A Qu,Jiabin %+ School of Business Administration, Guangdong University of Finance & Economics, Luntou Road 21, Haizhu District, Guangzhou, 510320, China, 86 13512791305, hanx015@163.com %K online physician rating %K user-generated content %K physician rating website %K behavioral intention %K actual behavior %D 2020 %7 4.6.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Although online physician rating information is popular among Chinese health consumers, the limited number of reviews greatly hampers the effective usage of this information. To date, little has been discussed on the variables that influence online physician rating from the users’ perspective. Objective: This study aims to investigate the factors associated with the actual behavior and intention of generating online physician rating information in urban China. Methods: A web-based cross-sectional survey was conducted, and the valid responses of 1371 Chinese health consumers were recorded. Using a pilot interview, we analyzed the effects of demographics, health variables, cognitive variables, and technology-related variables on online physician rating information generation. Binary multivariate logistic regression, multiple linear regression, one-way analysis of variance analyses, and independent samples t test were performed to analyze the rating behavior and the intentions of the health consumers. The survey instrument was designed based on the existing literature and the pilot interview. Results: In this survey, 56.7% (778/1371) of the responders used online physician rating information, and 20.9% (287/1371) of the responders rated the physicians on the physician rating website at least once (posters). The actual physician rating behavior was mainly predicted by health-related factors and was significantly associated with seeking web-based physician information (odds ratio [OR] 5.548, 95% CI 3.072-10.017; P<.001), usage of web-based physician service (OR 2.771, 95% CI 1.979-3.879; P<.001), health information-seeking ability (OR 1.138, 95% CI 0.993-1.304; P=.04), serious disease development (OR 2.699, 95% CI 1.889-3.856; P<.001), good medical experience (OR 2.149, 95% CI 1.473-3.135; P<.001), altruism (OR 0.612, 95% CI 0.483-0.774; P<.001), self-efficacy (OR 1.453, 95% CI 1.182-1.787; P<.001), and trust in online physician rating information (OR 1.315, 95% CI 1.089-1.586; P=.004). Some factors influencing the intentions of the posters and nonposters rating the physicians were different, and the rating intention was mainly determined by cognitive and health-related factors. For posters, seeking web-based physician information (β=.486; P=.007), using web-based medical service (β=.420; P=.002), ability to seek health information (β=.193; P=.002), rating habits (β=.105; P=.02), altruism (β=.414; P<.001), self-efficacy (β=.102; P=.06), trust (β=.351; P<.001), and perceived ease of use (β=.275; P<.001) served as significant predictors of the rating intention. For nonposters, ability to seek health information (β=.077; P=.003), chronic disease development (β=.092; P=.06), bad medical experience (β=.047; P=.02), rating habits (β=.085; P<.001), altruism (β=.411; P<.001), self-efficacy (β=.171; P<.001), trust (β=.252; P<.001), and perceived usefulness of rating physicians (β=.109; P<.001) were significantly associated with the rating intention. Conclusions: We showed that different factors affected the physician rating behavior and rating intention. Health-related variables influenced the physician rating behavior, while cognitive variables were critical in the rating intentions. We have proposed some practical implications for physician rating websites and physicians to promote online physician rating information generation. %M 32496198 %R 10.2196/14417 %U http://www.jmir.org/2020/6/e14417/ %U https://doi.org/10.2196/14417 %U http://www.ncbi.nlm.nih.gov/pubmed/32496198 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 5 %P e16708 %T Association Between Web-Based Physician Ratings and Physician Disciplinary Convictions: Retrospective Observational Study %A Liu,Jessica Janine %A Goldberg,Hanna R %A Lentz,Eric JM %A Matelski,John Justin %A Alam,Asim %A Bell,Chaim M %+ Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto General Hospital, 200 Elizabeth Street, Room 14EN213, Toronto, ON, M5G 2C4, Canada, 1 4163403111, jessica.liu@uhn.ca %K quality improvement %K patient satisfaction %K patient-centered care %D 2020 %7 14.5.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites are commonly used by the public, yet the relationship between web-based physician ratings and health care quality is not well understood. Objective: The objective of our study was to use physician disciplinary convictions as an extreme marker for poor physician quality and to investigate whether disciplined physicians have lower ratings than nondisciplined matched controls. Methods: This was a retrospective national observational study of all disciplined physicians in Canada (751 physicians, 2000 to 2013). We searched ratings (2005-2015) from the country’s leading online physician rating website for this group, and for 751 matched controls according to gender, specialty, practice years, and location. We compared overall ratings (out of a score of 5) as well as mean ratings by the type of misconduct. We also compared ratings for each type of misconduct and punishment. Results: There were 62.7% (471/751) of convicted and disciplined physicians (cases) with web-based ratings and 64.6% (485/751) of nondisciplined physicians (controls) with ratings. Of 312 matched case-control pairs, disciplined physicians were rated lower than controls overall (3.62 vs 4.00; P<.001). Disciplined physicians had lower ratings for all types of misconduct and punishment—except for physicians disciplined for sexual offenses (n=90 pairs; 3.83 vs 3.86; P=.81). Sexual misconduct was the only category in which mean ratings for physicians were higher than those for other disciplined physicians (3.63 vs 3.35; P=.003) Conclusions: Physicians convicted for disciplinary misconduct generally had lower web-based ratings. Physicians convicted of sexual misconduct did not have lower ratings and were rated higher than other disciplined physicians. These findings may have future implications for the identification of physicians providing poor-quality care. %M 32406851 %R 10.2196/16708 %U https://www.jmir.org/2020/5/e16708 %U https://doi.org/10.2196/16708 %U http://www.ncbi.nlm.nih.gov/pubmed/32406851 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 3 %N 1 %P e17171 %T Assessment of Patient Satisfaction With Dermatology Clinics According to Clinic Type: Mixed Methods Study %A Costigan,Jennifer %A Feldman,Sue S %A Lemak,Mark %+ Department of Health Services Research, School of Health Professions, University of Alabama at Birmingham, 1716 9th Avenue South, SHPB #590K, Birmingham, AL, 35294, United States, 1 205 975 0809, suefeldman1009@gmail.com %K Consumer Assessment of Healthcare Providers and Systems survey scores %K patient satisfaction %K dermatology %K private dermatology clinic %K rapid access dermatology clinic %K wait time %K patient resource stewardship %K communication %D 2020 %7 12.5.2020 %9 Original Paper %J JMIR Dermatol %G English %X Background: Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey responses are considered significant indicators of the quality of care and patient satisfaction. There is a pressing need to improve patient satisfaction rates as CAHPS survey responses are considered when determining the amount a facility will be reimbursed by the Centers of Medicare and Medicaid each year. Low overall CAHPS scores for an academic medical center’s dermatology clinics were anecdotally attributed to clinic type. However, it was unclear whether clinic type was contributing to the low scores or whether there were other factors. Objective: This study aimed to determine where the efforts of patient satisfaction improvement should be focused for two different types of dermatology clinics (private and rapid access clinics). Methods: This study used a concurrent mixed methods design. Secondary data derived from the University of Alabama at Birmingham Hospital’s Press Ganey website were analyzed for clinic type comparisons and unstructured data were qualitatively analyzed to further enrich the quantitative findings. The University of Alabama at Birmingham Hospital is an academic medical center. The data were analyzed to determine the contributors responsible for each clinic not meeting national benchmarks. Thereafter, a review of these contributing factors was further performed to assess the difference in CAHPS scores between the private and rapid access clinics to determine if clinic type was a contributing factor to the overall scores. Results: The data sample included 821 responses from May 2017 to May 2018. Overall, when both private clinics and rapid access clinics were viewed collectively, majority of the patients reported stewardship of patient resources as the most poorly rated factor (367/549, 66.8%) and physician communication quality as the most positively rated factor (581/638, 91.0%). However, when private clinics and rapid access clinics were viewed individually, rapid access clinics contributed slightly to the overall lower dermatology scores at the academic medical center. Conclusions: This study determined that different factors were responsible for lower CAHPS scores for the two different dermatology clinics. Some of the contributing factors were associated with the mission of the clinic. It was suspected that the mission had not been properly communicated to patients, leading to misaligned expectations of care at each clinic. %R 10.2196/17171 %U http://derma.jmir.org/2020/1/e17171/ %U https://doi.org/10.2196/17171 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 4 %P e16635 %T The Buffering Effect of Health Care Provider Video Biographies When Viewed in Combination With Negative Reviews: “You Can’t Fake Nice” %A Perrault,Evan K %A Hildenbrand,Grace M %+ Brian Lamb School of Communication, Purdue University, 100 North University Street, West Lafayette, IN, 47907, United States, 1 7654966429, perrault@purdue.edu %K patient ratings %K health care providers %K video %K biographies %K expectancy violations %K thin slice %D 2020 %7 14.4.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients seek information from numerous sources before choosing a primary care provider; two of the most popular sources are providers’ own online biographies and patient rating websites. However, prior research has generally only examined how these sources influence patients’ decisions in isolation. Objective: This study aimed to determine how primary care providers’ online biographies and online patient ratings interact to affect patients’ decision making, especially in the face of negative reviews. Methods: An 8-condition online experiment (n=866) was conducted, manipulating patient ratings and the timing of viewing a provider’s online biographical video (pre- or postrating viewing). Results: When participants were shown a short video introduction of a provider after reading predominantly negative reviews a positive expectancy violation occurred, which was also related to more positive perceptions of the provider. When exposed to all negative reviews, 43% of participants indicated they would still choose to make an appointment with the provider, with many indicating that the video provided the evidence needed to help make up their own minds. Conclusions: These findings are especially relevant to health care organizations seeking to combat a recent rise in fake patient reviews. Providing patients with realistic expectations of the care that clinicians can offer via their own online biographical videos can help counteract negative patient comments online. %M 32286234 %R 10.2196/16635 %U https://www.jmir.org/2020/4/e16635 %U https://doi.org/10.2196/16635 %U http://www.ncbi.nlm.nih.gov/pubmed/32286234 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 4 %P e16526 %T Exploring the Factors Influencing Consumers to Voluntarily Reward Free Health Service Contributors in Online Health Communities: Empirical Study %A Zhou,Junjie %A Liu,Fang %A Zhou,Tingting %+ China Life Property & Casualty Insurance Company Limited, No 16 Jinrong Street, Beijing, China, 86 1066190179, liu-fang@chinalife-p.com.cn %K telemedicine %K health services %K social media %K reward %K social interaction %K social support %K pay-what-you-want %D 2020 %7 14.4.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Rewarding health knowledge and health service contributors with money is one possible approach for the sustainable provision of health knowledge and health services in online health communities (OHCs); however, the reasons why consumers voluntarily reward free health knowledge and health service contributors are still underinvestigated. Objective: This study aimed to address the abovementioned gap by exploring the factors influencing consumers’ voluntary rewarding behaviors (VRBs) toward contributors of free health services in OHCs. Methods: On the basis of prior studies and the cognitive-experiential self-theory (CEST), we incorporated two health service content–related variables (ie, informational support and emotional support) and two interpersonal factors (ie, social norm compliance and social interaction) and built a proposed model. We crawled a dataset from a Chinese OHC for mental health, coded it, extracted nine variables, and tested the model with a negative binomial model. Results: The data sample included 2148 health-related questions and 12,133 answers. The empirical results indicated that the effects of informational support (β=.168; P<.001), emotional support (β=.463; P<.001), social norm compliance (β=.510; P<.001), and social interaction (β=.281; P<.001) were significant. The moderating effects of social interaction on informational support (β=.032; P=.02) and emotional support (β=−.086; P<.001) were significant. The moderating effect of social interaction on social norm compliance (β=.014; P=.38) was insignificant. Conclusions: Informational support, emotional support, social norm compliance, and social interaction positively influence consumers to voluntarily reward free online health service contributors. Social interaction enhances the effect of informational support but weakens the effect of emotional support. This study contributes to the literature on knowledge sharing in OHCs by exploring the factors influencing consumers’ VRBs toward free online health service contributors and contributes to the CEST literature by verifying that the effects of experiential and rational systems on individual behaviors can vary while external factors change. %M 32286231 %R 10.2196/16526 %U http://www.jmir.org/2020/4/e16526/ %U https://doi.org/10.2196/16526 %U http://www.ncbi.nlm.nih.gov/pubmed/32286231 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 4 %P e14134 %T Influence of Health Literacy on Effects of Patient Rating Websites: Survey Study Using a Hypothetical Situation and Fictitious Doctors %A Schulz,Peter Johannes %A Rothenfluh,Fabia %+ Università della Svizzera Italiana, Via G Buffi, 13, Lugano, 6900, Switzerland, 41 58 666 4724, schulzp@usi.ch %K physician rating websites %K warning messages %K experiment %K physician competence assessment %K patient feedback %D 2020 %7 6.4.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRWs) are a device people use actively and passively, although their objective capabilities are insufficient when it comes to judging the medical performance and qualification of physicians. PRWs are an innovation born of the potential of the Internet and boosted very much by the longstanding policy of improving and encouraging patient participation in medical decision-making. A mismatch is feared between patient motivations to participate and their capabilities of doing so well. Awareness of such a mismatch might contribute to some skepticism of patient-written physician reviews on PRWs. Objective: We intend to test whether health literacy is able to dampen the effects that a patient-written review of a physician’s performance might have on physician choice. Methods: An experiment was conducted within a survey interview. Participants were put into a fictitious decision situation in which they had to choose between two physicians on the basis of their profiles on a PRW. One of the physician profiles contained the experimental stimulus in the form of a friendly and a critical written review. The dependent variable was physician choice. An attitude differential, trust differential, and two measures of health literacy, the newest vital sign as an example of a performance-based measure and eHealth Literacy Scale as an example of a perception-based measure, were tested for roles as intermediary variables. Analysis traced the influence of the review tendency on the dependent variables and a possible moderating effect of health literacy on these influences. Results: Reviews of a physician’s competence and medical skill affected participant choice of a physician. High health literacy dampened these effects only in the case of the perception-based measure and only for the negative review. Correspondingly, the effect of the review tendency appeared to be stronger for the positive review. Attitudes and trust only affected physician choice when included as covariants, considerably increasing the variance explained by regression models. Conclusions: Findings sustain physician worries that even one negative PRW review can affect patient choice and damage doctors’ reputations. Hopes that health literacy might raise awareness of the poor basis of physician reviews and ratings given by patients have some foundation. %M 32250275 %R 10.2196/14134 %U https://www.jmir.org/2020/4/e14134 %U https://doi.org/10.2196/14134 %U http://www.ncbi.nlm.nih.gov/pubmed/32250275 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 2 %P e13830 %T What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data %A Bidmon,Sonja %A Elshiewy,Ossama %A Terlutter,Ralf %A Boztug,Yasemin %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 4048, sonja.bidmon@aau.at %K online physician ratings %K patient satisfaction %K multiattribute models %K health care management %D 2020 %7 3.2.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Customer-oriented health care management and patient satisfaction have become important for physicians to attract patients in an increasingly competitive environment. Satisfaction influences patients’ choice of physician and leads to higher patient retention and higher willingness to engage in positive word of mouth. In addition, higher satisfaction has positive effects on patients’ willingness to follow the advice given by the physician. In recent years, physician-rating websites (PRWs) have emerged in the health care sector and are increasingly used by patients. Patients’ usage includes either posting an evaluation to provide feedback to others about their own experience with a physician or reading evaluations of other patients before choosing a physician. The emergence of PRWs offers new avenues to analyze patient satisfaction and its key drivers. PRW data enable both satisfaction analyses and implications on the level of the individual physician as well as satisfaction analyses and implications on an overall level. Objective: This study aimed to identify linear and nonlinear effects of patients’ perceived quality of physician appointment service attributes on the overall evaluation measures that are published on PRWs. Methods: We analyzed large-scale survey data from a German PRW containing 84,680 surveys of patients rating a total of 7038 physicians on 24 service attributes and 4 overall evaluation measures. Elasticities are estimated from regression models with perceived attribute quality as explanatory variables and overall evaluation measures as dependent variables. Depending on the magnitude of the elasticity, service attributes are classified into 3 categories: attributes with diminishing, constant, or increasing returns to overall evaluation. Results: The proposed approach revealed new insights into what patients value when visiting physicians and what they take for granted. Improvements in the physicians’ pleasantness and friendliness have increasing returns to the publicly available overall evaluation (b=1.26). The practices’ cleanliness (b=1.05) and the communication behavior of a physician during a visit (b level between .97 and 1.03) have constant returns. Indiscretion in the waiting rooms, extended waiting times, and a lack of modernity of the medical equipment (b level between .46 and .59) have the strongest diminishing returns to overall evaluation. Conclusions: The categorization of the service attributes supports physicians in identifying potential for improvements and prioritizing resource allocation to improve the publicly available overall evaluation ratings on PRWs. Thus, the study contributes to patient-centered health care management and, furthermore, promotes the utility of PRWs through large-scale data analysis. %M 32012063 %R 10.2196/13830 %U https://www.jmir.org/2020/2/e13830 %U https://doi.org/10.2196/13830 %U http://www.ncbi.nlm.nih.gov/pubmed/32012063 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 7 %N 4 %P e13053 %T Measuring Regional Quality of Health Care Using Unsolicited Online Data: Text Analysis Study %A Hendrikx,Roy Johannus Petrus %A Drewes,Hanneke Wil-Trees %A Spreeuwenberg,Marieke %A Ruwaard,Dirk %A Baan,Caroline %+ Tranzo Scientific Center for Care and Welfare, Tilburg University, Warandelaan 2, Tilburg, 5000 LE, Netherlands, 31 611647091, roy.hendrikx@rivm.nl %K text mining %K population health management %K regional care %K quality of care %K online data %K big data %K patient-reported experience measures %D 2019 %7 16.12.2019 %9 Original Paper %J JMIR Med Inform %G English %X Background: Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses. Objective: The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating. Methods: The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning—naïve Bayes and random forest models—was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives. Results: A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being “taken seriously” was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives. Conclusions: Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful. %M 31841116 %R 10.2196/13053 %U http://medinform.jmir.org/2019/4/e13053/ %U https://doi.org/10.2196/13053 %U http://www.ncbi.nlm.nih.gov/pubmed/31841116 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 7 %N 4 %P e16185 %T How Online Reviews and Services Affect Physician Outpatient Visits: Content Analysis of Evidence From Two Online Health Care Communities %A Lu,Wei %A Wu,Hong %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Hubei Province, Wuhan, 430060, China, 86 132 7794 2186, wuhong634214924@163.com %K online health care communities %K online reviews %K online services %K outpatient care %K channel effect %K patient choice %D 2019 %7 2.12.2019 %9 Original Paper %J JMIR Med Inform %G English %X Background: Online healthcare communities are changing the ways of physician-patient communication and how patients choose outpatient care physicians. Although a majority of empirical work has examined the role of online reviews in consumer decisions, less research has been done in health care, and endogeneity of online reviews has not been fully considered. Moreover, the important factor of physician online services has been neglected in patient decisions. Objective: In this paper, we addressed the endogeneity of online reviews and examined the impact of online reviews and services on outpatient visits based on theories of reviews and channel effects. Methods: We used a difference-in-difference approach to account for physician- and website-specific effects by collecting information from 474 physician homepages on two online health care communities. Results: We found that the number of reviews was more effective in influencing patient decisions compared with the overall review rating. An improvement in reviews leads to a relative increase in physician outpatient visits on that website. There are channel effects in health care: online services complement offline services (outpatient care appointments). Results further indicate that online services moderate the relationship between online reviews and physician outpatient visits. Conclusions: This study investigated the effect of reviews and channel effects in health care by conducting a difference-in-difference analysis on two online health care communities. Our findings provide basic research on online health care communities. %M 31789597 %R 10.2196/16185 %U http://medinform.jmir.org/2019/4/e16185/ %U https://doi.org/10.2196/16185 %U http://www.ncbi.nlm.nih.gov/pubmed/31789597 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 11 %P e13371 %T Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study %A Borchert,Jill S %A Wang,Bo %A Ramzanali,Muzaina %A Stein,Amy B %A Malaiyandi,Latha M %A Dineley,Kirk E %+ College of Graduate Studies, Midwestern University, 555 31st Street, Downers Grove, IL, 60515, United States, 1 6309603907, kdinel@midwestern.edu %K drug safety %K drug ineffective %K postmarketing %K pharmacovigilance %K internet %K pharmacoepidemiology %K adverse effect %K hypnotic %K insomnia %K patient-reported outcomes %D 2019 %7 8.11.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient online drug reviews are a resource for other patients seeking information about the practical benefits and drawbacks of drug therapies. Patient reviews may also serve as a source of postmarketing safety data that are more user-friendly than regulatory databases. However, the reliability of online reviews has been questioned, because they do not undergo professional review and lack means of verification. Objective: We evaluated online reviews of hypnotic medications, because they are commonly used and their therapeutic efficacy is particularly amenable to patient self-evaluation. Our primary objective was to compare the types and frequencies of adverse events reported to the Food and Drug Administration Adverse Event Reporting System (FAERS) with analogous information in patient reviews on the consumer health website Drugs.com. The secondary objectives were to describe patient reports of efficacy and adverse events and assess the influence of medication cost, effectiveness, and adverse events on user ratings of hypnotic medications. Methods: Patient ratings and narratives were retrieved from 1407 reviews on Drugs.com between February 2007 and March 2018 for eszopiclone, ramelteon, suvorexant, zaleplon, and zolpidem. Reviews were coded to preferred terms in the Medical Dictionary for Regulatory Activities. These reviews were compared to 5916 cases in the FAERS database from January 2015 to September 2017. Results: Similar adverse events were reported to both Drugs.com and FAERS. Both resources identified a lack of efficacy as a common complaint for all five drugs. Both resources revealed that amnesia commonly occurs with eszopiclone, zaleplon, and zolpidem, while nightmares commonly occur with suvorexant. Compared to FAERS, online reviews of zolpidem reported a much higher frequency of amnesia and partial sleep activities. User ratings were highest for zolpidem and lowest for suvorexant. Statistical analyses showed that patient ratings are influenced by considerations of efficacy and adverse events, while drug cost is unimportant. Conclusions: For hypnotic medications, online patient reviews and FAERS emphasized similar adverse events. Online reviewers rated drugs based on perception of efficacy and adverse events. We conclude that online patient reviews of hypnotics are a valid source that can supplement traditional adverse event reporting systems. %M 31702558 %R 10.2196/13371 %U http://www.jmir.org/2019/11/e13371/ %U https://doi.org/10.2196/13371 %U http://www.ncbi.nlm.nih.gov/pubmed/31702558 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 9 %P e14336 %T The Content and Nature of Narrative Comments on Swiss Physician Rating Websites: Analysis of 849 Comments %A McLennan,Stuart %+ Institute of History and Ethics in Medicine, Technical University of Munich, Ismaninger Straße 22, Munich, 81675, Germany, 49 089 4140 4041, stuart.mclennan@tum.de %K physician rating websites %K patient satisfaction %D 2019 %7 30.9.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: The majority of physician rating websites (PRWs) provide users the option to leave narrative comments about their physicians. Narrative comments potentially provide richer insights into patients’ experiences and feelings that cannot be fully captured in predefined quantitative rating scales and are increasingly being examined. However, the content and nature of narrative comments on Swiss PRWs has not been examined to date. Objective: This study aimed to examine (1) the types of issues raised in narrative comments on Swiss PRWs and (2) the evaluation tendencies of the narrative comments. Methods: A random stratified sample of 966 physicians was generated from the regions of Zürich and Geneva. Every selected physician was searched for on 3 PRWs (OkDoc, DocApp, and Medicosearch) and Google, and narrative comments were collected. Narrative comments were analyzed and classified according to a theoretical categorization framework of physician-, staff-, and practice-related issues. Results: The selected physicians had a total of 849 comments. In total, 43 subcategories addressing the physician (n=21), staff (n=8), and practice (n=14) were identified. None of the PRWs’ comments covered all 43 subcategories of the categorization framework; comments on Google covered 86% (37/43) of the subcategories, Medicosearch covered 72% (31/43), DocApp covered 60% (26/43), and OkDoc covered 56% (24/43). In total, 2441 distinct issues were identified within the 43 subcategories of the categorization framework; 83.65% (2042/2441) of the issues related to the physician, 6.63% (162/2441) related to the staff, and 9.70% (237/2441) related to the practice. Overall, 95% (41/43) of the subcategories of the categorization framework and 81.60% (1992/2441) of the distinct issues identified were concerning aspects of performance (interpersonal skills of the physician and staff, infrastructure, and organization and management of the practice) that are considered assessable by patients. Overall, 83.0% (705/849) of comments were classified as positive, 2.5% (21/849) as neutral, and 14.5% (123/849) as negative. However, there were significant differences between PRWs, regions, and specialty regarding negative comments: 90.2% (111/123) of negative comments were on Google, 74.7% (92/123) were regarding physicians in Zurich, and 73.2% (90/123) were from specialists. Conclusions: From the narrative comments analyzed, it can be reported that interpersonal issues make up nearly half of all negative issues identified, and it is recommended that physicians should focus on improving these issues. The current suppression of negative comments by Swiss PRWs is concerning, and there is a need for a consensus-based criterion to be developed to determine which comments should be published publicly. Finally, it would be helpful if Swiss patients are made aware of the current large differences between Swiss PRWs regarding the frequency and nature of ratings to help them determine which PRW will provide them with the most useful information. %M 31573918 %R 10.2196/14336 %U http://www.jmir.org/2019/9/e14336/ %U https://doi.org/10.2196/14336 %U http://www.ncbi.nlm.nih.gov/pubmed/31573918 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 8 %P e10195 %T Association of Social Media Presence with Online Physician Ratings and Surgical Volume Among California Urologists: Observational Study %A Houman,Justin %A Weinberger,James %A Caron,Ashley %A Hannemann,Alex %A Zaliznyak,Michael %A Patel,Devin %A Moradzadeh,Ariel %A Daskivich,Timothy J %+ Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, United States, 1 7149287950, justin.houman@cshs.org %K social media %K surgical volume %K physician ratings %D 2019 %7 13.08.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Urologists are increasingly using various forms of social media to promote their professional practice and attract patients. Currently, the association of social media on a urologists’ practice is unknown. Objectives: We aimed to determine whether social media presence is associated with higher online physician ratings and surgical volume among California urologists. Methods: We sampled 195 California urologists who were rated on the ProPublica Surgeon Scorecard website. We obtained information on professional use of online social media (Facebook, Instagram, Twitter, blog, and YouTube) in 2014 and defined social media presence as a binary variable (yes/no) for use of an individual platform or any platform. We collected data on online physician ratings across websites (Yelp, Healthgrades, Vitals, RateMD, and UCompareHealthcare) and calculated the mean physician ratings across all websites as an average weighted by the number of reviews. We then collected data on surgical volume for radical prostatectomy from the ProPublica Surgeon Scorecard website. We used multivariable linear regression to determine the association of social media presence with physician ratings and surgical volume. Results: Among our sample of 195 urologists, 62 (32%) were active on some form of social media. Social media presence on any platform was associated with a slightly higher mean physician rating (β coefficient: .3; 95% CI 0.03-0.5; P=.05). However, only YouTube was associated with higher physician ratings (β coefficient: .3; 95% CI 0.2-0.5; P=.04). Social media presence on YouTube was strongly associated with increased radical prostatectomy volume (β coefficient: 7.4; 95% CI 0.3-14.5; P=.04). Social media presence on any platform was associated with increased radical prostatectomy volume (β coefficient: 7.1; 95% CI –0.7 to 14.2; P=.05). Conclusions: Urologists’ use of social media, especially YouTube, is associated with a modest increase in physician ratings and prostatectomy volume. Although a majority of urologists are not currently active on social media, patients may be more inclined to endorse and choose subspecialist urologists who post videos of their surgical technique. %M 31411141 %R 10.2196/10195 %U https://www.jmir.org/2019/8/e10195/ %U https://doi.org/10.2196/10195 %U http://www.ncbi.nlm.nih.gov/pubmed/31411141 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 8 %P e14634 %T What Do Patients Complain About Online: A Systematic Review and Taxonomy Framework Based on Patient Centeredness %A Liu,Jing %A Hou,Shengchao %A Evans,Richard %A Xia,Chenxi %A Xia,Weidong %A Ma,Jingdong %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No 13 Hangkong Road, Qiaokou District, Wuhan,, China, 86 27 83692826, jdma@hust.edu.cn %K patient-centered care %K delivery of health care %K systematic review %K taxonomy %D 2019 %7 07.08.2019 %9 Review %J J Med Internet Res %G English %X Background: Complaints made online by patients about their health care experiences are becoming prevalent because of widespread worldwide internet connectivity. An a priori framework, based on patient centeredness, may be useful in identifying the types of issues patients complain about online across multiple settings. It may also assist in examining whether the determinants of patient-centered care (PCC) mirror the determinants of patient experiences. Objective: The objective of our study was to develop a taxonomy framework for patient complaints online based on patient centeredness and to examine whether the determinants of PCC mirror the determinants of patient experiences. Methods: First, the best fit framework synthesis technique was applied to develop the proposed a priori framework. Second, electronic databases, including Web of Science, Scopus, and PubMed, were searched for articles published between 2000 and June 2018. Studies were only included if they collected primary quantitative data on patients’ online complaints. Third, a deductive and inductive thematic analysis approach was adopted to code the themes of recognized complaints into the framework. Results: In total, 17 studies from 5 countries were included in this study. Patient complaint online taxonomies and theme terms varied. According to our framework, patients expressed most dissatisfaction with patient-centered processes (101,586/204,363, 49.71%), followed by prerequisites (appropriate skills and knowledge of physicians; 50,563, 24.74%) and the care environment (48,563/204,363, 23.76%). The least dissatisfied theme was expected outcomes (3651/204,363, 1.79%). People expressed little dissatisfaction with expanded PCC dimensions, such as involvement of family and friends (591/204,363, 0.29%). Variation in the concerns across different countries’ patients were also observed. Conclusions: Online complaints made by patients are of major value to health care providers, regulatory bodies, and patients themselves. Our PCC framework can be applied to analyze them under a wide range of conditions, treatments, and countries. This review has shown significant heterogeneity of patients’ online complaints across different countries. %M 31392961 %R 10.2196/14634 %U https://www.jmir.org/2019/8/e14634/ %U https://doi.org/10.2196/14634 %U http://www.ncbi.nlm.nih.gov/pubmed/31392961 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 7 %P e13816 %T Quantitative Ratings and Narrative Comments on Swiss Physician Rating Websites: Frequency Analysis %A McLennan,Stuart %+ Institute of History and Ethics in Medicine, Technical University of Munich, Ismaninger Straße 22, Munich, 81675, Germany, 49 089 4140 4041, stuart.mclennan@tum.de %K physician rating websites %K patient satisfaction %K Switzerland %D 2019 %7 26.07.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRWs) have been developed as part of a wider move toward transparency around health care quality, and these allow patients to anonymously rate, comment, and discuss physicians’ quality on the Web. The first Swiss PRWs were established in 2008, at the same time as many international PRWs. However, there has been limited research conducted on PRWs in Switzerland to date. International research has indicated that a key shortcoming of PRWs is that they have an insufficient number of ratings. Objective: The aim of this study was to examine the frequency of quantitative ratings and narrative comments on the Swiss PRWs. Methods: In November 2017, a random stratified sample of 966 physicians was generated from the regions of Zürich and Geneva. Every selected physician was searched for on 4 rating websites (OkDoc, DocApp, Medicosearch, and Google) between November 2017 and July 2018. It was recorded whether the physician could be identified, what the physician’s quantitative rating was, and whether the physician had received narrative comments. In addition, Alexa Internet was used to examine the number of visitors to the PRWs, compared with other websites. Results: Overall, the portion of physicians able to be identified on the PRWs ranged from 42.4% (410/966) on OkDoc to 87.3% (843/966) on DocApp. Of the identifiable physicians, only a few of the selected physicians had been rated quantitatively (4.5% [38/843] on DocApp to 49.8% [273/548] on Google) or received narrative comments (4.5% [38/843] on DocApp to 31.2% [171/548] on Google) at least once. Rated physicians also had, on average, a low number of quantitative ratings (1.47 ratings on OkDoc to 3.74 rating on Google) and narrative comments (1.23 comment on OkDoc to 3.03 comments on Google). All 3 websites allowing ratings used the same rating scale (1-5 stars) and had a very positive average rating: DocApp (4.71), Medicosearch (4.69), and Google (4.41). There were significant differences among the PRWs (with the majority of ratings being posted on Google in past 2 years) and regions (with physicians in Zurich more likely to have been rated and have more ratings on average). Only Google (position 1) and Medicosearch (position 8358) are placed among the top 10,000 visited websites in Switzerland. Conclusions: It appears that this is the first time Google has been included in a study examining physician ratings internationally and it is noticeable how Google has had substantially more ratings than the 3 dedicated PRWs in Switzerland over the past 2 and a half years. Overall, this study indicates that Swiss PRWs are not yet a reliable source of unbiased information regarding patient experiences and satisfaction with Swiss physicians; many selected physicians were unable to be identified, only a few physicians had been rated, and the ratings posted were overwhelmingly positive. %M 31350838 %R 10.2196/13816 %U http://www.jmir.org/2019/7/e13816/ %U https://doi.org/10.2196/13816 %U http://www.ncbi.nlm.nih.gov/pubmed/31350838 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 7 %P e12436 %T Online Ratings of Urologists: Comprehensive Analysis %A Pike,C William %A Zillioux,Jacqueline %A Rapp,David %+ Department of Urology, University of Virginia Medical Center, 500 Ray C Hunt Drive, Charlottesville, VA, 22908, United States, 1 8043859511, derapp@yahoo.com %K online physician ratings %K urology %K reputation management %D 2019 %7 02.07.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician-rating websites are being increasingly used by patients to help guide physician choice. As such, an understanding of these websites and factors that influence ratings is valuable to physicians. Objective: We sought to perform a comprehensive analysis of online urology ratings information, with a specific focus on the relationship between number of ratings or comments and overall physician rating. Methods: We analyzed urologist ratings on the Healthgrades website. The data retrieval focused on physician and staff ratings information. Our analysis included descriptive statistics of physician and staff ratings and correlation analysis between physician or staff performance and overall physician rating. Finally, we performed a best-fit analysis to assess for an association between number of physician ratings and overall rating. Results: From a total of 9921 urology profiles analyzed, there were 99,959 ratings and 23,492 comments. Most ratings were either 5 (“excellent”) (67.53%, 67,505/99,959) or 1 (“poor”) (24.22%, 24,218/99,959). All physician and staff performance ratings demonstrated a positive and statistically significant correlation with overall physician rating (P<.001 for all analyses). Best-fit analysis demonstrated a negative relationship between number of ratings or comments and overall rating until physicians achieved 21 ratings or 6 comments. Thereafter, a positive relationship was seen. Conclusions: In our study, a dichotomous rating distribution was seen with more than 90% of ratings being either excellent or poor. A negative relationship between number of ratings or comments and overall rating was initially seen, after which a positive relationship was demonstrated. Combined, these data suggest that physicians can benefit from understanding online ratings and that proactive steps to encourage patient rating submissions may help optimize overall rating. %M 31267982 %R 10.2196/12436 %U https://www.jmir.org/2019/7/e12436/ %U https://doi.org/10.2196/12436 %U http://www.ncbi.nlm.nih.gov/pubmed/31267982 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 6 %P e11188 %T The Impact of Web-Based Ratings on Patient Choice of a Primary Care Physician Versus a Specialist: Randomized Controlled Experiment %A Li,Siyue %A Hubner,Austin %+ College of Media and International Culture, Zhejiang University, Tianmushan Rd #148, Hangzhou, 310000, China, 86 87951596, siyueaprilli@gmail.com %K technical skills %K interpersonal skills %K physician ratings %K physician selection %D 2019 %7 28.06.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician review websites have empowered prospective patients to acquire information about physicians. However, little is known about how Web-based ratings on different aspects of a physician may affect patients’ selection of physicians differently. Objective: The objectives of this study were to examine (1) how patients weigh ratings on a physician’s technical skills and interpersonal skills in their selection of physicians and (2) whether and how people’s choice of a primary care physician versus a specialist is affected differently by Web-based ratings. Methods: A 2×2×2×2 between-subjects experiment was conducted. Over 600 participants were recruited through a crowdsourcing website and randomly assigned to view a mockup physician review Web page that contained information on a physician’s basic information and patients’ ratings. After reviewing the Web page, participants were asked to complete a survey on their perceptions of the physician and willingness to seek health care from the physician. Results: The results showed that participants were more willing to choose a physician with higher ratings on technical skills than on interpersonal skills compared with a physician with higher ratings on interpersonal skills than on technical skills, t369.96=22.36, P<.001, Cohen d=1.22. In the selection of different types of physicians, patients were more likely to choose a specialist with higher ratings on technical skills than on interpersonal skills, compared with a primary care physician with the same ratings, F1,521=5.34, P=.021. Conclusions: The findings suggest that people place more weight on technical skills than interpersonal skills in their selection of a physician based on their ratings on the Web. Specifically, people are more likely to make a compromise on interpersonal skills in their choice of a specialist compared with a primary care physician. This study emphasizes the importance of examining Web-based physician ratings in a more nuanced way in relation to the selection of different types of physicians. Trial Registration: ISRCTN Registry ISRCTN91316463; http://www.isrctn.com/ISRCTN91316463 %M 31254337 %R 10.2196/11188 %U http://www.jmir.org/2019/6/e11188/ %U https://doi.org/10.2196/11188 %U http://www.ncbi.nlm.nih.gov/pubmed/31254337 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 6 %P e12454 %T When Similarity Beats Expertise—Differential Effects of Patient and Expert Ratings on Physician Choice: Field and Experimental Study %A Kranzbühler,Anne-Madeleine %A Kleijnen,Mirella H P %A Verlegh,Peeter W J %A Teerling,Marije %+ Department of Product Innovation Management, Delft University of Technology, Landbergstraat 15, Delft, 2628 CE, Netherlands, 31 152783451, a.kranzbuhler@tudelft.nl %K decision making %K choice behavior %K judgment %D 2019 %7 26.06.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Increasing numbers of patients consult Web-based rating platforms before making health care decisions. These platforms often provide ratings from other patients, reflecting their subjective experience. However, patients often lack the knowledge to be able to judge the objective quality of health services. To account for this potential bias, many rating platforms complement patient ratings with more objective expert ratings, which can lead to conflicting signals as these different types of evaluations are not always aligned. Objective: This study aimed to fill the gap on how consumers combine information from 2 different sources—patients or experts—to form opinions and make purchase decisions in a health care context. More specifically, we assessed prospective patients’ decision making when considering both types of ratings simultaneously on a Web-based rating platform. In addition, we examined how the influence of patient and expert ratings is conditional upon rating volume (ie, the number of patient opinions). Methods: In a field study, we analyzed a dataset from a Web-based physician rating platform containing clickstream data for more than 5000 US doctors. We complemented this with an experimental lab study consisting of a sample of 112 students from a Dutch university. The average age was 23.1 years, and 60.7% (68/112) of the respondents were female. Results: The field data illustrated the moderating effect of rating volume. If the patient advice was based on small numbers, prospective patients tended to base their selection of a physician on expert rather than patient advice (profile clicks beta=.14, P<.001; call clicks beta=.28, P=.03). However, when the group of patients substantially grew in size, prospective patients started to rely on patients rather than the expert (profile clicks beta=.23, SE=0.07, P=.004; call clicks beta=.43, SE=0.32, P=.10). The experimental study replicated and validated these findings for conflicting patient versus expert advice in a controlled setting. When patient ratings were aggregated from a high number of opinions, prospective patients’ evaluations were affected more strongly by patient than expert advice (meanpatient positive/expert negative=3.06, SD=0.94; meanexpert positive/patient negative=2.55, SD=0.89; F1,108=4.93, P=.03). Conversely, when patient ratings were aggregated from a low volume, participants were affected more strongly by expert compared with patient advice (meanpatient positive/expert negative=2.36, SD=0.76; meanexpert positive/patient negative=3.01, SD=0.81; F1,108=8.42, P=.004). This effect occurred despite the fact that they considered the patients to be less knowledgeable than experts. Conclusions: When confronted with information from both sources simultaneously, prospective patients are influenced more strongly by other patients. This effect reverses when the patient rating has been aggregated from a (very) small number of individual opinions. This has important implications for how to present health care provider ratings to prospective patients to aid their decision-making process. %M 31244481 %R 10.2196/12454 %U http://www.jmir.org/2019/6/e12454/ %U https://doi.org/10.2196/12454 %U http://www.ncbi.nlm.nih.gov/pubmed/31244481 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 4 %P e11646 %T “But His Yelp Reviews Are Awful!”: Analysis of General Surgeons’ Yelp Reviews %A Liu,Cynthia %A Uffenheimer,Meka %A Nasseri,Yosef %A Cohen,Jason %A Ellenhorn,Joshua %+ The Surgery Group of Los Angeles, Research Foundation, Suite 880W, 8635 W 3rd Street, Los Angeles, CA, 90048, United States, 1 310 289 1518, yosefnasseri@gmail.com %K patient satisfaction %K general surgery %K Los Angeles %K Web-based ratings %K digital health %K Yelp %D 2019 %7 30.04.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients use Web-based platforms to review general surgeons. However, little is known about the free-form text and structured content of the reviews or how they relate to the physicians’ characteristics or their practices. Objective: This observational study aimed to analyze the Web-based reviews of general surgeons on the west side of Los Angeles. Methods: Demographics, practice characteristics, and Web-based presence were recorded. We evaluated frequency and types of Yelp reviews and assigned negative remarks to 5 categories. Tabulated results were evaluated using independent t test, one-way analysis of variance, and Pearson correlation analysis to determine associations between the number of total and negative reviews with respect to practice structure and physician characteristics. Results: Of the 146 general surgeons, 51 (35%) had at least 1 review and 29 (20%) had at least 1 negative review. There were 806 total reviews, 679 (84.2%) positive reviews and 127 (15.8%) negative reviews. The negative reviews contained a total of 376 negative remarks, categorized into physician demeanor (124/376, 32.9%), clinical outcomes (81/376, 22%), office or staff (83/376, 22%), scheduling (44/376, 12%), and billing (44/376, 12%). Surgeons with a professional website had significantly more reviews than those without (P=.003). Surgeons in private practice had significantly more reviews (P=.002) and more negative reviews (P=.03) than surgeons who were institution employed. A strong and direct correlation was found between a surgeon’s number of reviews and number of negative reviews (P<.001). Conclusions: As the most common category of complaints was about physician demeanor, surgeons may optimize their Web-based reputation by improving their bedside manner. A surgeon’s Web presence, private practice, and the total number of reviews are significantly associated with both positive and negative reviews. %M 31038463 %R 10.2196/11646 %U http://www.jmir.org/2019/4/e11646/ %U https://doi.org/10.2196/11646 %U http://www.ncbi.nlm.nih.gov/pubmed/31038463 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 4 %P e12521 %T What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews %A Hong,Y Alicia %A Liang,Chen %A Radcliff,Tiffany A %A Wigfall,Lisa T %A Street,Richard L %+ Department of Health Administration and Policy, George Mason University, 4400 University Drive, MS 1J3, Fairfax, VA, 22030, United States, 1 703 993 1929, yhong22@gmu.edu %K patient review websites %K patient online review %K systematic review %D 2019 %7 8.4.2019 %9 Review %J J Med Internet Res %G English %X Background: The number of patient online reviews (PORs) has grown significantly, and PORs have played an increasingly important role in patients’ choice of health care providers. Objective: The objective of our study was to systematically review studies on PORs, summarize the major findings and study characteristics, identify literature gaps, and make recommendations for future research. Methods: A major database search was completed in January 2019. Studies were included if they (1) focused on PORs of physicians and hospitals, (2) reported qualitative or quantitative results from analysis of PORs, and (3) peer-reviewed empirical studies. Study characteristics and major findings were synthesized using predesigned tables. Results: A total of 63 studies (69 articles) that met the above criteria were included in the review. Most studies (n=48) were conducted in the United States, including Puerto Rico, and the remaining were from Europe, Australia, and China. Earlier studies (published before 2010) used content analysis with small sample sizes; more recent studies retrieved and analyzed larger datasets using machine learning technologies. The number of PORs ranged from fewer than 200 to over 700,000. About 90% of the studies were focused on clinicians, typically specialists such as surgeons; 27% covered health care organizations, typically hospitals; and some studied both. A majority of PORs were positive and patients’ comments on their providers were favorable. Although most studies were descriptive, some compared PORs with traditional surveys of patient experience and found a high degree of correlation and some compared PORs with clinical outcomes but found a low level of correlation. Conclusions: PORs contain valuable information that can generate insights into quality of care and patient-provider relationship, but it has not been systematically used for studies of health care quality. With the advancement of machine learning and data analysis tools, we anticipate more research on PORs based on testable hypotheses and rigorous analytic methods. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42018085057; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=85057 (Archived by WebCite at http://www.webcitation.org/76ddvTZ1C) %R 10.2196/12521 %U http://www.jmir.org/2019/4/e12521/ %U https://doi.org/10.2196/12521 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 5 %N 1 %P e10530 %T Investigation of Radiation Oncologists’ Awareness of Online Reputation Management %A Waxer,Jonathan Fredric %A Srivastav,Sudesh %A DiBiase,Christian Steven %A DiBiase,Steven Joseph %+ Department of Radiation Oncology, New York-Presbyterian Queens, Weill Cornell Medicine, 56-45 Main Street, Flushing, NY, 11355, United States, 1 718 670 1501, sdibiase@tulane.edu %K reputation %K management %K internet %K patient satisfaction %K surveys and questionnaires %K radiation oncology %D 2019 %7 01.04.2019 %9 Original Paper %J JMIR Cancer %G English %X Background: Online reputation management (ORM) is an emerging practice strategy that emphasizes the systematic and proactive monitoring of online reviews relating to one’s professional reputation. Objective: We developed this survey project to assess whether radiation oncologists are aware of ORM and how it is utilized in their practices. We hypothesized that ORM is largely unknown by most practicing radiation oncologists and that little time is spent actively managing their reputations. Methods: An online survey was submitted to 1222 radiation oncologists using the Qualtrics research platform. Physician emails were gathered from the American Society for Radiation Oncology member directory. A total of 85 physicians initiated the survey, whereas 76 physicians completed more than or equal to 94% (15/16) of the survey questions and were subsequently used in our analyses. The survey consisted of 15 questions querying practice demographics, patient satisfaction determination, ORM understanding, and activities to address ORM and 1 question for physicians to opt-in to a US $50 Amazon gift card raffle. The survey data were summarized using a frequency table, and data were analyzed using the Chi-square test, Fisher exact test, and Spearman correlation coefficients. Results: We calculated a 7% (85/1222) response rate for our survey, with a completion rate of 89% (76/85). A majority of respondents (97%, 74/76) endorsed being somewhat or strongly concerned about patient satisfaction (P<.001). However, 58% (44/76) of respondents reported spending 0 hours per week reviewing or managing their online reputation and 39% (30/76) reported spending less than 1 hour per week (P<.001). A majority of physicians (58%, 44/76) endorsed no familiarity with ORM (P<.001) and 70% (53/76) did not actively manage their online reputation (P<.001). Although 83% (63/76) of respondents strongly or somewhat believed that patients read online reviews (P<.001), 57% (43/76) of respondents did not check their online reviews (P=.25) and 80% (61/76) endorsed never responding to online reviews (P<.001). Moreover, 58% (44/76) of the respondents strongly or somewhat supported the idea of managing their online reputation going forward (P=.001). In addition, 11 out of the 28 pairs of questions asked in our correlation studies reached statistical significance. Degree of concern for patient satisfaction and the notion of managing one’s ORM going forward were the 2 most frequently correlated topics of statistical significance in our analyses. Conclusions: ORM is presently under-recognized in radiation oncology. Although most practitioners are concerned about patient satisfaction, little effort is directed toward the internet on this matter. ORM offers an area of practice improvement for many practicing radiation oncologists. %M 30932863 %R 10.2196/10530 %U https://cancer.jmir.org/2019/1/e10530/ %U https://doi.org/10.2196/10530 %U http://www.ncbi.nlm.nih.gov/pubmed/30932863 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 3 %P e12007 %T Reporting of Patient Experience Data on Health Systems’ Websites and Commercial Physician-Rating Websites: Mixed-Methods Analysis %A Lagu,Tara %A Norton,Caroline M %A Russo,Lindsey M %A Priya,Aruna %A Goff,Sarah L %A Lindenauer,Peter K %+ Baystate Health, Institute for Healthcare Delivery and Population Science and Department of Medicine, University of Massachusetts Medical School-Baystate, 3601 Main St, Springfield, MA, 01199, United States, 1 4137947688, lagutc@gmail.com %K physician reviews %K social networking %K public reporting %D 2019 %7 27.03.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Some hospitals’ and health systems’ websites report physician-level ratings and comments drawn from the Consumer Assessment of Healthcare Providers and Systems surveys. Objective: The aim was to examine the prevalence and content of health system websites reporting these data and compare narratives from these sites to narratives from commercial physician-rating sites. Methods: We identified health system websites active between June 1 and 30, 2016, that posted clinician reviews. For 140 randomly selected clinicians, we extracted the number of star ratings and narrative comments. We conducted a qualitative analysis of a random sample of these physicians’ narrative reviews and compared these to a random sample of reviews from commercial physician-rating websites. We described composite quantitative scores for sampled physicians and compared the frequency of themes between reviews drawn from health systems’ and commercial physician-rating websites. Results: We identified 42 health systems that published composite star ratings (42/42, 100%) or narratives (33/42, 79%). Most (27/42, 64%) stated that they excluded narratives deemed offensive. Of 140 clinicians, the majority had composite scores listed (star ratings: 122/140, 87.1%; narrative reviews: 114/140, 81.4%), with medians of 110 star ratings (IQR 42-175) and 25.5 (IQR 13-48) narratives. The rating median was 4.8 (IQR 4.7-4.9) out of five stars, and no clinician had a score less than 4.2. Compared to commercial physician-rating websites, we found significantly fewer negative comments on health system websites (35.5%, 76/214 vs 12.8%, 72/561, respectively; P<.001). Conclusions: The lack of variation in star ratings on health system sites may make it difficult to differentiate between clinicians. Most health systems report that they remove offensive comments, and we notably found fewer negative comments on health system websites compared to commercial physician-rating sites. %M 30916654 %R 10.2196/12007 %U http://www.jmir.org/2019/3/e12007/ %U https://doi.org/10.2196/12007 %U http://www.ncbi.nlm.nih.gov/pubmed/30916654 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 3 %P e12156 %T Investigating the Effect of Paid and Free Feedback About Physicians' Telemedicine Services on Patients’ and Physicians’ Behaviors: Panel Data Analysis %A Yang,Hualong %A Zhang,Xiaofei %+ Business School, Nankai Univeristy, 94 Weijin Road, Tianjin, 300071, China, 86 22 23501039, xiaofeizhang@nankai.edu.cn %K telemedicine %K feedback %K physician rating %K health care quality %K decision making %K physicians’ contribution %D 2019 %7 22.03.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: In recent years, paid online patient-physician interaction has been incorporated into the telemedicine markets. With the development of telemedicine and telemedicine services, online feedback has been widely applied, helping other patients to identify quality services. Recently, in China, a new type of service feedback has been applied to the telemedicine markets, namely, paid feedback. Patients who are satisfied with a physician’s online service can buy a virtual gift or give a tip to the physicians. This paid feedback can improve the reliability of service feedback and reduce the proportion of false information because it increases the cost for feedback providers. Paid online feedback can benefit the physicians, such as by providing them with monetary incentives; however, research on the impacts and value of such paid feedback from the physician perspective in the telemedicine markets is scant. To fill this research gap, this study was designed to understand the role of paid feedback by developing a research model based on the theories of signaling and self-determination. Objective: This study aimed to explore the effects of free and paid feedback on patients’ choice and physicians’ behaviors as well as to investigate the substitute relationship between these 2 types of feedback in the telemedicine markets. Methods: A JAVA software program was used to collect online patient-doctor interaction data over a 6-month period from a popular telemedicine market in China (Good Physician Online). This study drew on a 2-equation panel model to test the hypotheses. Both fixed and random effect models were used to estimate the combined effects of paid feedback and free feedback on patients’ choice and physicians’ contribution. Finally, the Hausman test was adopted to investigate which model is better to explain our empirical results. Results: The results of this study show that paid feedback has a stronger effect on patients’ choice (a5=0.566; t2192=9.160; P<.001) and physicians’ contribution (β4=1.332; t2193=11.067; P<.001) in telemedicine markets than free feedback. Moreover, our research also proves that paid feedback and free feedback have a substitute relationship in determining patients’ and physicians’ behaviors (a6=−0.304; t2191=−5.805; P<.001 and β5=−0.823; t2192=−8.136; P<.001). Conclusions: Our findings contribute to the extant literature on service feedback in the telemedicine markets and provide insight for relevant stakeholders into how to design an effective feedback mechanism to improve patients’ service experience and physicians’ engagement. %M 30900997 %R 10.2196/12156 %U http://www.jmir.org/2019/3/e12156/ %U https://doi.org/10.2196/12156 %U http://www.ncbi.nlm.nih.gov/pubmed/30900997 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 3 %P e10170 %T The Effect of Online Effort and Reputation of Physicians on Patients’ Choice: 3-Wave Data Analysis of China’s Good Doctor Website %A Deng,Zhaohua %A Hong,Ziying %A Zhang,Wei %A Evans,Richard %A Chen,Yanyan %+ Smart Health Institute, School of Medicine and Health Management, Huazhong University of Science and Technology, No. 13 Hangkong Road, Qiaokou District, Wuhan, 430030, China, 86 13397110378, weizhanghust@hust.edu.cn %K physician-rating websites %K physician efforts %K physician reputations %K patient choices %K panel data analysis %D 2019 %7 08.03.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Nowadays, patients are seeking physician information more frequently via the internet. Physician-rating websites (PRWs) have been recognized as the most convenient way to gain insight and detailed information about specific physicians before receiving consultation. However, little is known about how the information provided on PRWs may affect patients’ decisions to seek medical advice. Objective: This study aimed to examine whether the physicians’ online efforts and their reputation have a relationship with patients’ choice of physician on PRWs. Methods: A model, based on social exchange theory, was developed to analyze the factors associated with the number of online patients. A 3-wave data collection exercise, covering 4037 physicians on China’s Good Doctor website, was conducted during the months of February, April, and June 2017. Increases in consultation in a 60-day period were used as the dependent variable, whereas 2 series of data were analyzed using linear regression modeling. The fixed-effect model was used to analyze the 3-wave data. Results: The adjusted R2 value in the linear regression models were 0.28 and 0.27, whereas in the fixed-effect model, it was .30. Both the linear regression and fixed-effect models yielded a good fit. A positive effect of physicians’ effort on the aggregated number of online patients was identified in all models (R2=0.30 and R2=0.37 in 2 regression models; R2=0.23 in fixed effect model; P<.001). The proxies of physicians’ reputations indicated different results, with total number of page views of physicians’ homepages (R2=0.43 and R2=0.46; R2=0.16; P<.001) and number of votes received (R2=0.33 and R2=0.27; R2=0.43; P<.001) being seen as positive. Virtual gifts were not significant in all models, whereas thank-you messages were only significant in the fixed-effect model (R2=0.11; P=.02). The effort made by physicians online is positively associated with their aggregated number of patients consulted, whereas the effect of a physician’s reputation remains uncertain. The control effect of a physician’s title and hospital’s level was not significant in all linear regressions. Conclusions: Both the effort and reputation of physicians online contribute to the increased number of online patients’ consultation; however, the influence of a physician’s reputation varies. This may imply that physicians’ online effort and reputation are critical in attracting patients and that strategic manipulation of physician profiles is worthy of study. Practical insights are also discussed. %M 30848726 %R 10.2196/10170 %U https://www.jmir.org/2019/3/e10170/ %U https://doi.org/10.2196/10170 %U http://www.ncbi.nlm.nih.gov/pubmed/30848726 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 11 %P e11141 %T Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms %A Rivas,Ryan %A Montazeri,Niloofar %A Le,Nhat XT %A Hristidis,Vagelis %+ Department of Computer Science and Engineering, University of California, Riverside, 363 Winston Chung Hall, 900 University Avenue, Riverside, CA, 92521, United States, 1 951 827 2838, rriva002@ucr.edu %K patient satisfaction %K patient reported outcome measures %K quality indicators, health care %K supervised machine learning %D 2018 %7 12.11.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: An increasing number of doctor reviews are being generated by patients on the internet. These reviews address a diverse set of topics (features), including wait time, office staff, doctor’s skills, and bedside manners. Most previous work on automatic analysis of Web-based customer reviews assumes that (1) product features are described unambiguously by a small number of keywords, for example, battery for phones and (2) the opinion for each feature has a positive or negative sentiment. However, in the domain of doctor reviews, this setting is too restrictive: a feature such as visit duration for doctor reviews may be expressed in many ways and does not necessarily have a positive or negative sentiment. Objective: This study aimed to adapt existing and propose novel text classification methods on the domain of doctor reviews. These methods are evaluated on their accuracy to classify a diverse set of doctor review features. Methods: We first manually examined a large number of reviews to extract a set of features that are frequently mentioned in the reviews. Then we proposed a new algorithm that goes beyond bag-of-words or deep learning classification techniques by leveraging natural language processing (NLP) tools. Specifically, our algorithm automatically extracts dependency tree patterns and uses them to classify review sentences. Results: We evaluated several state-of-the-art text classification algorithms as well as our dependency tree–based classifier algorithm on a real-world doctor review dataset. We showed that methods using deep learning or NLP techniques tend to outperform traditional bag-of-words methods. In our experiments, the 2 best methods used NLP techniques; on average, our proposed classifier performed 2.19% better than an existing NLP-based method, but many of its predictions of specific opinions were incorrect. Conclusions: We conclude that it is feasible to classify doctor reviews. Automatically classifying these reviews would allow patients to easily search for doctors based on their personal preference criteria. %M 30425030 %R 10.2196/11141 %U http://www.jmir.org/2018/11/e11141/ %U https://doi.org/10.2196/11141 %U http://www.ncbi.nlm.nih.gov/pubmed/30425030 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 11 %P e289 %T Correlations Between Hospitals’ Social Media Presence and Reputation Score and Ranking: Cross-Sectional Analysis %A Triemstra,Justin D %A Poeppelman,Rachel Stork %A Arora,Vineet M %+ Department of Pediatrics, Helen DeVos Children's Hospital, Michigan State University College of Human Medicine, 330 Barclay Avenue, Suite 203, Grand Rapids, MI,, United States, 1 616 391 2123, justin.triemstra@helendevoschildrens.org %K social media %K hospitals %K benchmarking %K hospital ranking %D 2018 %7 08.11.2018 %9 Short Paper %J J Med Internet Res %G English %X Background: The US News and World Report reputation score correlates strongly with overall rank in adult and pediatric hospital rankings. Social media affects how information is disseminated to physicians and is used by hospitals as a marketing tool to recruit patients. It is unclear whether the reputation score for adult and children’s hospitals relates to social media presence. Objective: The objective of our study was to analyze the association between a hospital’s social media metrics and the US News 2017-2018 Best Hospital Rankings for adult and children’s hospitals. Methods: We conducted a cross-sectional analysis of the reputation score, total score, and social media metrics (Twitter, Facebook, and Instagram) of hospitals who received at least one subspecialty ranking in the 2017-2018 US News publicly available annual rankings. Regression analysis was employed to analyze the partial correlation coefficients between social media metrics and a hospital’s total points (ie, rank) and reputation score for both adult and children’s hospitals while controlling for the bed size and time on Twitter. Results: We observed significant correlations for children’s hospitals’ reputation score and total points with the number of Twitter followers (total points: r=.465, P<.001; reputation: r=.524, P<.001) and Facebook followers (total points: r=.392, P=.002; reputation: r=.518, P<.001). Significant correlations for the adult hospitals reputation score were found with the number of Twitter followers (r=.848, P<.001), number of tweets (r=.535, P<.001), Klout score (r=.242, P=.02), and Facebook followers (r=.743, P<.001). In addition, significant correlations for adult hospitals total points were found with Twitter followers (r=.548, P<.001), number of tweets (r=.358, P<.001), Klout score (r=.203, P=.05), Facebook followers (r=.500, P<.001), and Instagram followers (r=.692, P<.001). Conclusions: A statistically significant correlation exists between multiple social media metrics and both a hospital’s reputation score and total points (ie, overall rank). This association may indicate that a hospital’s reputation may be influenced by its social media presence or that the reputation or rank of a hospital drives social media followers. %M 30409768 %R 10.2196/jmir.9713 %U http://www.jmir.org/2018/11/e289/ %U https://doi.org/10.2196/jmir.9713 %U http://www.ncbi.nlm.nih.gov/pubmed/30409768 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 10 %P e11085 %T Identification of Primary Medication Concerns Regarding Thyroid Hormone Replacement Therapy From Online Patient Medication Reviews: Text Mining of Social Network Data %A Park,So Hyun %A Hong,Song Hee %+ Research Institute of Pharmaceutical Science, College of Pharmacy, Seoul National University, Gwanak-gu Gwanak-ro 1, Seoul,, Republic Of Korea, 82 02 880 1547, songhhong@snu.ac.kr %K medication counseling %K social network data %K primary medication concerns %K satisfaction with levothyroxine treatment %D 2018 %7 24.10.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients with hypothyroidism report poor health-related quality of life despite having undergone thyroid hormone replacement therapy (THRT). Understanding patient concerns regarding levothyroxine can help improve the treatment outcomes of THRT. Objective: This study aimed to (1) identify the distinctive themes in patient concerns regarding THRT, (2) determine whether patients have unique primary medication concerns specific to their demographics, and (3) determine the predictability of primary medication concerns on patient treatment satisfaction. Methods: We collected patient reviews from WebMD in the United States (1037 reviews about generic levothyroxine and 1075 reviews about the brand version) posted between September 1, 2007, and January 30, 2017. We used natural language processing to identify the themes of medication concerns. Multiple regression analyses were conducted in order to examine the predictability of the primary medication concerns on patient treatment satisfaction. Results: Natural language processing of the patient reviews of levothyroxine posted on a social networking site produced 6 distinctive themes of patient medication concerns related to levothyroxine treatment: how to take the drug, treatment initiation, dose adjustment, symptoms of pain, generic substitutability, and appearance. Patients had different primary medication concerns unique to their gender, age, and treatment duration. Furthermore, treatment satisfaction on levothyroxine depended on what primary medication concerns the patient had. Conclusions: Natural language processing of text content available on social media could identify different themes of patient medication concerns that can be validated in future studies to inform the design of tailored medication counseling for improved patient treatment satisfaction. %M 30355555 %R 10.2196/11085 %U http://www.jmir.org/2018/10/e11085/ %U https://doi.org/10.2196/11085 %U http://www.ncbi.nlm.nih.gov/pubmed/30355555 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 5 %N 4 %P e10726 %T Identifying the Underlying Factors Associated With Patients’ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews %A Zolnoori,Maryam %A Fung,Kin Wah %A Fontelo,Paul %A Kharrazi,Hadi %A Faiola,Anthony %A Wu,Yi Shuan Shirley %A Stoffel,Virginia %A Patrick,Timothy %+ Section of Medical Informatics, Department of Health Science Research, Mayo Clinic, 200 First Street SW, Rochester, MN,, United States, 1 3175151950, Zolnoori.Maryam@mayo.edu %K medication adherence %K attitude %K perception %K antidepressive agents %K patient-centered care %K chronic disease %K depression %K community networks %K internet %K social media %K data mining %K framework method %D 2018 %7 30.9.2018 %9 Original Paper %J JMIR Ment Health %G English %X Background: Nonadherence to antidepressants is a major obstacle to deriving antidepressants’ therapeutic benefits, resulting in significant burdens on the individuals and the health care system. Several studies have shown that nonadherence is weakly associated with personal and clinical variables but strongly associated with patients’ beliefs and attitudes toward medications. Patients’ drug review posts in online health care communities might provide a significant insight into patients’ attitude toward antidepressants and could be used to address the challenges of self-report methods such as patients’ recruitment. Objective: The aim of this study was to use patient-generated data to identify factors affecting the patient’s attitude toward 4 antidepressants drugs (sertraline [Zoloft], escitalopram [Lexapro], duloxetine [Cymbalta], and venlafaxine [Effexor XR]), which in turn, is a strong determinant of treatment nonadherence. We hypothesized that clinical variables (drug effectiveness; adverse drug reactions, ADRs; perceived distress from ADRs, ADR-PD; and duration of treatment) and personal variables (age, gender, and patients’ knowledge about medications) are associated with patients’ attitude toward antidepressants, and experience of ADRs and drug ineffectiveness are strongly associated with negative attitude. Methods: We used both qualitative and quantitative methods to analyze the dataset. Patients’ drug reviews were randomly selected from a health care forum called askapatient. The Framework method was used to build the analytical framework containing the themes for developing structured data from the qualitative drug reviews. Then, 4 annotators coded the drug reviews at the sentence level using the analytical framework. After managing missing values, we used chi-square and ordinal logistic regression to test and model the association between variables and attitude. Results: A total of 892 reviews posted between February 2001 and September 2016 were analyzed. Most of the patients were females (680/892, 76.2%) and aged less than 40 years (540/892, 60.5%). Patient attitude was significantly (P<.001) associated with experience of ADRs, ADR-PD, drug effectiveness, perceived lack of knowledge, experience of withdrawal, and duration of usage, whereas oth age (F4,874=0.72, P=.58) and gender (χ24=2.7, P=.21) were not found to be associated with patient attitudes. Moreover, modeling the relationship between variables and attitudes showed that drug effectiveness and perceived distress from adverse drug reactions were the 2 most significant factors affecting patients’ attitude toward antidepressants. Conclusions: Patients’ self-report experiences of medications in online health care communities can provide a direct insight into the underlying factors associated with patients’ perceptions and attitudes toward antidepressants. However, it cannot be used as a replacement for self-report methods because of the lack of information for some of the variables, colloquial language, and the unstructured format of the reports. %M 30287417 %R 10.2196/10726 %U http://mental.jmir.org/2018/4/e10726/ %U https://doi.org/10.2196/10726 %U http://www.ncbi.nlm.nih.gov/pubmed/30287417 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 8 %P e254 %T Developing Embedded Taxonomy and Mining Patients’ Interests From Web-Based Physician Reviews: Mixed-Methods Approach %A Li,Jia %A Liu,Minghui %A Li,Xiaojun %A Liu,Xuan %A Liu,Jingfang %+ School of Management, Shanghai University, 99 Shangda Road, Shanghai, 200444, China, 86 21 66133790 ext 803, jingfangliu2014@hotmail.com %K labeled-LDA %K physicians %K topic modeling %K topic taxonomy %K Web-based review %D 2018 %7 16.08.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Web-based physician reviews are invaluable gold mines that merit further investigation. Although many studies have explored the text information of physician reviews, very few have focused on developing a systematic topic taxonomy embedded in physician reviews. The first step toward mining physician reviews is to determine how the natural structure or dimensions is embedded in reviews. Therefore, it is relevant to develop the topic taxonomy rigorously and systematically. Objective: This study aims to develop a hierarchical topic taxonomy to uncover the latent structure of physician reviews and illustrate its application for mining patients’ interests based on the proposed taxonomy and algorithm. Methods: Data comprised 122,716 physician reviews, including reviews of 8501 doctors from a leading physician review website in China (haodf.com), collected between 2007 and 2015. Mixed methods, including a literature review, data-driven-based topic discovery, and human annotation were used to develop the physician review topic taxonomy. Results: The identified taxonomy included 3 domains or high-level categories and 9 subtopics or low-level categories. The physician-related domain included the categories of medical ethics, medical competence, communication skills, medical advice, and prescriptions. The patient-related domain included the categories of the patient profile, symptoms, diagnosis, and pathogenesis. The system-related domain included the categories of financing and operation process. The F-measure of the proposed classification algorithm reached 0.816 on average. Symptoms (Cohen d=1.58, Δu=0.216, t=229.75, and P<.001) are more often mentioned by patients with acute diseases, whereas communication skills (Cohen d=−0.29, Δu=−0.038, t=−42.01, and P<.001), financing (Cohen d=−0.68, Δu=−0.098, t=−99.26, and P<.001), and diagnosis and pathogenesis (Cohen d=−0.55, Δu=−0.078, t=−80.09, and P<.001) are more often mentioned by patients with chronic diseases. Patients with mild diseases were more interested in medical ethics (Cohen d=0.25, Δu 0.039, t=8.33, and P<.001), operation process (Cohen d=0.57, Δu 0.060, t=18.75, and P<.001), patient profile (Cohen d=1.19, Δu 0.132, t=39.33, and P<.001), and symptoms (Cohen d=1.91, Δu=0.274, t=62.82, and P<.001). Meanwhile, patients with serious diseases were more interested in medical competence (Cohen d=−0.99, Δu=−0.165, t=−32.58, and P<.001), medical advice and prescription (Cohen d=−0.65, Δu=−0.082, t=−21.45, and P<.001), financing (Cohen d=−0.26, Δu=−0.018, t=−8.45, and P<.001), and diagnosis and pathogenesis (Cohen d=−1.55, Δu=−0.229, t=−50.93, and P<.001). Conclusions: This mixed-methods approach, integrating literature reviews, data-driven topic discovery, and human annotation, is an effective and rigorous way to develop a physician review topic taxonomy. The proposed algorithm based on Labeled-Latent Dirichlet Allocation can achieve impressive classification results for mining patients’ interests. Furthermore, the mining results reveal marked differences in patients’ interests across different disease types, socioeconomic development levels, and hospital levels. %M 30115610 %R 10.2196/jmir.8868 %U http://www.jmir.org/2018/8/e254/ %U https://doi.org/10.2196/jmir.8868 %U http://www.ncbi.nlm.nih.gov/pubmed/30115610 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 7 %P e243 %T Public Awareness, Usage, and Predictors for the Use of Doctor Rating Websites: Cross-Sectional Study in England %A Patel,Salma %A Cain,Rebecca %A Neailey,Kevin %A Hooberman,Lucy %+ School of Health and Society, University of Salford, The Crescent, Salford, Manchester, M5 4WT, United Kingdom, 44 (0)161 295 2394, s.patel48@salford.ac.uk %K online reviews %K Physician quality %K primary care %K Internet %K quality patient empowerment %K quality transparency %K public reporting %D 2018 %7 25.07.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: With the advent and popularity of social media and consumer rating websites, as well as the emergence of the digitally engaged patient, there has been an increased interest in doctor rating websites or online patient feedback websites, both inside and outside academia. However, there is very little known about how the public across England views such rating websites as a mode to give patient experience feedback. Objective: The aim of the overall study was to measure and understand public awareness, usage, and attitudes towards doctor rating websites as a mode to give experiential feedback about GPs in general practice in England. This paper reports on the findings of one of the aims of the study, which was to measure public awareness, current usage and future consideration of usage of online patient feedback websites, within the context of other feedback methods, This could allow the value of online patient feedback websites to be determined from the patients’ perspective. Methods: A mixed methods population questionnaire was designed, validated and implemented face-to-face using a cross-sectional design with a representative sample of the public (n=844) in England. The results of the questionnaire were analyzed using chi-square tests, binomial logistic regressions, and content analysis. The qualitative results will be reported elsewhere. Results: Public awareness of online patient feedback websites as a channel to leave experiential feedback about GPs was found to be low at 15.2% (128/844). However, usage and future consideration to use online patient feedback websites were found to be extremely low, with current patient usage at just 0.4% (3/844), and patient intention to use online patient feedback in the future at 17.8% (150/844). Furthermore, only 4.0-5.0% of those who would consider leaving feedback about a GP in the future selected doctor rating websites as their most preferred method; more than half of patients said they would consider leaving feedback about GPs using another method, but not using an online patient feedback website. Conclusions: The findings suggest that online patient feedback websites may not be an effective channel for collecting feedback on patient experience in general practice. Feedback on online patient feedback websites is not likely to be representative of the patient experience in the near future, challenging the use of online patient feedback not just as a mode for collecting patient experience data, but for patient choice and monitoring too. We recommend the National Health Service channels its investment and resources towards providing more direct and private feedback methods in general practice (such as opportunities for face-to-face feedback, email-based feedback, and web-based private feedback forms), as these are currently much more likely to be used by the majority of patients in England. %M 30045831 %R 10.2196/jmir.9523 %U http://www.jmir.org/2018/7/e243/ %U https://doi.org/10.2196/jmir.9523 %U http://www.ncbi.nlm.nih.gov/pubmed/30045831 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 7 %P e240 %T Evaluating Doctor Performance: Ordinal Regression-Based Approach %A Shi,Yong %A Li,Peijia %A Yu,Xiaodan %A Wang,Huadong %A Niu,Lingfeng %+ Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, 80 Zhongguancun East Road, Haidian District, Beijing, 100190, China, 86 15600616246, niulf@ucas.ac.cn %K performance evaluation %K ordinal regression %K mHealth %K support vector machines %K ordinal partitioning %D 2018 %7 18.07.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Doctor’s performance evaluation is an important task in mobile health (mHealth), which aims to evaluate the overall quality of online diagnosis and patient outcomes so that customer satisfaction and loyalty can be attained. However, most patients tend not to rate doctors’ performance, therefore, it is imperative to develop a model to make doctor’s performance evaluation automatic. When evaluating doctors’ performance, we rate it into a score label that is as close as possible to the true one. Objective: This study aims to perform automatic doctor’s performance evaluation from online textual consultations between doctors and patients by way of a novel machine learning method. Methods: We propose a solution that models doctor’s performance evaluation as an ordinal regression problem. In doing so, a support vector machine combined with an ordinal partitioning model (SVMOP), along with an innovative predictive function will be developed to capture the hidden preferences of the ordering labels over doctor’s performance evaluation. When engineering the basic text features, eight customized features (extracted from over 70,000 medical entries) were added and further boosted by the Gradient Boosting Decision Tree algorithm. Results: Real data sets from one of the largest mobile doctor/patient communication platforms in China are used in our study. Statistically, 64% of data on mHealth platforms lack the evaluation labels from patients. Experimental results reveal that our approach can support an automatic doctor performance evaluation. Compared with other auto-evaluation models, SVMOP improves mean absolute error (MAE) by 0.1, mean square error (MSE) by 0.5, pairwise accuracy (PAcc) by 5%; the suggested customized features improve MAE by 0.1, MSE by 0.2, PAcc by 3%. After boosting, performance is further improved. Based on SVMOP, predictive features like politeness and sentiment words can be mined, which can be further applied to guide the development of mHealth platforms. Conclusions: The initial modelling of doctor performance evaluation is an ordinal regression problem. Experiments show that the performance of our proposed model with revised prediction function is better than many other machine learning methods on MAE, MSE, as well as PAcc. With this model, the mHealth platform could not only make an online auto-evaluation of physician performance, but also obtain the most effective features, thereby guiding physician performance and the development of mHealth platforms. %M 30021708 %R 10.2196/jmir.9300 %U http://www.jmir.org/2018/7/e240/ %U https://doi.org/10.2196/jmir.9300 %U http://www.ncbi.nlm.nih.gov/pubmed/30021708 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 6 %P e212 %T Content, Quality, and Assessment Tools of Physician-Rating Websites in 12 Countries: Quantitative Analysis %A Rothenfluh,Fabia %A Schulz,Peter J %+ Institute of Communication and Health, Università della Svizzera italiana, Via G. Buffi 13, Lugano, 6900, Switzerland, 41 058 666 4485, fabia.rothenfluh@usi.ch %K physician rating websites %K content analysis %K website quality %K patient Web portals %K rating tools %K health information %K health care quality assessment %K patient reviews %D 2018 %7 14.06.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Websites on which users can rate their physician are becoming increasingly popular, but little is known about the website quality, the information content, and the tools they offer users to assess physicians. This study assesses these aspects on physician-rating websites in German- and English-speaking countries. Objective: The objective of this study was to collect information on websites with a physician rating or review tool in 12 countries in terms of metadata, website quality (transparency, privacy and freedom of speech of physicians and patients, check mechanisms for appropriateness and accuracy of reviews, and ease of page navigation), professional information about the physician, rating scales and tools, as well as traffic rank. Methods: A systematic Web search based on a set of predefined keywords was conducted on Google, Bing, and Yahoo in August 2016. A final sample of 143 physician-rating websites was analyzed and coded for metadata, quality, information content, and the physician-rating tools. Results: The majority of websites were registered in the United States (40/143) or Germany (25/143). The vast majority were commercially owned (120/143, 83.9%), and 69.9% (100/143) displayed some form of physician advertisement. Overall, information content (mean 9.95/25) as well as quality were low (mean 18.67/47). Websites registered in the United Kingdom obtained the highest quality scores (mean 26.50/47), followed by Australian websites (mean 21.50/47). In terms of rating tools, physician-rating websites were most frequently asking users to score overall performance, punctuality, or wait time in practice. Conclusions: This study evidences that websites that provide physician rating should improve and communicate their quality standards, especially in terms of physician and user protection, as well as transparency. In addition, given that quality standards on physician-rating websites are low overall, the development of transparent guidelines is required. Furthermore, attention should be paid to the financial goals that the majority of physician-rating websites, especially the ones that are commercially owned, pursue. %M 29903704 %R 10.2196/jmir.9105 %U http://www.jmir.org/2018/6/e212/ %U https://doi.org/10.2196/jmir.9105 %U http://www.ncbi.nlm.nih.gov/pubmed/29903704 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 5 %P e176 %T Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers %A Daskivich,Timothy %A Luu,Michael %A Noah,Benjamin %A Fuller,Garth %A Anger,Jennifer %A Spiegel,Brennan %+ Division of Urology, Cedars-Sinai Medical Center, 8635 West 3rd Street, Suite 1070W, Los Angeles, CA, 90048, United States, 1 310 423 4700, timothy.daskivich@csmc.edu %K online ratings %K consumer ratings %K patient satisfaction %K digital health %K telemedicine %D 2018 %7 09.05.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Health care consumers are increasingly using online ratings to select providers, but differences in the distribution of scores across specialties and skew of the data have the potential to mislead consumers about the interpretation of ratings. Objective: The objective of our study was to determine whether distributions of consumer ratings differ across specialties and to provide specialty-specific data to assist consumers and clinicians in interpreting ratings. Methods: We sampled 212,933 health care providers rated on the Healthgrades consumer ratings website, representing 29 medical specialties (n=128,678), 15 surgical specialties (n=72,531), and 6 allied health (nonmedical, nonnursing) professions (n=11,724) in the United States. We created boxplots depicting distributions and tested the normality of overall patient satisfaction scores. We then determined the specialty-specific percentile rank for scores across groupings of specialties and individual specialties. Results: Allied health providers had higher median overall satisfaction scores (4.5, interquartile range [IQR] 4.0-5.0) than physicians in medical specialties (4.0, IQR 3.3-4.5) and surgical specialties (4.2, IQR 3.6-4.6, P<.001). Overall satisfaction scores were highly left skewed (normal between –0.5 and 0.5) for all specialties, but skewness was greatest among allied health providers (–1.23, 95% CI –1.280 to –1.181), followed by surgical (–0.77, 95% CI –0.787 to –0.755) and medical specialties (–0.64, 95% CI –0.648 to –0.628). As a result of the skewness, the percentages of overall satisfaction scores less than 4 were only 23% for allied health, 37% for surgical specialties, and 50% for medical specialties. Percentile ranks for overall satisfaction scores varied across specialties; percentile ranks for scores of 2 (0.7%, 2.9%, 0.8%), 3 (5.8%, 16.6%, 8.1%), 4 (23.0%, 50.3%, 37.3%), and 5 (63.9%, 89.5%, 86.8%) differed for allied health, medical specialties, and surgical specialties, respectively. Conclusions: Online consumer ratings of health care providers are highly left skewed, fall within narrow ranges, and differ by specialty, which precludes meaningful interpretation by health care consumers. Specialty-specific percentile ranks may help consumers to more meaningfully assess online physician ratings. %M 29743150 %R 10.2196/jmir.9160 %U http://www.jmir.org/2018/5/e176/ %U https://doi.org/10.2196/jmir.9160 %U http://www.ncbi.nlm.nih.gov/pubmed/29743150 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 7 %N 1 %P e8 %T The Validity of Online Patient Ratings of Physicians: Analysis of Physician Peer Reviews and Patient Ratings %A McGrath,Robert J %A Priestley,Jennifer Lewis %A Zhou,Yiyun %A Culligan,Patrick J %+ Graduate College, Kennesaw State University, 1000 Chastain Road, Kennesaw, Kennesaw, GA,, United States, 1 4043331288, yzhou20@kennesaw.edu %K physician review websites %K online patient ratings %K physician peer review %D 2018 %7 09.04.2018 %9 Short Paper %J Interact J Med Res %G English %X Background: Information from ratings sites are increasingly informing patient decisions related to health care and the selection of physicians. Objective: The current study sought to determine the validity of online patient ratings of physicians through comparison with physician peer review. Methods: We extracted 223,715 reviews of 41,104 physicians from 10 of the largest cities in the United States, including 1142 physicians listed as “America’s Top Doctors” through physician peer review. Differences in mean online patient ratings were tested for physicians who were listed and those who were not. Results: Overall, no differences were found between the online patient ratings based upon physician peer review status. However, statistical differences were found for four specialties (family medicine, allergists, internal medicine, and pediatrics), with online patient ratings significantly higher for those physicians listed as a peer-reviewed “Top Doctor” versus those who were not. Conclusions: The results of this large-scale study indicate that while online patient ratings are consistent with physician peer review for four nonsurgical, primarily in-office specializations, patient ratings were not consistent with physician peer review for specializations like anesthesiology. This result indicates that the validity of patient ratings varies by medical specialization. %M 29631992 %R 10.2196/ijmr.9350 %U http://www.i-jmr.org/2018/1/e8/ %U https://doi.org/10.2196/ijmr.9350 %U http://www.ncbi.nlm.nih.gov/pubmed/29631992 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 3 %P e99 %T How Online Quality Ratings Influence Patients’ Choice of Medical Providers: Controlled Experimental Survey Study %A Yaraghi,Niam %A Wang,Weiguang %A Gao,Guodong (Gordon) %A Agarwal,Ritu %+ Center for Technology Innovation, The Brookings Institution, 1755 Massachusetts Ave NW, Washington, DC, 20036, United States, 1 2027632073, niam.yaraghi@uconn.edu %K quality of health care %K health care evaluation mechanisms %D 2018 %7 26.03.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: In recent years, the information environment for patients to learn about physician quality is being rapidly changed by Web-based ratings from both commercial and government efforts. However, little is known about how various types of Web-based ratings affect individuals’ choice of physicians. Objective: The objective of this research was to measure the relative importance of Web-based quality ratings from governmental and commercial agencies on individuals’ choice of primary care physicians. Methods: In a choice-based conjoint experiment conducted on a sample of 1000 Amazon Mechanical Turk users in October 2016, individuals were asked to choose their preferred primary care physician from pairs of physicians with different ratings in clinical and nonclinical aspects of care provided by governmental and commercial agencies. Results: The relative log odds of choosing a physician increases by 1.31 (95% CI 1.26-1.37; P<.001) and 1.32 (95% CI 1.27-1.39; P<.001) units when the government clinical ratings and commercial nonclinical ratings move from 2 to 4 stars, respectively. The relative log odds of choosing a physician increases by 1.12 (95% CI 1.07-1.18; P<.001) units when the commercial clinical ratings move from 2 to 4 stars. The relative log odds of selecting a physician with 4 stars in nonclinical ratings provided by the government is 1.03 (95% CI 0.98-1.09; P<.001) units higher than a physician with 2 stars in this rating. The log odds of selecting a physician with 4 stars in nonclinical government ratings relative to a physician with 2 stars is 0.23 (95% CI 0.13-0.33; P<.001) units higher for females compared with males. Similar star increase in nonclinical commercial ratings increases the relative log odds of selecting the physician by female respondents by 0.15 (95% CI 0.04-0.26; P=.006) units. Conclusions: Individuals perceive nonclinical ratings provided by commercial websites as important as clinical ratings provided by government websites when choosing a primary care physician. There are significant gender differences in how the ratings are used. More research is needed on whether patients are making the best use of different types of ratings, as well as the optimal allocation of resources in improving physician ratings from the government’s perspective. %M 29581091 %R 10.2196/jmir.8986 %U http://www.jmir.org/2018/3/e99/ %U https://doi.org/10.2196/jmir.8986 %U http://www.ncbi.nlm.nih.gov/pubmed/29581091 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 3 %P e76 %T Scope, Breadth, and Differences in Online Physician Ratings Related to Geography, Specialty, and Year: Observational Retrospective Study %A Liu,Jessica Janine %A Matelski,John Justin %A Bell,Chaim M %+ Department of Medicine, University of Toronto, University Health Network, Toronto General Hospital, 14EN213, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada, 1 416 340 3111 ext 4908, jessica.liu@uhn.ca %K quality improvement %K patient satisfaction %K patient-centered care %K online ratings %D 2018 %7 07.03.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician ratings websites have emerged as a novel forum for consumers to comment on their health care experiences. Little is known about such ratings in Canada. Objective: We investigated the scope and trends for specialty, geographic region, and time for online physician ratings in Canada using a national data source from the country’s leading physician-rating website. Methods: This observational retrospective study used online ratings data from Canadian physicians (January 2005-September 2013; N=640,603). For specialty, province, and year of rating, we assessed whether physicians were likely to be rated favorably by using the proportion of ratings greater than the overall median rating. Results: In total, 57,412 unique physicians had 640,603 individual ratings. Overall, ratings were positive (mean 3.9, SD 1.3). On average, each physician had 11.2 (SD 10.1) ratings. By comparing specialties with Canadian Institute of Health Information physician population numbers over our study period, we inferred that certain specialties (obstetrics and gynecology, family practice, surgery, and dermatology) were more commonly rated, whereas others (pathology, radiology, genetics, and anesthesia) were less represented. Ratings varied by specialty; cardiac surgery, nephrology, genetics, and radiology were more likely to be rated in the top 50th percentile, whereas addiction medicine, dermatology, neurology, and psychiatry were more often rated in the lower 50th percentile of ratings. Regarding geographic practice location, ratings were more likely to be favorable for physicians practicing in eastern provinces compared with western and central Canada. Regarding year, the absolute number of ratings peaked in 2007 before stabilizing and decreasing by 2013. Moreover, ratings were most likely to be positive in 2007 and again in 2013. Conclusions: Physician-rating websites are a relatively novel source of provider-level patient satisfaction and are a valuable source of the patient experience. It is important to understand the breadth and scope of such ratings, particularly regarding specialty, geographic practice location, and changes over time. %M 29514775 %R 10.2196/jmir.7475 %U http://www.jmir.org/2018/3/e76/ %U https://doi.org/10.2196/jmir.7475 %U http://www.ncbi.nlm.nih.gov/pubmed/29514775 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 1 %P e35 %T Unhappy Patients Are Not Alike: Content Analysis of the Negative Comments from China's Good Doctor Website %A Zhang,Wei %A Deng,Zhaohua %A Hong,Ziying %A Evans,Richard %A Ma,Jingdong %A Zhang,Hui %+ Institute of Smart Health, School of Medicine and Health Management, Huazhong University of Science and Technology, No. 13 Hangkong Road, Qiaokou District, Wuhan, 430030, China, 86 15926318828, zh-deng@hust.edu.cn %K patient satisfaction %K physician-patient relationship %K Good Doctors website %K patient complaint. %D 2018 %7 25.01.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: With the rise in popularity of Web 2.0 technologies, the sharing of patient experiences about physicians on online forums and medical websites has become a common practice. However, negative comments posted by patients are considered to be more influential by other patients and physicians than those that are satisfactory. Objective: The aim of this study was to analyze negative comments posted online about physicians and to identify possible solutions to improve patient satisfaction, as well as their relationship with physicians. Methods: A Java-based program was developed to collect patient comments on the Good Doctor website, one of the most popular online health communities in China. A total of 3012 negative comments concerning 1029 physicians (mean 2.93 [SD 4.14]) from 5 highly ranked hospitals in Beijing were extracted for content analysis. An initial coding framework was constructed with 2 research assistants involved in the codification. Results: Analysis, based on the collected 3012 negative comments, revealed that unhappy patients are not alike and that their complaints cover a wide range of issues experienced throughout the whole process of medical consultation. Among them, physicians in Obstetrics and Gynecology (606/3012, 20.12%; P=.001) and Internal Medicine (487/3012, 16.17%; P=.80) received the most negative comments. For negative comments per physician, Dermatology and Sexually Transmitted Diseases (mean 5.72, P<.001) and Andrology (mean 5, P=.02) ranked the highest. Complaints relating to insufficient medical consultation duration (577/3012, 19.16%), physician impatience (527/3012, 17.50%), and perceived poor therapeutic effect (370/3012, 12.28%) received the highest number of negative comments. Specific groups of people, such as those accompanying older patients or children, traveling patients, or very important person registrants, were shown to demonstrate little tolerance for poor medical service. Conclusions: Analysis of online patient complaints provides an innovative approach to understand factors associated with patient dissatisfaction. The outcomes of this study could be of benefit to hospitals or physicians seeking to improve their delivery of patient-centered services. Patients are expected to be more understanding of overloaded physicians’ workloads, which are impacted by China’s stretched medical resources, as efforts are made to build more harmonious physician-patient relationships. %M 29371176 %R 10.2196/jmir.8223 %U http://www.jmir.org/2018/1/e35/ %U https://doi.org/10.2196/jmir.8223 %U http://www.ncbi.nlm.nih.gov/pubmed/29371176 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 1 %P e26 %T A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews %A Chen,Jinying %A Druhl,Emily %A Polepalli Ramesh,Balaji %A Houston,Thomas K %A Brandt,Cynthia A %A Zulman,Donna M %A Vimalananda,Varsha G %A Malkani,Samir %A Yu,Hong %+ Department of Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, United States, 1 774 455 3527, jinying.chen@umassmed.edu %K electronic health records %K natural language processing %K consumer health informatics %K usability testing %K computer software %D 2018 %7 22.01.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Many health care systems now allow patients to access their electronic health record (EHR) notes online through patient portals. Medical jargon in EHR notes can confuse patients, which may interfere with potential benefits of patient access to EHR notes. Objective: The aim of this study was to develop and evaluate the usability and content quality of NoteAid, a Web-based natural language processing system that links medical terms in EHR notes to lay definitions, that is, definitions easily understood by lay people. Methods: NoteAid incorporates two core components: CoDeMed, a lexical resource of lay definitions for medical terms, and MedLink, a computational unit that links medical terms to lay definitions. We developed innovative computational methods, including an adapted distant supervision algorithm to prioritize medical terms important for EHR comprehension to facilitate the effort of building CoDeMed. Ten physician domain experts evaluated the user interface and content quality of NoteAid. The evaluation protocol included a cognitive walkthrough session and a postsession questionnaire. Physician feedback sessions were audio-recorded. We used standard content analysis methods to analyze qualitative data from these sessions. Results: Physician feedback was mixed. Positive feedback on NoteAid included (1) Easy to use, (2) Good visual display, (3) Satisfactory system speed, and (4) Adequate lay definitions. Opportunities for improvement arising from evaluation sessions and feedback included (1) improving the display of definitions for partially matched terms, (2) including more medical terms in CoDeMed, (3) improving the handling of terms whose definitions vary depending on different contexts, and (4) standardizing the scope of definitions for medicines. On the basis of these results, we have improved NoteAid’s user interface and a number of definitions, and added 4502 more definitions in CoDeMed. Conclusions: Physician evaluation yielded useful feedback for content validation and refinement of this innovative tool that has the potential to improve patient EHR comprehension and experience using patient portals. Future ongoing work will develop algorithms to handle ambiguous medical terms and test and evaluate NoteAid with patients. %M 29358159 %R 10.2196/jmir.8669 %U http://www.jmir.org/2018/1/e26/ %U https://doi.org/10.2196/jmir.8669 %U http://www.ncbi.nlm.nih.gov/pubmed/29358159 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 11 %P e387 %T Public Awareness and Use of German Physician Ratings Websites: Cross-Sectional Survey of Four North German Cities %A McLennan,Stuart %A Strech,Daniel %A Meyer,Andrea %A Kahrass,Hannes %+ Institute for Biomedical Ethics, Universität Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071786, s.mclennan@unibas.ch %K physician rating websites %K patient satisfaction %D 2017 %7 09.11.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRWs) allow patients to rate, comment, and discuss physicians’ quality. The ability of PRWs to influence patient decision making and health care quality is dependent, in part, on sufficient awareness and usage of PRWs. However, previous studies have found relatively low levels of awareness and usage of PRWs, which has raised concerns about the representativeness and validity of information on PRWs. Objective: The objectives of this study were to examine (1) participants’ awareness, use, and contribution of ratings on PRWs and how this compares with other rating websites; (2) factors that predict awareness, use, and contribution of ratings on PRWs; and (3) participants’ attitudes toward PRWs in relation to selecting a physician. Methods: A mailed cross-sectional survey was sent to a random sample (N=1542) from four North German cities (Nordhorn, Hildesheim, Bremen, and Hamburg) between April and July 2016. Survey questions explored respondents’ awareness, use, and contribution of ratings on rating websites for service (physicians, hospitals, and hotels and restaurants) and products (media and technical) in general and the role of PRWs when searching for a new physician. Results: A total of 280 completed surveys were returned (280/1542, 18.16% response rate), with the following findings: (1) Overall, 72.5% (200/276) of respondents were aware of PRWs. Of the respondents who were aware of PRWs, 43.6% (86/197) had used PRWs. Of the respondents who had used PRWs, 23% (19/83) had rated physicians at least once. Awareness, use, and contribution of ratings on PRWs were significantly lower in comparison with all other rating websites, except for hospital rating websites. (2) Except for the impact of responders’ gender and marital status on the awareness of PRWs and responders’ age on the use of PRWs, no other predictors had a relevant impact. (3) Whereas 31.8% (85/267) of the respondents reported that PRWs were a very important or somewhat important information source when searching for a new physician, respondents significantly more often reported that family, friends and colleagues (259/277, 93.5%), other physicians (219/274, 79.9%), and practice websites (108/266, 40.6%) were important information sources. Conclusions: Whereas awareness of German PRWs appears to have substantially increased, the use of PRWs and contribution of ratings remains relatively low. Further research is needed to examine the reasons why only a few patients are rating physicians. However, given the information inequality between provider and consumer will always be higher for consumers using the services of physicians, it is possible that people will always rely more on interpersonal recommendations than impersonal public information before selecting a physician. %M 29122739 %R 10.2196/jmir.7581 %U http://www.jmir.org/2017/11/e387/ %U https://doi.org/10.2196/jmir.7581 %U http://www.ncbi.nlm.nih.gov/pubmed/29122739 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 8 %P e299 %T Developments in the Frequency of Ratings and Evaluation Tendencies: A Review of German Physician Rating Websites %A McLennan,Stuart %A Strech,Daniel %A Reimann,Swantje %+ Institute for History, Ethics and Philosophy of Medicine, Hannover Medical School, OE 5450, Carl-Neuberg-Str. 1, Hannover, 30625, Germany, 49 5115326498, strech.daniel@mh-hannover.de %K physician rating websites %K patient satisfaction %D 2017 %7 25.08.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRWs) have been developed to allow all patients to rate, comment, and discuss physicians’ quality online as a source of information for others searching for a physician. At the beginning of 2010, a sample of 298 randomly selected physicians from the physician associations in Hamburg and Thuringia were searched for on 6 German PRWs to examine the frequency of ratings and evaluation tendencies. Objective: The objective of this study was to examine (1) the number of identifiable physicians on German PRWs; (2) the number of rated physicians on German PRWs; (3) the average and maximum number of ratings per physician on German PRWs; (4) the average rating on German PRWs; (5) the website visitor ranking positions of German PRWs; and (6) how these data compare with 2010 results. Methods: A random stratified sample of 298 selected physicians from the physician associations in Hamburg and Thuringia was generated. Every selected physician was searched for on the 6 PRWs (Jameda, Imedo, Docinsider, Esando, Topmedic, and Medführer) used in the 2010 study and a PRW, Arztnavigator, launched by Allgemeine Ortskrankenkasse (AOK). Results: The results were as follows: (1) Between 65.1% (194/298) on Imedo to 94.6% (282/298) on AOK-Arztnavigator of the physicians were identified on the selected PRWs. (2) Between 16.4% (49/298) on Esando to 83.2% (248/298) on Jameda of the sample had been rated at least once. (3) The average number of ratings per physician ranged from 1.2 (Esando) to 7.5 (AOK-Arztnavigator). The maximum number of ratings per physician ranged from 3 (Esando) to 115 (Docinsider), indicating an increase compared with the ratings of 2 to 27 in the 2010 study sample. (4) The average converted standardized rating (1=positive, 2=neutral, and 3=negative) ranged from 1.0 (Medführer) to 1.2 (Jameda and Topmedic). (5) Only Jameda (position 317) and Medführer (position 9796) were placed among the top 10,000 visited websites in Germany. Conclusions: Whereas there has been an overall increase in the number of ratings when summing up ratings from all 7 analyzed German PRWs, this represents an average addition of only 4 new ratings per physician in a year. The increase has also not been even across the PRWs, and it would be advisable for the users of PRWs to utilize a number of PRWs to ascertain the rating of any given physician. Further research is needed to identify barriers for patients to rate their physicians and to assist efforts to increase the number of ratings on PRWs to consequently improve the fairness and practical importance of PRWs. %M 28842391 %R 10.2196/jmir.6599 %U http://www.jmir.org/2017/8/e299/ %U https://doi.org/10.2196/jmir.6599 %U http://www.ncbi.nlm.nih.gov/pubmed/28842391 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 8 %P e254 %T Web-Based Physician Ratings for California Physicians on Probation %A Murphy,Gregory P %A Awad,Mohannad A %A Osterberg,E Charles %A Gaither,Thomas W %A Chumnarnsongkhroh,Thanabhudee %A Washington,Samuel L %A Breyer,Benjamin N %+ Zuckerberg San Francisco General Hospital, Department of Urology, University of California, San Francisco, Suite 3A, 1001 Potrero Ave, San Francisco, CA, 94110, United States, 1 4152068805, benjamin.breyer@ucsf.edu %K online physician ratings %K probation %K Internet %K quality of care %D 2017 %7 22.08.2017 %9 Original Paper %J J Med Internet Res %G English %X Background:  Web-based physician ratings systems are a popular tool to help patients evaluate physicians. Websites help patients find information regarding physician licensure, office hours, and disciplinary records along with ratings and reviews. Whether higher patient ratings are associated with higher quality of care is unclear. Objective:  The aim of this study was to characterize the impact of physician probation on consumer ratings by comparing website ratings between doctors on probation against matched controls. Methods:  A retrospective review of data from the Medical Board of California for physicians placed on probation from December 1989 to September 2015 was performed. Violations were categorized into nine types. Nonprobation controls were matched by zip code and specialty with probation cases in a 2:1 ratio using the California Department of Consumer Affairs website. Web-based reviews were recorded from vitals.com, healthgrades.com, and ratemds.com (ratings range from 1-5). Results:  A total of 410 physicians were placed on probation for 866 violations. The mean (standard deviation [SD]) number of ratings per doctor was 5.2 (7.8) for cases and 4 (6.3) for controls (P=.003). The mean rating for physicians on probation was 3.7 (1.6) compared with 4.0 (1.0) for controls when all three rating websites were pooled (P<.001). Violations for medical documentation, incompetence, prescription negligence, and fraud were found to have statistically significant lower rating scores. Conversely, scores for professionalism, drugs or alcohol, crime, sexual misconduct, and personal illness were similar between cases and controls. In a univariate analysis, probation was found to be associated with lower rating, odds ratio=1.5 (95% CI 1.0-2.2). This association was not significant in a multivariate model when we included age and gender. Conclusions:  Web-based physician ratings were lower for doctors on probation indicating that patients may perceive a difference. Despite these statistical findings, the absolute difference was quite small. Physician rating websites have utility but are imperfect proxies for competence. Further research on physician Web-based ratings is warranted to understand what they measure and how they are associated with quality. %M 28830852 %R 10.2196/jmir.7488 %U http://www.jmir.org/2017/8/e254/ %U https://doi.org/10.2196/jmir.7488 %U http://www.ncbi.nlm.nih.gov/pubmed/28830852 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 7 %P e275 %T Do Physicians Respond to Web-Based Patient Ratings? An Analysis of Physicians’ Responses to More Than One Million Web-Based Ratings Over a Six-Year Period %A Emmert,Martin %A Sauter,Lisa %A Jablonski,Lisa %A Sander,Uwe %A Taheri-Zadeh,Fatemeh %+ Institute of Management, School of Business and Economics, Health Services Management, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 90403, Germany, 49 9115302 ext 253, Martin.Emmert@fau.de %K Internet %K online ratings %K doctor-patient communication %K public reporting %K transparency %D 2017 %7 26.07.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician-rating websites (PRWs) may lead to quality improvements in case they enable and establish a peer-to-peer communication between patients and physicians. Yet, we know little about whether and how physicians respond on the Web to patient ratings. Objective: The objective of this study was to describe trends in physicians’ Web-based responses to patient ratings over time, to identify what physician characteristics influence Web-based responses, and to examine the topics physicians are likely to respond to. Methods: We analyzed physician responses to more than 1 million patient ratings displayed on the German PRW, jameda, from 2010 to 2015. Quantitative analysis contained chi-square analyses and the Mann-Whitney U test. Quantitative content techniques were applied to determine the topics physicians respond to based on a randomly selected sample of 600 Web-based ratings and corresponding physician responses. Results: Overall, physicians responded to 1.58% (16,640/1,052,347) of all Web-based ratings, with an increasing trend over time from 0.70% (157/22,355) in 2010 to 1.88% (6377/339,919) in 2015. Web-based ratings that were responded to had significantly worse rating results than ratings that were not responded to (2.15 vs 1.74, P<.001). Physicians who respond on the Web to patient ratings differ significantly from nonresponders regarding several characteristics such as gender and patient recommendation results (P<.001 each). Regarding scaled-survey rating elements, physicians were most likely to respond to the waiting time within the practice (19.4%, 99/509) and the time spent with the patient (18.3%, 110/600). Almost one-third of topics in narrative comments were answered by the physicians (30.66%, 382/1246). Conclusions: So far, only a minority of physicians have taken the chance to respond on the Web to patient ratings. This is likely because of (1) the low awareness of PRWs among physicians, (2) the fact that only a few PRWs enable physicians to respond on the Web to patient ratings, and (3) the lack of an active moderator to establish peer-to-peer communication. PRW providers should foster more frequent communication between the patient and the physician and encourage physicians to respond on the Web to patient ratings. Further research is needed to learn more about the motivation of physicians to respond or not respond to Web-based patient ratings. %M 28747292 %R 10.2196/jmir.7538 %U http://www.jmir.org/2017/7/e275/ %U https://doi.org/10.2196/jmir.7538 %U http://www.ncbi.nlm.nih.gov/pubmed/28747292 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 3 %N 3 %P e43 %T Online Reviews as Health Data: Examining the Association Between Availability of Health Care Services and Patient Star Ratings Exemplified by the Yelp Academic Dataset %A Tran,Nam N %A Lee,Joon %+ Health Data Science Lab, School of Public Health and Health Systems, University of Waterloo, 200 University Ave W, Waterloo, ON,, Canada, 1 519 888 4567 ext 31567, joon.lee@uwaterloo.ca %K Yelp %K health care access %K health care availability %K patient satisfaction %K patient rating %K patient experience %K open hour %K clinic hour %K online reviews %D 2017 %7 12.07.2017 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: There have been public health interventions that aim to reduce barriers to health care access by extending opening hours of health care facilities. However, the impact of opening hours from the patient’s perspective is not well understood. Objective: This study aims to investigate the relationship between temporal accessibility of health care services and how patients rate the providers on Yelp, an online review website that is popular in the United States. Using crowdsourced open Internet data, such as Yelp, can help circumvent the traditional survey method. Methods: From Yelp’s limited academic dataset, this study examined the pattern of visits to health care providers and performed a secondary analysis to examine the association between patient rating (measured by Yelp’s rating) and temporal accessibility of health care services (measured by opening hours) using ordinal logistic regression models. Other covariates included were whether an appointment was required, the type of health care service, the region of the health care service provider, the number of reviews the health care service provider received in the past, the number of nearby competitors, the mean rating of competitors, and the standard deviation of competitors’ ratings. Results: From the 2085 health care service providers identified, opening hours during certain periods, the type of health care service, and the variability of competitors’ ratings showed an association with patient rating. Most of the visits to health care service providers took place between normal working hours (9 AM-5 PM) from Sunday to Thursday, and the least on Saturday. A model fitted to the entire sample showed that increasing hours during normal working hours on Monday (OR 0.926, 95% CI 0.880-0.973, P=0.03), Saturday (OR 0.897, 95% CI 0.860-0.935, P<0.001), Sunday (OR 0.904, 95% CI 0.841-0.970, P=0.005), and outside normal working hours on Friday (OR 0.872, 95% CI 0.760-0.998, P=0.048) was associated with receiving lower ratings. But increasing hours during outside normal working hours on Sunday was associated with receiving higher ratings (OR 1.400, 95% CI 1.036-1.924, P=0.03). There were also observed differences in patient ratings among the health care services types, but not geographically or by appointment requirement. Conclusions: This study shows that public health interventions, especially those involving opening hours, could use crowdsourced open Internet data to enhance the evidence base for decision making and evaluation in the future. This study illustrates one example of how Yelp data could be used to understand patient experiences with health care services, making a case for future research for exploring online reviews as a health dataset. %M 28701293 %R 10.2196/publichealth.7001 %U http://publichealth.jmir.org/2017/3/e43/ %U https://doi.org/10.2196/publichealth.7001 %U http://www.ncbi.nlm.nih.gov/pubmed/28701293 %0 Journal Article %I %V %N %P %T %D %7 .. %9 %J %G English %X %U %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 4 %P e105 %T The Reviews Are in: A Qualitative Content Analysis of Consumer Perspectives on Apps for Bipolar Disorder %A Nicholas,Jennifer %A Fogarty,Andrea S %A Boydell,Katherine %A Christensen,Helen %+ Black Dog Institute, University of New South Wales, Hospital rd, Prince of Wales Hospital, Sydney, 2031, Australia, 61 293828507, J.nicholas@blackdog.org.au %K mobile applications %K bipolar disorder %K smartphone %K telemedicine %K qualitative research %D 2017 %7 07.04.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: The delivery of mobile health (mHealth) services is acceptable to mental health consumers. However, despite the benefits of accessibility, cost-effectiveness, anonymity, and ability to tailor content to individual needs, consumer engagement remains a hurdle for uptake and continued use. This may be unsurprising as few studies have examined app content from the consumer perspective or assessed consumer preferences for the content of apps for mental health management. An opportunity to examine consumer perspectives exists in using naturally generated data that is publically available in the Google Play and Apple app stores. Whereas commercial developers routinely use this data, to date there has been no in-depth evaluation within scientific research. Objective: The aim of our study was to explore what consumers consider useful content for mental health management apps, identify unmet needs, and understand user expectations of mental health apps within the context of apps for bipolar disorder. Methods: Publically available English language consumer reviews of 48 apps for bipolar disorder were used as data, providing a total of 2173 reviews. Review text was coded and analyzed using a team approach to qualitative content analysis. Results were presented in 2 forms: (1) a quantitative summary of the 9 major and minor themes and (2) a qualitative synthesis of key thematic findings. Results: The majority of reviews were for symptom monitoring apps (87.94%, 1911/2173). The qualitative content analysis revealed 5 main themes: (1) laudatory talk, comments regarding the app’s benefits including helpfulness and successful design features (74.00% of reviews, 1608/2173); (2) unfavorable feedback, negative reviews largely concerning unmet needs, privacy and technical issues, and potential dangers of app use (25.54%, 555/2173); (3) conceptions of community, referring to both communities of users with mental ill-health accessed via the app and a community created among app users and developers (24.25%, 527/2173); (4) wishlist features, app features requested by users (17.53%, 381/2173); and (5) apps and therapy, app use within clinical care (10.58%, 230/2173). Four minor themes were also identified: (1) app cost, (2) privacy and data security, (3) comparisons with traditional monitoring, and (4) evidence-based mHealth. Conclusions: Although mostly positive, the proportion of reviews containing wishlist requests indicates consumer needs are not adequately addressed by currently available disorder management apps. Consumers value content that is helpful, supportive, and easy to use, and they are integrating apps into their health management and clinical care without necessarily considering the evidence-base or clinical effectiveness of the tool. User expectations regarding developer responsiveness to their needs has implications for community-based participatory research and integrated knowledge translation. However, this expectation is incompatible with current mHealth funding structures. %M 28389420 %R 10.2196/jmir.7273 %U http://www.jmir.org/2017/4/e105/ %U https://doi.org/10.2196/jmir.7273 %U http://www.ncbi.nlm.nih.gov/pubmed/28389420 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 3 %P e65 %T Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy %A Gibbons,Chris %A Richards,Suzanne %A Valderas,Jose Maria %A Campbell,John %+ The Psychometrics Centre, University of Cambridge, 16 Mill Lane, Cambridge, CB2 1RH, United Kingdom, 44 1223 765 203, cg598@cam.ac.uk %K machine learning %K surveys and questionnaires %K feedback %K data mining %K work performance %D 2017 %7 15.03.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective: The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods: We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results: Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P<.05). Scores did not vary between doctors who were rated as popular or innovative and those who were not rated at all (P>.05). Conclusions: Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high performance. Colleague open-text comments that signal respect, professionalism, and being interpersonal may be key indicators of doctor’s performance. %M 28298265 %R 10.2196/jmir.6533 %U http://www.jmir.org/2017/3/e65/ %U https://doi.org/10.2196/jmir.6533 %U http://www.ncbi.nlm.nih.gov/pubmed/28298265 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 12 %P e324 %T Association Between Physician Online Rating and Quality of Care %A Okike,Kanu %A Peter-Bibb,Taylor K %A Xie,Kristal C %A Okike,Okike N %+ Department of Orthopedic Surgery, Kaiser Permanente Moanalua Medical Center, 3288 Moanalua Road, Honolulu, HI, 96821, United States, 1 808 432 7326, okike@post.harvard.edu %K online reviews %K cardiac surgery %K physician quality %D 2016 %7 13.12.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients are increasingly using physician review websites to find “a good doctor.” However, to our knowledge, no prior study has examined the relationship between online rating and an accepted measure of quality. Objective: The purpose of this study was to assess the association between online physician rating and an accepted measure of quality: 30-day risk-adjusted mortality rate following coronary artery bypass graft (CABG) surgery. Methods: In the US states of California, Massachusetts, New Jersey, New York, and Pennsylvania—which together account for over one-quarter of the US population—risk-adjusted mortality rates are publicly reported for all cardiac surgeons. From these reports, we recorded the 30-day mortality rate following isolated CABG surgery for each surgeon practicing in these 5 states. For each surgeon listed in the state reports, we then conducted Internet-based searches to determine his or her online rating(s). We then assessed the relationship between physician online rating and risk-adjusted mortality rate. Results: Of the 614 surgeons listed in the state reports, we found 96.1% (590/614) to be rated online. The average online rating was 4.4 out of 5, and 78.7% (483/614) of the online ratings were 4 or higher. The median number of reviews used to formulate each rating was 4 (range 1-89), and 32.70% (503/1538) of the ratings were based on 2 or fewer reviews. Overall, there was no correlation between surgeon online rating and risk-adjusted mortality rate (P=.13). Risk-adjusted mortality rates were similar for surgeons across categories of average online rating (P>.05), and surgeon average online rating was similar across quartiles of surgeon risk-adjusted mortality rate (P>.05). Conclusions: In this study of cardiac surgeons practicing in the 5 US states that publicly report outcomes, we found no correlation between online rating and risk-adjusted mortality rates. Patients using online rating websites to guide their choice of physician should recognize that these ratings may not reflect actual quality of care as defined by accepted metrics. %M 27965191 %R 10.2196/jmir.6612 %U http://www.jmir.org/2016/12/e324/ %U https://doi.org/10.2196/jmir.6612 %U http://www.ncbi.nlm.nih.gov/pubmed/27965191 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 11 %P e297 %T Patients’ Need for Tailored Comparative Health Care Information: A Qualitative Study on Choosing a Hospital %A Zwijnenberg,Nicolien C %A Hendriks,Michelle %A Bloemendal,Evelien %A Damman,Olga C %A de Jong,Judith D %A Delnoij,Diana MJ %A Rademakers,Jany JD %+ Netherlands Institute for Health Services Research (NIVEL), PO Box 1568, Utrecht, 3500 BN, Netherlands, 31 +31 30 2729863, m.hendriks@nivel.nl %K patients %K decision making %K choice behavior %K qualitative research %K quality of health care %K hospitals %D 2016 %7 28.11.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: The Internet is increasingly being used to provide patients with information about the quality of care of different health care providers. Although online comparative health care information is widely available internationally, and patients have been shown to be interested in this information, its effect on patients’ decision making is still limited. Objective: This study aimed to explore patients’ preferences regarding information presentation and their values concerning tailored comparative health care information. Meeting patients’ information presentation needs might increase the perceived relevance and use of the information. Methods: A total of 38 people participated in 4 focus groups. Comparative health care information about hip and knee replacement surgery was used as a case example. One part of the interview focused on patients’ information presentation preferences, whereas the other part focused on patients’ values of tailored information (ie, showing reviews of patients with comparable demographics). The qualitative data were transcribed verbatim and analyzed using the constant comparative method. Results: The following themes were deduced from the transcripts: number of health care providers to be presented, order in which providers are presented, relevancy of tailoring patient reviews, and concerns about tailoring. Participants’ preferences differed concerning how many and in which order health care providers must be presented. Most participants had no interest in patient reviews that were shown for specific subgroups based on age, gender, or ethnicity. Concerns of tailoring were related to the representativeness of results and the complexity of information. A need for information about the medical specialist when choosing a hospital was stressed by several participants. Conclusions: The preferences for how comparative health care information should be presented differ between people. “Information on demand” and information about the medical specialist might be promising ways to increase the relevancy and use of online comparative health care information. Future research should focus on how different groups of people use comparative health care information for different health care choices in real life. %M 27895006 %R 10.2196/jmir.4436 %U http://www.jmir.org/2016/11/e297/ %U https://doi.org/10.2196/jmir.4436 %U http://www.ncbi.nlm.nih.gov/pubmed/27895006 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 10 %P e276 %T The Impact of the Internet on Health Consultation Market Concentration: An Econometric Analysis of Secondary Data %A Li,Jia %A Zhang,Ya %A Ma,Ling %A Liu,Xuan %+ E-commerce Institute, School of Business, East China University of Science and Technology, 130 Meilong Rd., Shanghai, 200237, China, 86 2164253177, maling@ecust.edu.cn %K long tail effect %K superstar effect %K E-consultation %K market concentration %K information asymmetry %K signaling theory %K online reputation %K self-representation %D 2016 %7 28.10.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market. Objective: The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation). Methods: We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis. Results: The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated. Conclusions: When health care services are delivered online, the market will be more concentrated (known as the “Superstar” effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors. %M 27793793 %R 10.2196/jmir.6423 %U http://www.jmir.org/2016/10/e276/ %U https://doi.org/10.2196/jmir.6423 %U http://www.ncbi.nlm.nih.gov/pubmed/27793793 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 10 %P e279 %T Correlating Ratings of Health Insurance Plans to Their Providers' Attributes %A Shetty,Prajna %A Rivas,Ryan %A Hristidis,Vagelis %+ University of California, Riverside, 363 Winston Chung Hall, 900 University Ave, Riverside, CA, 92521, United States, 1 951 827 2838, rriva002@ucr.edu %K health insurance %K doctor reviews %K doctor attributes %K insurance plans quality %D 2016 %7 24.10.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: There is a push towards quality measures in health care. As a consequence, the National Committee for Quality Assurance (NCQA) has been publishing insurance plan quality measures. Objective: The objective of this study was to examine the relationship between insurance plan quality measures and the participating providers (doctors). Methods: We collected and analyzed provider and insurance plan data from several online sources, including provider directories, provider referrals and awards, patient reviewing sites, and hospital rankings. The relationships between the provider attributes and the insurance plan quality measures were examined. Results: Our analysis yielded several findings: (1) there is a moderate Pearson correlation (r=.376) between consumer satisfaction insurance plan scores and review ratings of the member providers, (2) referral frequency and provider awards are negligibly correlated to consumer satisfaction plan scores (correlations of r=.031 and r=.183, respectively), (3) there is weak positive correlation (r=.266) between the cost charged for the same procedures and consumer satisfaction plan scores, and (4) there is no significant correlation between member specialists’ review ratings and specialty-specific insurance plan treatment scores for most specialties, except a surprising weak negative correlation for diabetes treatment (r=-.259). Conclusions: Our findings may be used by consumers to make informed choices about their insurance plans or by insurances to understand the relationship between patients’ satisfaction and their network of providers. %M 27777217 %R 10.2196/jmir.6475 %U http://www.jmir.org/2016/10/e279/ %U https://doi.org/10.2196/jmir.6475 %U http://www.ncbi.nlm.nih.gov/pubmed/27777217 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 9 %P e254 %T Do Health Care Providers Use Online Patient Ratings to Improve the Quality of Care? Results From an Online-Based Cross-Sectional Study %A Emmert,Martin %A Meszmer,Nina %A Sander,Uwe %+ Health Services Management, Institute of Management, School of Business and Economics, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 90403, Germany, 49 9115302 ext 253, Martin.Emmert@fau.de %K public reporting %K physician-rating website %K quality measures %K patient care %K quality of health care %D 2016 %7 19.09.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Objective: Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. Methods: We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers’ demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Results: Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Conclusions: Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care. %M 27644135 %R 10.2196/jmir.5889 %U http://www.jmir.org/2016/9/e254/ %U https://doi.org/10.2196/jmir.5889 %U http://www.ncbi.nlm.nih.gov/pubmed/27644135 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 8 %P e217 %T Exploring Patients’ Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study %A Patel,Salma %A Cain,Rebecca %A Neailey,Kevin %A Hooberman,Lucy %+ WMG, University of Warwick, Coventry, CV47AL, United Kingdom, 44 24 7657 5951, salma.patel@warwick.ac.uk %K Web-based reviews %K physician quality %K primary care %K Internet %K quality patient empowerment %K quality transparency %K public reporting %D 2016 %7 05.08.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient feedback websites or doctor rating websites are increasingly being used by patients to give feedback about their health care experiences. There is little known about why patients in England may give Web-based feedback and what may motivate or dissuade them from giving Web-based feedback. Objective: The aim of this study was to explore patients’ views toward giving Web-based feedback and ratings to general practitioners (GPs), within the context of other feedback methods available in primary care in England, and in particular, paper-based feedback cards. Methods: A descriptive exploratory qualitative approach using face-to-face semistructured interviews was used in this study. Purposive sampling was used to recruit 18 participants from different age groups in London and Coventry. Interviews were transcribed verbatim and analyzed using applied thematic analysis. Results: Half of the participants in this study were not aware of the opportunity to leave feedback for GPs, and there was limited awareness about the methods available to leave feedback for a GP. The majority of participants were not convinced that formal patient feedback was needed by GPs or would be used by GPs for improvement, regardless of whether they gave it via a website or on paper. Some participants said or suggested that they may leave feedback on a website rather than on a paper-based feedback card for several reasons: because of the ability and ease of giving it remotely; because it would be shared with the public; and because it would be taken more seriously by GPs. Others, however, suggested that they would not use a website to leave feedback for the opposite reasons: because of accessibility issues; privacy and security concerns; and because they felt feedback left on a website may be ignored. Conclusions: Patient feedback and rating websites as they currently are will not replace other mechanisms for patients in England to leave feedback for a GP. Rather, they may motivate a small number of patients who have more altruistic motives or wish to place collective pressure on a GP to give Web-based feedback. If the National Health Service or GP practices want more patients to leave Web-based feedback, we suggest they first make patients aware that they can leave anonymous feedback securely on a website for a GP. They can then convince them that their feedback is needed and wanted by GPs for improvement, and that the reviews they leave on the website will be of benefit to other patients to decide which GP to see or which GP practice to join. %M 27496366 %R 10.2196/jmir.5865 %U http://www.jmir.org/2016/8/e217/ %U https://doi.org/10.2196/jmir.5865 %U http://www.ncbi.nlm.nih.gov/pubmed/27496366 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 7 %P e202 %T Health Care Applicability of a Patient-Centric Web Portal for Patients’ Medication Experience %A Hong,Song Hee %A Lee,Woojung %A AlRuthia,Yazed %+ College of Pharmacy, Seoul National University, College of Pharmacy Bldg 20-210, Seoul,, Republic Of Korea, 82 2 880 1547, songhhong@snu.ac.kr %K patient-physician communication %K medication experience outcomes %K patient reports %K Internet %K patient-centered practice %K Web portal %D 2016 %7 22.07.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: With the advent of the patient-centered care paradigm, it is important to examine what patients’ reports of medication experience (PROME) mean to patient care. PROME available through a Web portal provide information on medication treatment options and outcomes from the patient’s perspective. Patients who find certain PROME compelling are likely to mention them at their physician visit, triggering a discussion between the patient and the physician. However, no studies have examined PROME’s potential applicability to patient care. Objective: This study aimed to examine older (≥50 years) adults’ perceptions of the health care applicability of a hypothetical PROME Web portal. Specifically, this study investigated whether PROME would facilitate patient-physician communication, and identified the preferred reporting items and the trusted sponsors of such a PROME Web portal. Methods: We used a cross-sectional, self-administered, 5-point Likert scale survey to examine participants’ perceptions of a hypothetical PROME Web portal that compared PROME for 5 common antihypertensive medications. Between August and December 2013, we recruited 300 members of 7 seniors’ centers in a metropolitan area of a southeastern state of the United States to participate in the survey. Results: An overwhelming majority of study participants (243/300, 81.0%) had a favorable perception of PROME’s health care applicability. They were mostly positive that PROME would facilitate patient-physician communication, except for the perception that physicians would be upset by the mention of PROME (n=133, 44.3%). Further, 85.7% (n=257) of participants considered the PROME information trustworthy, and 72.0% (n=216) were willing to participate by reporting their own medication experiences. Study participants wanted the PROME Web portal to report the number of reviews, star ratings, and individual comments concerning different medication attributes such as side effects (224/809, 27.7%), cost (168/809, 20.8%), and effectiveness (153/809, 18.9%). Finally, the PROME Web portal sponsorship was important to participants, with the most trusted sponsor being academic institutions (120/400, 30.0%). Conclusions: PROME, if well compiled through Web portals, have the potential to facilitate patient-physician communication. %M 27450362 %R 10.2196/jmir.5813 %U http://www.jmir.org/2016/7/e202/ %U https://doi.org/10.2196/jmir.5813 %U http://www.ncbi.nlm.nih.gov/pubmed/27450362 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 7 %P e201 %T Investigating the Potential Contribution of Patient Rating Sites to Hospital Supervision: Exploratory Results From an Interview Study in the Netherlands %A Kleefstra,Sophia Martine %A Zandbelt,Linda C %A Borghans,Ine %A de Haes,Hanneke J.C.J.M %A Kool,Rudolf B %+ Dutch Health Care Inspectorate, Department of Risk Detection and Development, Stadsplateau 1, Utrecht, 3521 AZ, Netherlands, 31 881205000, sm.kleefstra@igz.nl %K patient rating sites %K patient satisfaction %K patient experiences %K hospitals %K quality of health care %K supervision %D 2016 %7 20.07.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Over the last decades, the patient perspective on health care quality has been unconditionally integrated into quality management. For several years now, patient rating sites have been rapidly gaining attention. These offer a new approach toward hearing the patient’s perspective on the quality of health care. Objective: The aim of our study was to explore whether and how patient reviews of hospitals, as reported on rating sites, have the potential to contribute to health care inspector’s daily supervision of hospital care. Methods: Given the unexplored nature of the topic, an interview study among hospital inspectors was designed in the Netherlands. We performed 2 rounds of interviews with 10 senior inspectors, addressing their use and their judgment on the relevance of review data from a rating site. Results: All 10 Dutch senior hospital inspectors participated in this research. The inspectors initially showed some reluctance to use the major patient rating site in their daily supervision. This was mainly because of objections such as worries about how representative they are, subjectivity, and doubts about the relevance of patient reviews for supervision. However, confrontation with, and assessment of, negative reviews by the inspectors resulted in 23% of the reviews being deemed relevant for risk identification. Most inspectors were cautiously positive about the contribution of the reviews to their risk identification. Conclusions: Patient rating sites may be of value to the risk-based supervision of hospital care carried out by the Health Care Inspectorate. Health care inspectors do have several objections against the use of patient rating sites for daily supervision. However, when they are presented with texts of negative reviews from a hospital under their supervision, it appears that most inspectors consider it as an additional source of information to detect poor quality of care. Still, it should always be accompanied and verified by other quality and safety indicators. More research on the value and usability of patient rating sites in daily hospital supervision and other health settings is needed. %M 27439392 %R 10.2196/jmir.5552 %U http://www.jmir.org/2016/7/e201/ %U https://doi.org/10.2196/jmir.5552 %U http://www.ncbi.nlm.nih.gov/pubmed/27439392 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 7 %P e198 %T Influence of Intensified Supervision by Health Care Inspectorates on Online Patient Ratings of Hospitals: A Multilevel Study of More Than 43,000 Online Ratings %A Kool,Rudolf Bertijn %A Kleefstra,Sophia Martine %A Borghans,Ine %A Atsma,Femke %A van de Belt,Tom H %+ Radboud University Medical Center, Radboud Institute for Health Sciences, IQ Healthcare, Postbus 9101, Huispost 114, Nijmegen,, Netherlands, 31 611531143, tijn.kool@radboudumc.nl %K rating sites %K supervision %K social media %K online reviews %K hospitals %D 2016 %7 15.07.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: In the Netherlands, hospitals with quality or safety issues are put under intensified supervision by the Dutch Health Care Inspectorate, which involves frequent announced and unannounced site visits and other measures. Patient rating sites are an upcoming phenomenon in health care. Patient reviews might be influenced by perceived quality including the media coverage of health care providers when the health care inspectorate imposes intensified supervision, but no data are available to show how these are related. Objective: The aim of this study was to investigate whether and how being under intensified supervision of the health care inspectorate influences online patient ratings of hospitals. Methods: We performed a longitudinal study using data from the patient rating site Zorgkaart Nederland, from January 1, 2010 to December 31, 2015. We compared data of 7 hospitals under intensified supervision with a control group of 28 hospitals. The dataset contained 43,856 ratings. We performed a multilevel logistic regression analysis to account for clustering of ratings within hospitals. Fixed effects in our analysis were hospital type, time, and the period of intensified supervision. Random effect was the hospital. The outcome variable was the dichotomized rating score. Results: The period of intensified supervision was associated with a low rating score for the hospitals compared with control group hospitals; both 1 year before intensified supervision (odds ratio, OR, 1.67, 95% CI 1.06-2.63) and 1 year after (OR 1.79, 95% CI 1.14-2.81) the differences are significant. For all periods, the odds on a low rating score for hospitals under intensified supervision are higher than for the control group hospitals, corrected for time. Time is also associated with low rating scores, with decreasing ORs over time since 2010. Conclusions: Hospitals that are confronted with intensified supervision by the health care inspectorate have lower ratings on patient rating sites. The scores are independent of the period: before, during, or just after the intervention by the health care inspectorate. Health care inspectorates might learn from these results because they indicate that the inspectorate identifies the same hospitals as “at risk” as the patients rate as underperformers. %M 27421302 %R 10.2196/jmir.5884 %U http://www.jmir.org/2016/7/e198/ %U https://doi.org/10.2196/jmir.5884 %U http://www.ncbi.nlm.nih.gov/pubmed/27421302 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 7 %P e186 %T Which Doctor to Trust: A Recommender System for Identifying the Right Doctors %A Guo,Li %A Jin,Bo %A Yao,Cuili %A Yang,Haoyu %A Huang,Degen %A Wang,Fei %+ School of Innovation and Entrepreneurship, Dalian University of Technology, 816 Yanjiao Building, Dalian University of Technolog, 2 Linggong Road, High-Tech Zone, Dalian, 116024, China, 86 13084100305, jinbo@dlut.edu.cn %K recommender systems %K feature selection %K rank aggregation %K key opinion leaders %D 2016 %7 07.07.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Key opinion leaders (KOLs) are people who can influence public opinion on a certain subject matter. In the field of medical and health informatics, it is critical to identify KOLs on various disease conditions. However, there have been very few studies on this topic. Objective: We aimed to develop a recommender system for identifying KOLs for any specific disease with health care data mining. Methods: We exploited an unsupervised aggregation approach for integrating various ranking features to identify doctors who have the potential to be KOLs on a range of diseases. We introduce the design, implementation, and deployment details of the recommender system. This system collects the professional footprints of doctors, such as papers in scientific journals, presentation activities, patient advocacy, and media exposure, and uses them as ranking features to identify KOLs. Results: We collected the information of 2,381,750 doctors in China from 3,657,797 medical journal papers they published, together with their profiles, academic publications, and funding. The empirical results demonstrated that our system outperformed several benchmark systems by a significant margin. Moreover, we conducted a case study in a real-world system to verify the applicability of our proposed method. Conclusions: Our results show that doctors’ profiles and their academic publications are key data sources for identifying KOLs in the field of medical and health informatics. Moreover, we deployed the recommender system and applied the data service to a recommender system of the China-based Internet technology company NetEase. Patients can obtain authority ranking lists of doctors with this system on any given disease. %M 27390219 %R 10.2196/jmir.6015 %U http://www.jmir.org/2016/7/e186/ %U https://doi.org/10.2196/jmir.6015 %U http://www.ncbi.nlm.nih.gov/pubmed/27390219 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 6 %P e129 %T Consumer Decision-Making Based on Review Websites: Are There Differences Between Choosing a Hotel and Choosing a Physician? %A Rothenfluh,Fabia %A Germeni,Evi %A Schulz,Peter J %+ Institute of Communication and Health, Faculty of Communication Sciences, Università della Svizzera italiana, Via Giuseppe Buffi 13, Lugano, 6900, Switzerland, 0041 58 666 4485, fabia.rothenfluh@usi.ch %K physician rating website %K qualitative research %K health care quality assessment %K electronic word of mouth %K health care provider %K physician choice %K patient satisfaction %D 2016 %7 16.06.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Web users are increasingly encouraged to rate and review consumer services (eg, hotels, restaurants) and, more recently, this is also the case for physicians and medical services. The resemblance in the setup and design of commercial rating websites (CRWs) and Web-based physician rating websites (PRWs) raises the question of whether choice-making processes based on the two types of websites could also be similar. Objective: This qualitative study sought to explore the extent to which consumer decision making based on Web-based reviews is the same for consumer services (ie, choice of a hotel) and health services (ie, choice of a pediatrician), while providing an in-depth understanding of potential differences or similarities. Methods: Between June and August 2015, we carried out a total of 22 qualitative interviews with young parents residing in the German-speaking part of Switzerland. Participants were invited to complete 2 choice tasks, which involved (1) choosing a hotel based on the commercial Web-based rating website TripAdvisor and (2) selecting a pediatrician based on the PRW Jameda. To better understand consumers’ thought processes, we instructed participants to “think aloud”, namely to verbalize their thinking while sorting through information and reaching decisions. Using a semistructured interview guide, we subsequently posed open-ended questions to allow them to elaborate more on factors influencing their decision making, level of confidence in their final choice, and perceived differences and similarities in their search for a hotel and a physician. All interviews were recorded, transcribed, and analyzed using an inductive thematic approach. Results: Participants spent on average 9:57 minutes (standard deviation=9:22, minimum=3:46, maximum=22:25) searching for a hotel and 6:17 minutes (standard deviation=4:47, minimum=00:38, maximum=19:25) searching for a pediatrician. Although the choice of a pediatrician was perceived as more important than the choice of a hotel, participants found choosing a physician much easier than selecting an appropriate accommodation. Four main themes emerged from the analysis of our interview data that can explain the differences in search time and choice confidence: (1) trial and error, (2) trust, (3) competence assessment, and (4) affect and likeability. Conclusions: Our results suggest that, despite congruent website designs, individuals only trust review information to choose a hotel, but refuse to fully rely on it for selecting a physician. The design and content of Web-based PRWs need to be adjusted to better address the differing information needs of health consumers. %M 27311623 %R 10.2196/jmir.5580 %U http://www.jmir.org/2016/6/e129/ %U https://doi.org/10.2196/jmir.5580 %U http://www.ncbi.nlm.nih.gov/pubmed/27311623 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 18 %N 5 %P e108 %T The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews %A Hao,Haijing %A Zhang,Kunpeng %+ Department of Management Science and Information Systems, University of Massachusetts Boston, 100 Morrissey Blvd, Boston, MA, 02125, United States, 1 8572728162, haohaijing@gmail.com %K online doctor review %K physician ratings %K text mining %K China health consumers %D 2016 %7 10.05.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Many Web-based health care platforms allow patients to evaluate physicians by posting open-end textual reviews based on their experiences. These reviews are helpful resources for other patients to choose high-quality doctors, especially in countries like China where no doctor referral systems exist. Analyzing such a large amount of user-generated content to understand the voice of health consumers has attracted much attention from health care providers and health care researchers. Objective: The aim of this paper is to automatically extract hidden topics from Web-based physician reviews using text-mining techniques to examine what Chinese patients have said about their doctors and whether these topics differ across various specialties. This knowledge will help health care consumers, providers, and researchers better understand this information. Methods: We conducted two-fold analyses on the data collected from the “Good Doctor Online” platform, the largest online health community in China. First, we explored all reviews from 2006-2014 using descriptive statistics. Second, we applied the well-known topic extraction algorithm Latent Dirichlet Allocation to more than 500,000 textual reviews from over 75,000 Chinese doctors across four major specialty areas to understand what Chinese health consumers said online about their doctor visits. Results: On the “Good Doctor Online” platform, 112,873 out of 314,624 doctors had been reviewed at least once by April 11, 2014. Among the 772,979 textual reviews, we chose to focus on four major specialty areas that received the most reviews: Internal Medicine, Surgery, Obstetrics/Gynecology and Pediatrics, and Chinese Traditional Medicine. Among the doctors who received reviews from those four medical specialties, two-thirds of them received more than two reviews and in a few extreme cases, some doctors received more than 500 reviews. Across the four major areas, the most popular topics reviewers found were the experience of finding doctors, doctors’ technical skills and bedside manner, general appreciation from patients, and description of various symptoms. Conclusions: To the best of our knowledge, our work is the first study using an automated text-mining approach to analyze a large amount of unstructured textual data of Web-based physician reviews in China. Based on our analysis, we found that Chinese reviewers mainly concentrate on a few popular topics. This is consistent with the goal of Chinese online health platforms and demonstrates the health care focus in China’s health care system. Our text-mining approach reveals a new research area on how to use big data to help health care providers, health care administrators, and policy makers hear patient voices, target patient concerns, and improve the quality of care in this age of patient-centered care. Also, on the health care consumer side, our text mining technique helps patients make more informed decisions about which specialists to see without reading thousands of reviews, which is simply not feasible. In addition, our comparison analysis of Web-based physician reviews in China and the United States also indicates some cultural differences. %M 27165558 %R 10.2196/jmir.4430 %U http://www.jmir.org/2016/5/e108/ %U https://doi.org/10.2196/jmir.4430 %U http://www.ncbi.nlm.nih.gov/pubmed/27165558 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 12 %P e276 %T General Practitioners’ Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England %A Patel,Salma %A Cain,Rebecca %A Neailey,Kevin %A Hooberman,Lucy %+ WMG, University of Warwick, International Digital Laboratory, Coventry, CV4 7AL, United Kingdom, 44 24 7657 5951, salma.patel@warwick.ac.uk %K online reviews %K physician quality %K primary care %K Internet %K quality %K patient empowerment %K quality transparency %K public reporting %K attitude of health personnel %K delivery of health care %K feedback %D 2015 %7 08.12.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: The growth in the volume of online patient feedback, including online patient ratings and comments, suggests that patients are embracing the opportunity to review online their experience of receiving health care. Very little is known about health care professionals’ attitudes toward online patient feedback and whether health care professionals are comfortable with the public nature of the feedback. Objective: The aim of the overall study was to explore and describe general practitioners’ attitudes toward online patient feedback. This paper reports on the findings of one of the aims of the study, which was to explore and understand the concerns that general practitioners (GPs) in England have about online patient feedback. This could then be used to improve online patient feedback platforms and help to increase usage of online patient feedback by GPs and, by extension, their patients. Methods: A descriptive qualitative approach using face-to-face semistructured interviews was used in this study. A topic guide was developed following a literature review and discussions with key stakeholders. GPs (N=20) were recruited from Cambridgeshire, London, and Northwest England through probability and snowball sampling. Interviews were transcribed verbatim and analyzed in NVivo using the framework method, a form of thematic analysis. Results: Most participants in this study had concerns about online patient feedback. They questioned the validity of online patient feedback because of data and user biases and lack of representativeness, the usability of online patient feedback due to the feedback being anonymous, the transparency of online patient feedback because of the risk of false allegations and breaching confidentiality, and the resulting impact of all those factors on them, their professional practice, and their relationship with their patients. Conclusions: The majority of GPs interviewed had reservations and concerns about online patient feedback and questioned its validity and usefulness among other things. Based on the findings from the study, recommendations for online patient feedback website providers in England are given. These include suggestions to make some specific changes to the platform and the need to promote online patient feedback more among both GPs and health care users, which may help to reduce some of the concerns raised by GPs about online patient feedback in this study. %M 26681299 %R 10.2196/jmir.4989 %U http://www.jmir.org/2015/12/e276/ %U https://doi.org/10.2196/jmir.4989 %U http://www.ncbi.nlm.nih.gov/pubmed/26681299 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 8 %P e211 %T Assessment of Web-Based Consumer Reviews as a Resource for Drug Performance %A Adusumalli,Swarnaseetha %A Lee,HueyTyng %A Hoi,Qiangze %A Koo,Si-Lin %A Tan,Iain Beehuat %A Ng,Pauline Crystal %+ Genome Institute of Singapore, 60 Biopolis St., Singapore, , Singapore, 65 6808 8310, ngpc4@gis.a-star.edu.sg %K consumer drug reviews %K online drug ratings %K WebMD %K online health websites %D 2015 %7 28.08.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Some health websites provide a public forum for consumers to post ratings and reviews on drugs. Drug reviews are easily accessible and comprehensible, unlike clinical trials and published literature. Because the public increasingly uses the Internet as a source of medical information, it is important to know whether such information is reliable. Objective: We aim to examine whether Web-based consumer drug ratings and reviews can be used as a resource to compare drug performance. Methods: We analyzed 103,411 consumer-generated reviews on 615 drugs used to treat 249 disease conditions from the health website WebMD. Statistical analysis identified 427 drug pairs from 24 conditions for which two drugs treating the same condition had significantly and substantially different satisfaction ratings (with at least a half-point difference between Web-based ratings and P<.01). PubMed and Google Scholar were searched for publications that were assessed for concordance with findings online. Results: Scientific literature was found for 77 out of the 427 drug pairs and compared to findings online. Nearly two-thirds (48/77, 62%) of the online drug trends with at least a half-point difference in online ratings were supported by published literature (P=.02). For a 1-point online rating difference, the concordance rate increased to 68% (15/22) (P=.07). The discrepancies between scientific literature and findings online were further examined to obtain more insights into the usability of Web-based consumer-generated reviews. We discovered that (1) drugs with FDA black box warnings or used off-label were rated poorly in Web-based reviews, (2) drugs with addictive properties were rated higher than their counterparts in Web-based reviews, and (3) second-line or alternative drugs were rated higher. In addition, Web-based ratings indicated drug delivery problems. If FDA black box warning labels are used to resolve disagreements between publications and online trends, the concordance rate increases to 71% (55/77) (P<.001) for a half-point rating difference and 82% (18/22) for a 1-point rating difference (P=.002). Our results suggest that Web-based reviews can be used to inform patients’ drug choices, with certain caveats. Conclusions: Web-based reviews can be viewed as an orthogonal source of information for consumers, physicians, and drug manufacturers to assess the performance of a drug. However, one should be cautious to rely solely on consumer reviews as ratings can be strongly influenced by the consumer experience. %M 26319108 %R 10.2196/jmir.4396 %U http://www.jmir.org/2015/8/e211/ %U https://doi.org/10.2196/jmir.4396 %U http://www.ncbi.nlm.nih.gov/pubmed/26319108 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 2 %P e65 %T Identifying Quality Indicators Used by Patients to Choose Secondary Health Care Providers: A Mixed Methods Approach %A King,Dominic %A Zaman,Sameer %A Zaman,Saman Sara %A Kahlon,Gurnaaz Kaur %A Naik,Aditi %A Jessel,Amar Singh %A Nanavati,Niraj %A Shah,Akash %A Cox,Benita %A Darzi,Ara %+ Imperial College London, 10th Floor QEQM, St. Mary's Hospital, London, , United Kingdom, 44 7971500964, dominic.king@imperial.ac.uk %K mHealth %K patient choice %K mobile phone %K hospital ratings %D 2015 %7 05.06.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: Patients in health systems across the world can now choose between different health care providers. Patients are increasingly using websites and apps to compare the quality of health care services available in order to make a choice of provider. In keeping with many patient-facing platforms, most services currently providing comparative information on different providers do not take account of end-user requirements or the available evidence base. Objective: To investigate what factors were considered most important when choosing nonemergency secondary health care providers in the United Kingdom with the purpose of translating these insights into a ratings platform delivered through a consumer mHealth app. Methods: A mixed methods approach was used to identify key indicators incorporating a literature review to identify and categorize existing quality indicators, a questionnaire survey to formulate a ranked list of performance indicators, and focus groups to explore rationales behind the rankings. Findings from qualitative and quantitative methodologies were mapped onto each other under the four categories identified by the literature review. Results: Quality indicators were divided into four categories. Hospital access was the least important category. The mean differences between the other three categories hospital statistics, hospital staff, and hospital facilities, were not statistically significant. Staff competence was the most important indicator in the hospital staff category; cleanliness and up-to-date facilities were equally important in hospital facilities; ease of travel to the hospital was found to be most important in hospital access. All quality indicators within the hospital statistics category were equally important. Focus groups elaborated that users find it difficult to judge staff competence despite its importance. Conclusions: A mixed methods approach is presented, which supported a patient-centered development and evaluation of a hospital ratings mobile app. Where possible, mHealth developers should use systematic research methods in order to more closely meet the needs of the end user and add credibility to their platform. %M 26048441 %R 10.2196/mhealth.3808 %U http://mhealth.jmir.org/2015/2/e65/ %U https://doi.org/10.2196/mhealth.3808 %U http://www.ncbi.nlm.nih.gov/pubmed/26048441 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 6 %P e134 %T The Development of Online Doctor Reviews in China: An Analysis of the Largest Online Doctor Review Website in China %A Hao,Haijing %+ University of Massachusetts Boston, Department of Management Science and Information Systems, 100 Morrissey Boulevard, Boston, MA, 02125, United States, 1 6172877706, haohaijing@gmail.com %K online doctor reviews %K China health system %K quantitative review %K qualitative review %K patient empowerment %K physician quality %D 2015 %7 01.06.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Since the time of Web 2.0, more and more consumers have used online doctor reviews to rate their doctors or to look for a doctor. This phenomenon has received health care researchers’ attention worldwide, and many studies have been conducted on online doctor reviews in the United States and Europe. But no study has yet been done in China. Also, in China, without a mature primary care physician recommendation system, more and more Chinese consumers seek online doctor reviews to look for a good doctor for their health care concerns. Objective: This study sought to examine the online doctor review practice in China, including addressing the following questions: (1) How many doctors and specialty areas are available for online review? (2) How many online reviews are there on those doctors? (3) What specialty area doctors are more likely to be reviewed or receive more reviews? (4) Are those reviews positive or negative? Methods: This study explores an empirical dataset from Good Doctor website, haodf.com—the earliest and largest online doctor review and online health care community website in China—from 2006 to 2014, to examine the stated research questions by using descriptive statistics, binary logistic regression, and multivariate linear regression. Results: The dataset from the Good Doctor website contained 314,624 doctors across China and among them, 112,873 doctors received 731,543 quantitative reviews and 772,979 qualitative reviews as of April 11, 2014. On average, 37% of the doctors had been reviewed on the Good Doctor website. Gynecology-obstetrics-pediatrics doctors were most likely to be reviewed, with an odds ratio (OR) of 1.497 (95% CI 1.461-1.535), and internal medicine doctors were less likely to be reviewed, with an OR of 0.94 (95% CI 0.921-0.960), relative to the combined small specialty areas. Both traditional Chinese medicine doctors and surgeons were more likely to be reviewed than the combined small specialty areas, with an OR of 1.483 (95% CI 1.442-1.525) and an OR of 1.366 (95% CI 1.337-1.395), respectively. Quantitatively, traditional Chinese medicine doctors (P<.001) and gynecology-obstetrics-pediatrics doctors (P<.001) received more reviews than the combined small specialty areas. But internal medicine doctors received fewer reviews than the combined small specialty areas (P<.001). Also, the majority of quantitative reviews were positive—about 88% were positive for the doctors' treatment effect measure and 91% were positive for the bedside manner measure. This was the case for the four major specialty areas, which had the most number of doctors—internal medicine, gynecology-obstetrics-pediatrics, surgery, and traditional Chinese medicine. Conclusions: Like consumers in the United States and Europe, Chinese consumers have started to use online doctor reviews. Similar to previous research on other countries’ online doctor reviews, the online reviews in China covered almost every medical specialty, and most of the reviews were positive even though all of the reviewing procedures and the final available information were anonymous. The average number of reviews per rated doctor received in this dataset was 6, which was higher than that for doctors in the United States or Germany, probably because this dataset covered a longer time period than did the US or German dataset. But this number is still very small compared to any doctor’s real patient population, and it cannot represent the reality of that population. Also, since all the data used for analysis were from one single website, the data might be biased and might not be a representative national sample of China. %M 26032933 %R 10.2196/jmir.4365 %U http://www.jmir.org/2015/6/e134/ %U https://doi.org/10.2196/jmir.4365 %U http://www.ncbi.nlm.nih.gov/pubmed/26032933 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 5 %P e102 %T Sources of Traffic and Visitors’ Preferences Regarding Online Public Reports of Quality: Web Analytics and Online Survey Results %A Bardach,Naomi S %A Hibbard,Judith H %A Greaves,Felix %A Dudley,R Adams %+ University of California San Francisco, Department of Pediatrics, Philip R Lee Institute of Health Policy Studies, Center for Healthcare Value, 3333 California St Suite 265, San Francisco, CA, 94118, United States, 1 415 476 9188, bardachn@peds.ucsf.edu %K consumer health information %K Internet/statistics and numerical data %K search engine %K quality of health care %K consumer behavior %D 2015 %7 01.05.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: In the context of the Affordable Care Act, there is extensive emphasis on making provider quality transparent and publicly available. Online public reports of quality exist, but little is known about how visitors find reports or about their purpose in visiting. Objective: To address this gap, we gathered website analytics data from a national group of online public reports of hospital or physician quality and surveyed real-time visitors to those websites. Methods: Websites were recruited from a national group of online public reports of hospital or physician quality. Analytics data were gathered from each website: number of unique visitors, method of arrival for each unique visitor, and search terms resulting in visits. Depending on the website, a survey invitation was launched for unique visitors on landing pages or on pages with quality information. Survey topics included type of respondent (eg, consumer, health care professional), purpose of visit, areas of interest, website experience, and demographics. Results: There were 116,657 unique visitors to the 18 participating websites (1440 unique visitors/month per website), with most unique visitors arriving through search (63.95%, 74,606/116,657). Websites with a higher percent of traffic from search engines garnered more unique visitors (P=.001). The most common search terms were for individual hospitals (23.25%, 27,122/74,606) and website names (19.43%, 22,672/74,606); medical condition terms were uncommon (0.81%, 605/74,606). Survey view rate was 42.48% (49,560/116,657 invited) resulting in 1755 respondents (participation rate=3.6%). There were substantial proportions of consumer (48.43%, 850/1755) and health care professional respondents (31.39%, 551/1755). Across websites, proportions of consumer (21%-71%) and health care professional respondents (16%-48%) varied. Consumers were frequently interested in using the information to choose providers or assess the quality of their provider (52.7%, 225/427); the majority of those choosing a provider reported that they had used the information to do so (78%, 40/51). Health care professional (26.6%, 115/443) and consumer (20.8%, 92/442) respondents wanted cost information and consumers wanted patient narrative comments (31.5%, 139/442) on the public reports. Health care professional respondents rated the experience on the reports higher than consumers did (mean 7.2, SD 2.2 vs mean 6.2, SD 2.7; scale 0-10; P<.001). Conclusions: Report sponsors interested in increasing the influence of their reports could consider using techniques to improve search engine traffic, providing cost information and patient comments, and improving the website experience for both consumers and health care professionals. %M 25934100 %R 10.2196/jmir.3637 %U http://www.jmir.org/2015/5/e102/ %U https://doi.org/10.2196/jmir.3637 %U http://www.ncbi.nlm.nih.gov/pubmed/25934100 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 4 %P e93 %T Insights Into the Impact of Online Physician Reviews on Patients’ Decision Making: Randomized Experiment %A Grabner-Kräuter,Sonja %A Waiguny,Martin KJ %+ Department of Marketing and International Management, Alpen-Adria-Universität Klagenfurt, Universitätsstrasse 65-67, Klagenfurt, 9020, Austria, 43 463 2700 ext 4042, sonja.grabner@aau.at %K physician reviews %K physician-rating website %K physician choice making %K patient experiences %K word of mouth %D 2015 %7 09.04.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician-rating websites combine public reporting with social networking and offer an attractive means by which users can provide feedback on their physician and obtain information about other patients’ satisfaction and experiences. However, research on how users evaluate information on these portals is still scarce and only little knowledge is available about the potential influence of physician reviews on a patient’s choice. Objective: Starting from the perspective of prospective patients, this paper sets out to explore how certain characteristics of physician reviews affect the evaluation of the review and users’ attitudes toward the rated physician. We propose a model that relates review style and review number to constructs of review acceptance and check it with a Web-based experiment. Methods: We employed a randomized 2x2 between-subject, factorial experiment manipulating the style of a physician review (factual vs emotional) and the number of reviews for a certain physician (low vs high) to test our hypotheses. A total of 168 participants were presented with a Web-based questionnaire containing a short description of a dentist search scenario and the manipulated reviews for a fictitious dental physician. To investigate the proposed hypotheses, we carried out moderated regression analyses and a moderated mediation analysis using the PROCESS macro 2.11 for SPSS version 22. Results: Our analyses indicated that a higher number of reviews resulted in a more positive attitude toward the rated physician. The results of the regression model for attitude toward the physician suggest a positive main effect of the number of reviews (mean [low] 3.73, standard error [SE] 0.13, mean [high] 4.15, SE 0.13). We also observed an interaction effect with the style of the review—if the physician received only a few reviews, fact-oriented reviews (mean 4.09, SE 0.19) induced a more favorable attitude toward the physician compared to emotional reviews (mean 3.44, SE 0.19), but there was no such effect when the physician received many reviews. Furthermore, we found that review style also affected the perceived expertise of the reviewer. Fact-oriented reviews (mean 3.90, SE 0.13) lead to a higher perception of reviewer expertise compared to emotional reviews (mean 3.19, SE 0.13). However, this did not transfer to the attitude toward the physician. A similar effect of review style and number on the perceived credibility of the review was observed. While no differences between emotional and factual style were found if the physician received many reviews, a low number of reviews received lead to a significant difference in the perceived credibility, indicating that emotional reviews were rated less positively (mean 3.52, SE 0.18) compared to fact-oriented reviews (mean 4.15, SE 0.17). Our analyses also showed that perceived credibility of the review fully mediated the observed interaction effect on attitude toward the physician. Conclusions: Physician-rating websites are an interesting new source of information about the quality of health care from the patient’s perspective. This paper makes a unique contribution to an understudied area of research by providing some insights into how people evaluate online reviews of individual doctors. Information attributes, such as review style and review number, have an impact on the evaluation of the review and on the patient’s attitude toward the rated doctor. Further research is necessary to improve our understanding of the influence of such rating sites on the patient's choice of a physician. %M 25862516 %R 10.2196/jmir.3991 %U http://www.jmir.org/2015/4/e93/ %U https://doi.org/10.2196/jmir.3991 %U http://www.ncbi.nlm.nih.gov/pubmed/25862516 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 4 %P e90 %T Identifying Key Hospital Service Quality Factors in Online Health Communities %A Jung,Yuchul %A Hur,Cinyoung %A Jung,Dain %A Kim,Minki %+ Korea Advanced Institute of Science and Technology, College of Business, S304, KAIST Business School, 85 Hoegiro, Dongdaemun-gu, Seoul, 130-722, Republic Of Korea, 82 29583512, minki.kim@kaist.ac.kr %K hospital service factors %K online health communities %K social media-based key quality factors for hospitals %K recommendation type classification %K quality factor analysis %K healthcare policy %D 2015 %7 07.04.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. Objective: As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. Methods: We defined social media–based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea’s two biggest online portals were used to test the effectiveness of detection of social media–based key quality factors for hospitals. Results: To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and classification performance still has room for improvement, but the extraction results are applicable to more detailed analysis. Further analysis of the extracted information reveals that there are differences in the details of social media–based key quality factors for hospitals according to the regions in Korea, and the patterns of change seem to accurately reflect social events (eg, influenza epidemics). Conclusions: These findings could be used to provide timely information to caregivers, hospital officials, and medical officials for health care policies. %M 25855612 %R 10.2196/jmir.3646 %U http://www.jmir.org/2015/4/e90/ %U https://doi.org/10.2196/jmir.3646 %U http://www.ncbi.nlm.nih.gov/pubmed/25855612 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 1 %P e7 %T Using Patient Experiences on Dutch Social Media to Supervise Health Care Services: Exploratory Study %A van de Belt,Tom H %A Engelen,Lucien JLPG %A Verhoef,Lise M %A van der Weide,Marian JA %A Schoonhoven,Lisette %A Kool,Rudolf B %+ Radboud REshape Innovation Center, Radboud University Medical Center, REshape 911, 1st Fl., Reinier Postlaan 4, Nijmegen, 6525 GC, Netherlands, 31 24770080, t.vandebelt@reshape.umcn.nl %K social media %K rating sites %K patient safety %K supervision %D 2015 %7 15.01.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Social media has become mainstream and a growing number of people use it to share health care-related experiences, for example on health care rating sites. These users’ experiences and ratings on social media seem to be associated with quality of care. Therefore, information shared by citizens on social media could be of additional value for supervising the quality and safety of health care services by regulatory bodies, thereby stimulating participation by consumers. Objective: The objective of the study was to identify the added value of social media for two types of supervision by the Dutch Healthcare Inspectorate (DHI), which is the regulatory body charged with supervising the quality and safety of health care services in the Netherlands. These were (1) supervision in response to incidents reported by individuals, and (2) risk-based supervision. Methods: We performed an exploratory study in cooperation with the DHI and searched different social media sources such as Twitter, Facebook, and healthcare rating sites to find additional information for these incidents and topics, from five different sectors. Supervision experts determined the added value for each individual result found, making use of pre-developed scales. Results: Searches in social media resulted in relevant information for six of 40 incidents studied and provided relevant additional information in 72 of 116 cases in risk-based supervision of long-term elderly care. Conclusions: The results showed that social media could be used to include the patient’s perspective in supervision. However, it appeared that the rating site ZorgkaartNederland was the only source that provided information that was of additional value for the DHI, while other sources such as forums and social networks like Twitter and Facebook did not result in additional information. This information could be of importance for health care inspectorates, particularly for its enforcement by risk-based supervision in care of the elderly. Further research is needed to determine the added value for other health care sectors. %M 25592481 %R 10.2196/jmir.3906 %U http://www.jmir.org/2015/1/e7/ %U https://doi.org/10.2196/jmir.3906 %U http://www.ncbi.nlm.nih.gov/pubmed/25592481 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 1 %P e15 %T Evaluations of Dentists on a German Physician Rating Website: An Analysis of the Ratings %A Emmert,Martin %A Halling,Frank %A Meier,Florian %+ Institute of Management (IFM), School of Business and Economics, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 90403, Germany, 49 911 5302 ext 253, Martin.Emmert@fau.de %K physician rating website %K dentist %K patient experience %K Internet %K quality of care %D 2015 %7 12.01.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites have been gaining in importance in both practice and research. However, no evidence is available concerning patients’ ratings of dentists on physician rating websites. Objective: The aim of this study is to present a comprehensive analysis of the ratings of dentists on a German physician rating website over a 2-year period. Methods: All dentist ratings on a German physician rating website (Jameda) from 2012 and 2013 were analyzed. The available dataset contained 76,456 ratings of 23,902 dentists from 72,758 patients. Additional information included the overall score and subscores for 5 mandatory questions, the medical specialty and gender of the dentists, and the age, gender, and health insurance status of the patients. Statistical analysis was conducted using the median test and the Kendall tau-b test. Results: During the study period, 44.57% (23,902/53,626) of all dentists in Germany were evaluated on the physician rating website, Jameda. The number of ratings rose from 28,843 in 2012 to 47,613 in 2013, representing an increase of 65.08%. In detail, 45.37% (10,845/23,902) of dentists were rated once, 43.41% (10,376/23,902) between 2 and 5 times, and 11.21% (2681/23,902) more than 6 times (mean 3.16, SD 5.57). Approximately 90% (21,324/23,902, 89.21%) of dentists received a very good or good overall rating, whereas only 3.02% (721/23,902) were rated with the lowest scores. Better ratings were given either by female or older patients, or by those covered by private health insurance. The best-rated specialty was pediatric dentistry; the lowest ratings were given to orthodontists. Finally, dentists were rated slightly lower in 2013 compared to 2012 (P=.01). Conclusions: The rise in the number of ratings for dentists demonstrates the increasing popularity of physician rating websites and the need for information about health care providers. Future research should assess whether social media, especially Web-based ratings, are suitable in practice for patients and other stakeholders in health care (eg, insurance providers) to reflect the clinical quality of care. %M 25582914 %R 10.2196/jmir.3830 %U http://www.jmir.org/2015/1/e15/ %U https://doi.org/10.2196/jmir.3830 %U http://www.ncbi.nlm.nih.gov/pubmed/25582914 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 16 %N 8 %P e193 %T How Feedback Biases Give Ineffective Medical Treatments a Good Reputation %A de Barra,Mícheál %A Eriksson,Kimmo %A Strimling,Pontus %+ Centre for the Study of Cultural Evolution, Wallenberg Laboratory, Stockholm, WC1E 7HT, Sweden, 46 7531327690, mdebarra@gmail.com %K bias %K social media %K behavioral sciences %K reputation systems %K cultural evolution %D 2014 %7 21.08.2014 %9 Original Paper %J J Med Internet Res %G English %X Background: Medical treatments with no direct effect (like homeopathy) or that cause harm (like bloodletting) are common across cultures and throughout history. How do such treatments spread and persist? Most medical treatments result in a range of outcomes: some people improve while others deteriorate. If the people who improve are more inclined to tell others about their experiences than the people who deteriorate, ineffective or even harmful treatments can maintain a good reputation. Objective: The intent of this study was to test the hypothesis that positive outcomes are overrepresented in online medical product reviews, to examine if this reputational distortion is large enough to bias people’s decisions, and to explore the implications of this bias for the cultural evolution of medical treatments. Methods: We compared outcomes of weight loss treatments and fertility treatments in clinical trials to outcomes reported in 1901 reviews on Amazon. Then, in a series of experiments, we evaluated people’s choice of weight loss diet after reading different reviews. Finally, a mathematical model was used to examine if this bias could result in less effective treatments having a better reputation than more effective treatments. Results: Data are consistent with the hypothesis that people with better outcomes are more inclined to write reviews. After 6 months on the diet, 93% (64/69) of online reviewers reported a weight loss of 10 kg or more while just 27% (19/71) of clinical trial participants experienced this level of weight change. A similar positive distortion was found in fertility treatment reviews. In a series of experiments, we show that people are more inclined to begin a diet with many positive reviews, than a diet with reviews that are representative of the diet’s true effect. A mathematical model of medical cultural evolution shows that the size of the positive distortion critically depends on the shape of the outcome distribution. Conclusions: Online reviews overestimate the benefits of medical treatments, probably because people with negative outcomes are less inclined to tell others about their experiences. This bias can enable ineffective medical treatments to maintain a good reputation. %M 25147101 %R 10.2196/jmir.3214 %U http://www.jmir.org/2014/8/e193/ %U https://doi.org/10.2196/jmir.3214 %U http://www.ncbi.nlm.nih.gov/pubmed/25147101 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 16 %N 6 %P e148 %T What Explains Usage of Mobile Physician-Rating Apps? Results From a Web-Based Questionnaire %A Bidmon,Sonja %A Terlutter,Ralf %A Röttl,Johanna %+ Department of Marketing and International Management, Alpen-Adria Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 ext 4048, sonja.bidmon@aau.at %K physician-rating apps %K physician-rating websites %K sociodemographic variables %K psychographic variables %K digital literacy %K TAM %D 2014 %7 11.06.2014 %9 Original Paper %J J Med Internet Res %G English %X Background: Consumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking. Objective: This study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage. Methods: A total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses. Results: The suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients’ value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients’ value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of using apps for health-related information in the past and attitude toward PRWs, but not the amount of daily Internet use for health-related information, were significant predictors of willingness to pay. The perceived usefulness of the Internet to gain health-related information and the amount of daily Internet use in general did not have any significant effect on both of the endogenous variables. The moderation analysis with the group comparisons for users and nonusers of PRWs revealed that the attitude toward PRWs had significantly more impact on the adoption and willingness to pay for mobile physician-rating apps in the nonuser group. Conclusions: Important variables that contribute to the adoption of a mobile physician-rating app and the willingness to pay for it were identified. The results of this study are important for researchers because they can provide important insights about the variables that influence the acceptance of apps that allow for ratings of physicians. They are also useful for creators of mobile physician-rating apps because they can help tailor mobile physician-rating apps to the consumers’ characteristics and needs. %M 24918859 %R 10.2196/jmir.3122 %U http://www.jmir.org/2014/6/e148/ %U https://doi.org/10.2196/jmir.3122 %U http://www.ncbi.nlm.nih.gov/pubmed/24918859 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 16 %N 3 %P e97 %T Who Uses Physician-Rating Websites? Differences in Sociodemographic Variables, Psychographic Variables, and Health Status of Users and Nonusers of Physician-Rating Websites %A Terlutter,Ralf %A Bidmon,Sonja %A Röttl,Johanna %+ Department of Marketing and International Management, Alpen-Adria Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 4004, ralf.terlutter@aau.at %K physician-rating websites %K sociodemographic variables %K psychographic variables %K digital literacy %D 2014 %7 31.03.2014 %9 Original Paper %J J Med Internet Res %G English %X Background: The number of physician-rating websites (PRWs) is rising rapidly, but usage is still poor. So far, there has been little discussion about what kind of variables influence usage of PRWs. Objective: We focused on sociodemographic variables, psychographic variables, and health status of PRW users and nonusers. Methods: An online survey of 1006 randomly selected German patients was conducted in September 2012. We analyzed the patients’ knowledge and use of online PRWs. We also analyzed the impact of sociodemographic variables (gender, age, and education), psychographic variables (eg, feelings toward the Internet, digital literacy), and health status on use or nonuse as well as the judgment of and behavior intentions toward PRWs. The survey instrument was based on existing literature and was guided by several research questions. Results: A total of 29.3% (289/986) of the sample knew of a PRW and 26.1% (257/986) had already used a PRW. Younger people were more prone than older ones to use PRWs (t967=2.27, P=.02). Women used them more than men (χ21=9.4, P=.002), the more highly educated more than less educated people (χ24=19.7, P=.001), and people with chronic diseases more than people without (χ21=5.6, P=.02). No differences were found between users and nonusers in their daily private Internet use and in their use of the Internet for health-related information. Users had more positive feelings about the Internet and other Web-based applications in general (t489=3.07, P=.002) than nonusers, and they had higher digital literacy (t520=4.20, P<.001). Users ascribed higher usefulness to PRWs than nonusers (t612=11.61, P<.001) and users trusted information on PRWs to a greater degree than nonusers (t559=11.48, P<.001). Users were also more likely to rate a physician on a PRW in the future (t367=7.63, P<.001) and to use a PRW in the future (t619=15.01, P<.001). The results of 2 binary logistic regression analyses demonstrated that sociodemographic variables (gender, age, education) and health status alone did not predict whether persons were prone to use PRWs or not. Adding psychographic variables and information-seeking behavior variables to the binary logistic regression analyses led to a satisfying fit of the model and revealed that higher education, poorer health status, higher digital literacy (at the 10% level of significance), lower importance of family and pharmacist for health-related information, higher trust in information on PRWs, and higher appraisal of usefulness of PRWs served as significant predictors for usage of PRWs. Conclusions: Sociodemographic variables alone do not sufficiently predict use or nonuse of PRWs; specific psychographic variables and health status need to be taken into account. The results can help designers of PRWs to better tailor their product to specific target groups, which may increase use of PRWs in the future. %M 24686918 %R 10.2196/jmir.3145 %U http://www.jmir.org/2014/3/e97/ %U https://doi.org/10.2196/jmir.3145 %U http://www.ncbi.nlm.nih.gov/pubmed/24686918 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 16 %N 2 %P e56 %T Social Media and Rating Sites as Tools to Understanding Quality of Care: A Scoping Review %A Verhoef,Lise M %A Van de Belt,Tom H %A Engelen,Lucien JLPG %A Schoonhoven,Lisette %A Kool,Rudolf B %+ IQ healthcare, Radboud University Medical Center, Route 114, Geert Grooteplein-Noord 21, Nijmegen, 6525 EZ, Netherlands, 31 243667308, Lise.Verhoef@radboudumc.nl %K social media %K rating sites %K patient experiences %K patient satisfaction %K quality of health care %D 2014 %7 20.02.2014 %9 Review %J J Med Internet Res %G English %X Background: Insight into the quality of health care is important for any stakeholder including patients, professionals, and governments. In light of a patient-centered approach, it is essential to assess the quality of health care from a patient’s perspective, which is commonly done with surveys or focus groups. Unfortunately, these “traditional” methods have significant limitations that include social desirability bias, a time lag between experience and measurement, and difficulty reaching large groups of people. Information on social media could be of value to overcoming these limitations, since these new media are easy to use and are used by the majority of the population. Furthermore, an increasing number of people share health care experiences online or rate the quality of their health care provider on physician rating sites. The question is whether this information is relevant to determining or predicting the quality of health care. Objective: The goal of our research was to systematically analyze the relation between information shared on social media and quality of care. Methods: We performed a scoping review with the following goals: (1) to map the literature on the association between social media and quality of care, (2) to identify different mechanisms of this relationship, and (3) to determine a more detailed agenda for this relatively new research area. A recognized scoping review methodology was used. We developed a search strategy based on four themes: social media, patient experience, quality, and health care. Four online scientific databases were searched, articles were screened, and data extracted. Results related to the research question were described and categorized according to type of social media. Furthermore, national and international stakeholders were consulted throughout the study, to discuss and interpret results. Results: Twenty-nine articles were included, of which 21 were concerned with health care rating sites. Several studies indicate a relationship between information on social media and quality of health care. However, some drawbacks exist, especially regarding the use of rating sites. For example, since rating is anonymous, rating values are not risk adjusted and therefore vulnerable to fraud. Also, ratings are often based on only a few reviews and are predominantly positive. Furthermore, people providing feedback on health care via social media are presumably not always representative for the patient population. Conclusions: Social media and particularly rating sites are an interesting new source of information about quality of care from the patient’s perspective. This new source should be used to complement traditional methods, since measuring quality of care via social media has other, but not less serious, limitations. Future research should explore whether social media are suitable in practice for patients, health insurers, and governments to help them judge the quality performance of professionals and organizations. %M 24566844 %R 10.2196/jmir.3024 %U http://www.jmir.org/2014/2/e56/ %U https://doi.org/10.2196/jmir.3024 %U http://www.ncbi.nlm.nih.gov/pubmed/24566844 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 15 %N 11 %P e239 %T Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online %A Greaves,Felix %A Ramirez-Cano,Daniel %A Millett,Christopher %A Darzi,Ara %A Donaldson,Liam %+ Department of Primary Care and Public Health, Imperial College London, Charing Cross Hospital, London, W6 8RF, United Kingdom, 44 7866551172, fg08@imperial.ac.uk %K Internet %K patient experience %K quality %K machine learning %D 2013 %7 01.11.2013 %9 Original Paper %J J Med Internet Res %G English %X Background: There are large amounts of unstructured, free-text information about quality of health care available on the Internet in blogs, social networks, and on physician rating websites that are not captured in a systematic way. New analytical techniques, such as sentiment analysis, may allow us to understand and use this information more effectively to improve the quality of health care. Objective: We attempted to use machine learning to understand patients’ unstructured comments about their care. We used sentiment analysis techniques to categorize online free-text comments by patients as either positive or negative descriptions of their health care. We tried to automatically predict whether a patient would recommend a hospital, whether the hospital was clean, and whether they were treated with dignity from their free-text description, compared to the patient’s own quantitative rating of their care. Methods: We applied machine learning techniques to all 6412 online comments about hospitals on the English National Health Service website in 2010 using Weka data-mining software. We also compared the results obtained from sentiment analysis with the paper-based national inpatient survey results at the hospital level using Spearman rank correlation for all 161 acute adult hospital trusts in England. Results: There was 81%, 84%, and 89% agreement between quantitative ratings of care and those derived from free-text comments using sentiment analysis for cleanliness, being treated with dignity, and overall recommendation of hospital respectively (kappa scores: .40–.74, P<.001 for all). We observed mild to moderate associations between our machine learning predictions and responses to the large patient survey for the three categories examined (Spearman rho 0.37-0.51, P<.001 for all). Conclusions: The prediction accuracy that we have achieved using this machine learning process suggests that we are able to predict, from free-text, a reasonably accurate assessment of patients’ opinion about different performance aspects of a hospital and that these machine learning predictions are associated with results of more conventional surveys. %M 24184993 %R 10.2196/jmir.2721 %U http://www.jmir.org/2013/11/e239/ %U https://doi.org/10.2196/jmir.2721 %U http://www.ncbi.nlm.nih.gov/pubmed/24184993 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 15 %N 8 %P e187 %T Physician Choice Making and Characteristics Associated With Using Physician-Rating Websites: Cross-Sectional Study %A Emmert,Martin %A Meier,Florian %A Pisch,Frank %A Sander,Uwe %+ Institute of Management (IFM), School of Business and Economics, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 902403, Germany, 49 9115302 ext 253, Martin.Emmert@wiso.uni-erlangen.de %K physician-rating website %K public reporting %K patient satisfaction %K physician choice making %D 2013 %7 28.08.2013 %9 Original Paper %J J Med Internet Res %G English %X Background: Over the past decade, physician-rating websites have been gaining attention in scientific literature and in the media. However, little knowledge is available about the awareness and the impact of using such sites on health care professionals. It also remains unclear what key predictors are associated with the knowledge and the use of physician-rating websites. Objective: To estimate the current level of awareness and use of physician-rating websites in Germany and to determine their impact on physician choice making and the key predictors which are associated with the knowledge and the use of physician-rating websites. Methods: This study was designed as a cross-sectional survey. An online panel was consulted in January 2013. A questionnaire was developed containing 28 questions; a pretest was carried out to assess the comprehension of the questionnaire. Several sociodemographic (eg, age, gender, health insurance status, Internet use) and 2 health-related independent variables (ie, health status and health care utilization) were included. Data were analyzed using descriptive statistics, chi-square tests, and t tests. Binary multivariate logistic regression models were performed for elaborating the characteristics of physician-rating website users. Results from the logistic regression are presented for both the observed and weighted sample. Results: In total, 1505 respondents (mean age 43.73 years, SD 14.39; 857/1505, 57.25% female) completed our survey. Of all respondents, 32.09% (483/1505) heard of physician-rating websites and 25.32% (381/1505) already had used a website when searching for a physician. Furthermore, 11.03% (166/1505) had already posted a rating on a physician-rating website. Approximately 65.35% (249/381) consulted a particular physician based on the ratings shown on the websites; in contrast, 52.23% (199/381) had not consulted a particular physician because of the publicly reported ratings. Significantly higher likelihoods for being aware of the websites could be demonstrated for female participants (P<.001), those who were widowed (P=.01), covered by statutory health insurance (P=.02), and with higher health care utilization (P<.001). Health care utilization was significantly associated with all dependent variables in our multivariate logistic regression models (P<.001). Furthermore, significantly higher scores could be shown for health insurance status in the unweighted and Internet use in the weighted models. Conclusions: Neither health policy makers nor physicians should underestimate the influence of physician-rating websites. They already play an important role in providing information to help patients decide on an appropriate physician. Assuming there will be a rising level of public awareness, the influence of their use will increase well into the future. Future studies should assess the impact of physician-rating websites under experimental conditions and investigate whether physician-rating websites have the potential to reflect the quality of care offered by health care providers. %M 23985220 %R 10.2196/jmir.2702 %U http://www.jmir.org/2013/8/e187/ %U https://doi.org/10.2196/jmir.2702 %U http://www.ncbi.nlm.nih.gov/pubmed/23985220 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 15 %N 8 %P e157 %T An Analysis of Online Evaluations on a Physician Rating Website: Evidence From a German Public Reporting Instrument %A Emmert,Martin %A Meier,Florian %+ Institute of Management (IFM), School of Business and Economics, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 90403, Germany, 49 911 5302 ext 253, Martin.Emmert@fau.de %K physician rating website %K public reporting %K quality of care %K Internet %K patient satisfaction %D 2013 %7 06.08.2013 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites (PRW) have been gaining in popularity among patients who are seeking a physician. However, little evidence is available on the number, distribution, or trend of evaluations on PRWs. Furthermore, there is no published evidence available that analyzes the characteristics of the patients who provide ratings on PRWs. Objective: The objective of the study was to analyze all physician evaluations that were posted on the German PRW, jameda, in 2012. Methods: Data from the German PRW, jameda, from 2012 were analyzed and contained 127,192 ratings of 53,585 physicians from 107,148 patients. Information included medical specialty and gender of the physician, age, gender, and health insurance status of the patient, as well as the results of the physician ratings. Statistical analysis was carried out using the median test and Kendall Tau-b test. Results: Thirty-seven percent of all German physicians were rated on jameda in 2012. Nearly half of those physicians were rated once, and less than 2% were rated more than ten times (mean number of ratings 2.37, SD 3.17). About one third of all rated physicians were female. Rating patients were mostly female (60%), between 30-50 years (51%) and covered by Statutory Health Insurance (83%). A mean of 1.19 evaluations per patient could be calculated (SD 0.778). Most of the rated medical specialties were orthopedists, dermatologists, and gynecologists. Two thirds of all ratings could be assigned to the best category, “very good”. Female physicians had significantly better ratings than did their male colleagues (P<.001). Additionally, significant rating differences existed between medical specialties (P<.001). It could further be shown that older patients gave better ratings than did their younger counterparts (P<.001). The same was true for patients covered by private health insurance; they gave more favorable evaluations than did patients covered by statutory health insurance (P<.001). No significant rating differences could be detected between female and male patients (P=.505). The likelihood of a good rating was shown to increase with a rising number of both physician and patient ratings. Conclusions: Our findings are mostly in line with those published for PRWs from the United States. It could be shown that most of the ratings were positive, and differences existed regarding sociodemographic characteristics of both physicians and patients. An increase in the usage of PRWs might contribute to reducing the lack of publicly available information on physician quality. However, it remains unclear whether PRWs have the potential to reflect the quality of care offered by individual health care providers. Further research should assess in more detail the motivation of patients who rate their physicians online. %M 23919987 %R 10.2196/jmir.2655 %U http://www.jmir.org/2013/8/e157/ %U https://doi.org/10.2196/jmir.2655 %U http://www.ncbi.nlm.nih.gov/pubmed/23919987 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 15 %N 7 %P e131 %T Long-Term Doctor-Patient Relationships: Patient Perspective From Online Reviews %A Detz,Alissa %A López,Andrea %A Sarkar,Urmimala %+ Center for Vulnerable Populations, Division of General Internal Medicine, University of California, San Francisco, 1001 Potrero Ave, Bldg 10, FL 3, Ward 13, San Francisco, CA, 94110, United States, 1 415 206 6962, usarkar@medsfgh.ucsf.edu %K social media %K qualitative %K primary care %D 2013 %7 02.07.2013 %9 Original Paper %J J Med Internet Res %G English %X Background: Continuity of patient care is one of the cornerstones of primary care. Objective: To examine publicly available, Internet-based reviews of adult primary care physicians, specifically written by patients who report long-term relationships with their physicians. Methods: This substudy was nested within a larger qualitative content analysis of online physician ratings. We focused on reviews reflecting an established patient-physician relationship, that is, those seeing their physicians for at least 1 year. Results: Of the 712 Internet reviews of primary care physicians, 93 reviews (13.1%) were from patients that self-identified as having a long-term relationship with their physician, 11 reviews (1.5%) commented on a first-time visit to a physician, and the remainder of reviews (85.4%) did not specify the amount of time with their physician. Analysis revealed six overarching domains: (1) personality traits or descriptors of the physician, (2) technical competence, (3) communication, (4) access to physician, (5) office staff/environment, and (6) coordination of care. Conclusions: Our analysis shows that patients who have been with their physician for at least 1 year write positive reviews on public websites and focus on physician attributes. %M 23819959 %R 10.2196/jmir.2552 %U http://www.jmir.org/2013/7/e131/ %U https://doi.org/10.2196/jmir.2552 %U http://www.ncbi.nlm.nih.gov/pubmed/23819959 %0 Journal Article %@ 1438-8871 %I Gunther Eysenbach %V 15 %N 2 %P e24 %T Eight Questions About Physician-Rating Websites: A Systematic Review %A Emmert,Martin %A Sander,Uwe %A Pisch,Frank %+ Institute of Management (IFM), School of Business and Economics, Friedrich-Alexander-University Erlangen-Nuremberg, Lange Gasse 20, Nuremberg, 90411, Germany, 49 911 5302 253 ext 253, Martin.Emmert@wiso.uni-erlangen.de %K Physician rating websites %K patient narratives %K public reporting %K transparency %K systematic review %D 2013 %7 01.02.2013 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician-rating websites are currently gaining in popularity because they increase transparency in the health care system. However, research on the characteristics and content of these portals remains limited. Objective: To identify and synthesize published evidence in peer-reviewed journals regarding frequently discussed issues about physician-rating websites. Methods: Peer-reviewed English and German language literature was searched in seven databases (Medline (via PubMed), the Cochrane Library, Business Source Complete, ABI/Inform Complete, PsycInfo, Scopus, and ISI web of knowledge) without any time constraints. Additionally, reference lists of included studies were screened to assure completeness. The following eight previously defined questions were addressed: 1) What percentage of physicians has been rated? 2) What is the average number of ratings on physician-rating websites? 3) Are there any differences among rated physicians related to socioeconomic status? 4) Are ratings more likely to be positive or negative? 5) What significance do patient narratives have? 6) How should physicians deal with physician-rating websites? 7) What major shortcomings do physician-rating websites have? 8) What recommendations can be made for further improvement of physician-rating websites? Results: Twenty-four articles published in peer-reviewed journals met our inclusion criteria. Most studies were published by US (n=13) and German (n=8) researchers; however, the focus differed considerably. The current usage of physician-rating websites is still low but is increasing. International data show that 1 out of 6 physicians has been rated, and approximately 90% of all ratings on physician-rating websites were positive. Although often a concern, we could not find any evidence of "doctor-bashing". Physicians should not ignore these websites, but rather, monitor the information available and use it for internal and ex-ternal purpose. Several shortcomings limit the significance of the results published on physician-rating websites; some recommendations to address these limitations are presented. Conclusions: Although the number of publications is still low, physician-rating websites are gaining more attention in research. But the current condition of physician-rating websites is lacking. This is the case both in the United States and in Germany. Further research is necessary to increase the quality of the websites, especially from the patients’ perspective. %M 23372115 %R 10.2196/jmir.2360 %U http://www.jmir.org/2013/2/e24/ %U https://doi.org/10.2196/jmir.2360 %U http://www.ncbi.nlm.nih.gov/pubmed/23372115 %0 Journal Article %@ 1438-8871 %I Gunther Eysenbach %V 14 %N 5 %P e146 %T Patients’ Ratings of Family Physician Practices on the Internet: Usage and Associations With Conventional Measures of Quality in the English National Health Service %A Greaves,Felix %A Pape,Utz J %A Lee,Henry %A Smith,Dianna M %A Darzi,Ara %A Majeed,Azeem %A Millett,Christopher %+ Department of Primary Care and Public Health, Imperial College London, Reynolds Building, Charing Cross Hospital, London, W6 8RP, United Kingdom, 44 7866551172, felixgreaves@gmail.com %K Patient Experience %K Primary Care %K Internet %K Quality %D 2012 %7 17.10.2012 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients are increasingly rating their family physicians on the Internet in the same way as they might rate a hotel on TripAdvisor or a seller on eBay, despite physicians’ concerns about this process. Objective: This study aims to examine the usage of NHS Choices, a government website that encourages patients to rate the quality of family practices in England, and associations between web-based patient ratings and conventional measures of patient experience and clinical quality in primary care. Methods: We obtained all (16,952) ratings of family practices posted on NHS Choices between October 2009 and December 2010. We examined associations between patient ratings and family practice and population characteristics. Associations between ratings and survey measures of patient experience and clinical outcomes were examined. Results: 61% of the 8089 family practices in England were rated, and 69% of ratings would recommend their family practice. Practices serving younger, less deprived, and more densely populated areas were more likely to be rated. There were moderate associations with survey measures of patient experience (Spearman ρ 0.37−0.48, P<.001 for all 5 variables), but only weak associations with measures of clinical process and outcome (Spearman ρ less than ±0.18, P<.001 for 6 of 7 variables). Conclusion: The frequency of patients rating their family physicians on the Internet is variable in England, but the ratings are generally positive and are moderately associated with other measures of patient experience and weakly associated with clinical quality. Although potentially flawed, patient ratings on the Internet may provide an opportunity for organizational learning and, as it becomes more common, another lens to look at the quality of primary care. %M 23076301 %R 10.2196/jmir.2280 %U http://www.jmir.org/2012/5/e146/ %U https://doi.org/10.2196/jmir.2280 %U http://www.ncbi.nlm.nih.gov/pubmed/23076301 %0 Journal Article %@ 1438-8871 %I Gunther Eysenbach %V 14 %N 3 %P e94 %T Consistently Increasing Numbers of Online Ratings of Healthcare in England %A Greaves,Felix %A Millett,Christopher %+ Department of Primary Care and Public Health, Imperial College London, Reynolds Building, Charing Cross Campus, London, W6 8RP, United Kingdom, 44 7866 551172, felix.greaves08@imperial.ac.uk %K online reviews %K quality transparency %K public reporting %D 2012 %7 29.06.2012 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 22742977 %R 10.2196/jmir.2157 %U http://www.jmir.org/2012/3/e94/ %U https://doi.org/10.2196/jmir.2157 %U http://www.ncbi.nlm.nih.gov/pubmed/22742977 %0 Journal Article %@ 1438-8871 %I Gunther Eysenbach %V 14 %N 1 %P e38 %T A Changing Landscape of Physician Quality Reporting: Analysis of Patients’ Online Ratings of Their Physicians Over a 5-Year Period %A Gao,Guodong Gordon %A McCullough,Jeffrey S %A Agarwal,Ritu %A Jha,Ashish K %+ Center for Health Information and Decision Systems, Robert H Smith School of Business, University of Maryland, 4325 Van Munching Hall, College Park, MD, 20742, United States, 1 301 405 2218, ggao@rhsmith.umd.edu %K Physician quality %K online reviews %K patient empowerment %K quality transparency %K public reporting %D 2012 %7 24.02.2012 %9 Original Paper %J J Med Internet Res %G English %X Background: Americans increasingly post and consult online physician rankings, yet we know little about this new phenomenon of public physician quality reporting. Physicians worry these rankings will become an outlet for disgruntled patients. Objective: To describe trends in patients’ online ratings over time, across specialties, to identify what physician characteristics influence online ratings, and to examine how the value of ratings reflects physician quality. Methods: We used data from RateMDs.com, which included over 386,000 national ratings from 2005 to 2010 and provided insight into the evolution of patients’ online ratings. We obtained physician demographic data from the US Department of Health and Human Services’ Area Resource File. Finally, we matched patients’ ratings with physician-level data from the Virginia Medical Board and examined the probability of being rated and resultant rating levels. Results: We estimate that 1 in 6 practicing US physicians received an online review by January 2010. Obstetrician/gynecologists were twice as likely to be rated (P < .001) as other physicians. Online reviews were generally quite positive (mean 3.93 on a scale of 1 to 5). Based on the Virginia physician population, long-time graduates were more likely to be rated, while physicians who graduated in recent years received higher average ratings (P < .001). Patients gave slightly higher ratings to board-certified physicians (P = .04), those who graduated from highly rated medical schools (P = .002), and those without malpractice claims (P = .1). Conclusion: Online physician rating is rapidly growing in popularity and becoming commonplace with no evidence that they are dominated by disgruntled patients. There exist statistically significant correlations between the value of ratings and physician experience, board certification, education, and malpractice claims, suggesting a positive correlation between online ratings and physician quality. However, the magnitude is small. The average number of ratings per physician is still low, and most rating variation reflects evaluations of punctuality and staff. Understanding whether they truly reflect better care and how they are used will be critically important. %M 22366336 %R 10.2196/jmir.2003 %U http://www.jmir.org/2012/1/e38/ %U https://doi.org/10.2196/jmir.2003 %U http://www.ncbi.nlm.nih.gov/pubmed/22366336 %0 Journal Article %@ 1438-8871 %I Gunther Eysenbach %V 13 %N 4 %P e95 %T Analysis of 4999 Online Physician Ratings Indicates That Most Patients Give Physicians a Favorable Rating %A Kadry,Bassam %A Chu,Larry F %A Kadry,Bayan %A Gammas,Danya %A Macario,Alex %+ Department of Anesthesia, School of Medicine, Stanford University, 300 Pasteur Drive, H3580, Stanford, CA, 94305, United States, 1 (650) 723 6415, bkadry@stanford.edu %K Doctor ratings %K patient satisfaction %K online physician reviews %K consumer health %K physician rating %D 2011 %7 16.11.2011 %9 Original Paper %J J Med Internet Res %G English %X Background: Many online physician-rating sites provide patients with information about physicians and allow patients to rate physicians. Understanding what information is available is important given that patients may use this information to choose a physician. Objectives: The goals of this study were to (1) determine the most frequently visited physician-rating websites with user-generated content, (2) evaluate the available information on these websites, and (3) analyze 4999 individual online ratings of physicians. Methods: On October 1, 2010, using Google Trends we identified the 10 most frequently visited online physician-rating sites with user-generated content. We then studied each site to evaluate the available information (eg, board certification, years in practice), the types of rating scales (eg, 1–5, 1–4, 1–100), and dimensions of care (eg, recommend to a friend, waiting room time) used to rate physicians. We analyzed data from 4999 selected physician ratings without identifiers to assess how physicians are rated online. Results: The 10 most commonly visited websites with user-generated content were HealthGrades.com, Vitals.com, Yelp.com, YP.com, RevolutionHealth.com, RateMD.com, Angieslist.com, Checkbook.org, Kudzu.com, and ZocDoc.com. A total of 35 different dimensions of care were rated by patients in the websites, with a median of 4.5 (mean 4.9, SD 2.8, range 1–9) questions per site. Depending on the scale used for each physician-rating website, the average rating was 77 out of 100 for sites using a 100-point scale (SD 11, median 76, range 33–100), 3.84 out of 5 (77%) for sites using a 5-point scale (SD 0.98, median 4, range 1–5), and 3.1 out of 4 (78%) for sites using a 4-point scale (SD 0.72, median 3, range 1–4). The percentage of reviews rated ≥75 on a 100-point scale was 61.5% (246/400), ≥4 on a 5-point scale was 57.74% (2078/3599), and ≥3 on a 4-point scale was 74.0% (740/1000). The patient’s single overall rating of the physician correlated with the other dimensions of care that were rated by patients for the same physician (Pearson correlation, r = .73, P < .001). Conclusions: Most patients give physicians a favorable rating on online physician-rating sites. A single overall rating to evaluate physicians may be sufficient to assess a patient’s opinion of the physician. The optimal content and rating method that is useful to patients when visiting online physician-rating sites deserves further study. Conducting a qualitative analysis to compare the quantitative ratings would help validate the rating instruments used to evaluate physicians. %M 22088924 %R 10.2196/jmir.1960 %U http://www.jmir.org/2011/4/e95/ %U https://doi.org/10.2196/jmir.1960 %U http://www.ncbi.nlm.nih.gov/pubmed/22088924