Mobile Applications in Clinical and Perioperative Care for Anesthesia: Narrative Review

Introduction

Mobile health (mHealth)––digital health technologies using mobile phones, tablets, and wearables to improve health outcomes––have the potential to rapidly change the face of medicine, health care, and medical education. By 2019, 81% of Americans owned a smartphone, a significant increase from 35% in 2011 [1]. Additionally, there has been an increased level of interest in using mobile apps to monitor health in the US population, with 45,028 mHealth related applications available for download in Apple’s App Store in 2019, up from 28,343 in 2015 [2]. New advances in mobile apps provide opportunities for innovative patient care, real-time data delivery, and patient-provider engagement in anesthesiology.

Previous reviews in anesthesia have discussed commercially available digital health apps provided in the Apple App Store or Google Play market [3]. This review, however, describes recent clinically tested digital health apps found in scientific literature and how these tools may be integrated into anesthesiologists’ clinical practice.

This review aimed to describe the current scope of mobile application use within anesthesiology. We classified apps found in recent scientific literature into areas of clinical functionality that were deduced from the analysis of the included studies. We also described the limitations of mobile application studies and suggested future directions.

Methods

Overview

A review was conducted to answer the following research question: What mHealth applications in anesthesiology have been described in the published literature, and what are their utility and future potential in clinical practice?

Database Search

A complete literature search was conducted with the librarian's assistance using PubMed, Scopus, and clinicaltrials.gov for articles published from January 1, 2010, through April 1, 2020. The search terms were “mobile applications” OR “mobile health” OR “digital health” OR “mobile app” OR “iOS app” OR “mHealth” OR “smartphone” AND “anesthesiology” OR “anesthesia” OR “anesthetic” OR “anesthesiology” OR “anesthesia” OR “anesthetic. The search included titles, abstracts, and keywords for all databases.

Article Selection

Title, abstract, and full text of studies were reviewed by the first author (SP), and the senior author (LR) resolved any ambiguities. Only English language studies were included. Articles were included if they examined the use of an mHealth application in the setting of anesthesia or perioperative evaluation. Studies were excluded if they explored video interventions or did not examine the feasibility or utility of the mobile app.

Data Collection and Summary

Each article was assessed by design, population characteristics, methods, area of clinical functionality, and outcomes. A qualitative analysis was then conducted to summarize the depth and breadth of mHealth apps that have been utilized within anesthesiology. Major clinical functionalities were deduced from this qualitative analysis, and each study was then classified into one of these categories. We then described the limitations of the data from these studies and provided a basis for the future direction of mHealth in the field.

Results

Our search returned 80 studies on PubMed, 141 on Scopus, and 5 studies on clinicaltrials.gov, yielding a total of 226 studies, of which 49 were duplicate studies. The titles and abstracts of the remaining 177 articles were screened. We identified 66 that meet the criteria, and their full text was reviewed, after which 29 articles were selected for a qualitative review.

Within the literature, we identified three areas of clinical functionality: patient-centered care, systems-based improvement, and medical education. Patient-centered care was further subdivided into preoperative, intraoperative, and postoperative monitoring. Certain mobile applications within systems-based improvement were also subcategorized into medication safety or adverse event reporting or guideline compliance. An overview of each study's characteristics, methods, and outcomes can be found in Table 1.

Discussion

Patient-Centered Care

Within anesthesia, the perioperative surgical home has arisen as a model that encompasses the goals of patient-centered care [33]. Mobile apps will play a large role in this area as they can directly engage patients before they arrive at the hospital and after their procedures. By providing on-the-go education, monitoring, and behavioral interventions, the anesthesia team can reduce patient anxiety preoperatively, increase communication through real-time mobile interactions perioperatively, and improve compliance with perioperative instructions.

Preoperative Interventions

Mobile apps provide an opportunity to decrease anxiety without additional sedatives in the pediatric population. Preoperative anxiety in pediatric populations is estimated to be as high as 50% [34]. Lee et al randomized 120 children between ages 1 and 10 (ASA I, II) who were undergoing elective surgery to receive intravenous midazolam (M), behavioral intervention through smartphone applications (eg, Soundtouch interactive, Pororo Sticker Book, Angry Bird) tailored to the child’s developmental status and preferences (S), or both (SM). While they found that anxiety using the modified Yale Preoperative Anxiety Scale (m-YPAS) was lower post-intervention for all three groups (M group: mean 52.8, SD 11.8 vs mean 41.0, SD 7.0; S group: mean 59.2, SD 17.6 vs mean 36.4, SD 7.3; SM group: mean 58.3, SD 17.5 vs mean 26.0, SD 3.4), the S group had lower anxiety levels relative to the M group (P<.01), and the SM group had the lowest level of anxiety (P<.01) [5].

In another randomized controlled trial (RCT) of 84 pediatric patients ages 4 to 8, the children’s median anxiety levels were lower for patients in the smartphone group (parents verbally informed of the anesthetic procedure and child received smartphone app) versus the control group (parent verbally informed about the anesthetic procedure only). The smartphone group had significantly lower m-YPAS scores compared to the control group, measured in the operating room (OR) before anesthesia induction (55.0 vs 23.4; P<.001) [4]. The ability to tailor mobile app choices to a child’s developmental stage demonstrates how mobile technology can be customizable for individual patients.

Another novel use for smartphone apps in the preoperative area is to improve dynamic communications using a centralized platform such as Listeo+. The Listeo+ app provides personalized information to patients, reminders for preoperative recommendations, and a channel for various provider communications. Listeo+ is currently being tested in a multicenter RCT to evaluate the percentage of compliance to preoperative recommendations, thereby decreasing the rate of surgery cancellations [35].

Mobile apps, such as a preoperative functional capacity app, can assist with preoperative risk assessment, even before the patient enters the health care facility. At the University of Chicago, the Step Test app integrates the Duke Activity Status Index (DASI) with the 6-minute walk test (6MWT) [6]. Step Test uses voice prompts and Apple’s CMPedometer to derive calculated step counts for the 6MWT. Rubin et al demonstrated that Step Test’s estimated steps exhibited good agreement with a research-grade pedometer in a cohort of 78 patients (intraclass correlation coefficient of 0.87; P<.001). The app facilitates efficient administration of DASI and 6MWT and provides immediate data to providers without occupying clinic staff. Future applications may include improving functional capacity through patient optimization before procedures. In summary, emerging mHealth apps demonstrate their potential to transform preoperative care by decreasing anxiety and providing coordinated, efficient care. Hopefully, in the future, providing an interface to optimize patient health status before surgery to improve outcomes.

Intraoperative Monitoring

Digital mHealth apps have also been tested as tools to enhance intraoperative monitoring. An ideal mobile app for intraoperative monitoring should be easy-to-use, accurate, noninvasive, cost-effective, and reliable. Capstesia (version 1.1.6; Galenic App SL) is an inexpensive and attractive smartphone app used to calculate pulse pressure variations (PPV) and cardiac output (CO) from a picture taken of the arterial waveform on a monitor screen. In a simulated environment comparing 408 pairs of PPV readings, Capstesia’s PPV demonstrated acceptable accuracy compared with the manual PPV if at least 3 photos of the waveform were taken (measurement error <12%). Accuracy was improved if it was averaged across 5 photos [9] but is less practical in the OR setting. Additional validation studies showed that Capstesia had a percentage of error of 20% for PPV and 13.8% for CO among 20 patients in the intensive care unit [7]. However, when the app was studied in 57 patients undergoing elective cardiac surgeries, its calculated PPV only weakly predicted fluid responsiveness (sensitivity of 73%, 95% CI 0.54-0.92, and a specificity of 74%, 95% CI 0.48-0.90) [11]. When comparing Capstesia’s PPV to stroke volume variation from an uncalibrated pulse wave analysis monitor, Joosten et al found that there was 79% overall agreement between the two, with a kappa coefficient of 0.55 [10]. These results demonstrate the promise and difficulties of creating a mobile app for real-world clinical intraoperative settings.

Digital mHealth apps have also shown promise in intraoperative neuromuscular blockade (NMB) assessment. Often, recovery of NMB is done subjectively due to the lack of accelerators [36,37] and can result in residual weakness and respiratory complications [38]. In a sample of 22 patients, Carvalho et al demonstrated a strong correlation between train-of-four ratios obtained by a standard accelerometer against an Android app used with the phone attached to the patient’s hand (R=0.98). The app also had a small mean difference (0.0004, 95% limits of agreement +/ 0.12) against standard accelerometry [8]. Thus, the digital app is a feasible way to assess NMB. However, further studies are needed to demonstrate efficacy before the widespread application of mobile apps as monitoring devices in the OR.

Postoperative Monitoring

There is an increasing focus on patient-reported outcome measures (PROM), alongside traditional biomarkers, in evaluating clinical care [39]. Mobile apps have emerged as an exciting new tool to track PROMs such as symptoms, pain, and satisfaction with health care delivery beyond the inpatient stay. Apps have been tested in clinical trials demonstrating initial feasibility and cost-effectiveness compared to the standard of care [13,15,16].

One important measure that mobile apps help track is poorly managed acute postoperative pain, which can be related to increased risk of psychological morbidity, decreased quality of life (QoL), and chronic postsurgical pain [40]. The application Pain Assessment using a Novel Digital Application (Panda) contains electronic versions of the faces pain scale revised (FPS-R) and color analog scale (CAS). Figure 1 demonstrates both the original FPS-R and the electronic version seen on the app. In a prospective study of 62 patients, the app version correlated strongly with original scores at various postoperative time points (FPS-R: r>0.93; CAS: r>0.87) [19] and was preferable to the paper version (81% of FPS-R and 76% of CAS participants). Therefore, digital apps may improve adherence to self-reported pain. Additionally, in a study of 156 adult patients undergoing procedures commonly associated with postsurgical pain, Chiu et al found that the app version of the numeric rating scale 11 pain scores were equivalent to that of the paper version when used in adult patients following emergence from anesthesia and at discharge from the postanesthesia care unit [12]. The use of Panda in both adults and pediatric patients demonstrates the app's potential to be used in a variety of patient populations.

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Another postoperative mobile app was built for patient-initiated inquiry to identify complications earlier and improve patients’ QoL after surgery. An RCT of 1027 day-surgery patients examined postoperative follow-up with a smartphone app known as recovery assessment by phone points (RAPP). The authors found that there were lower health care costs associated with smartphone app follow-up compared to standard of care follow-up (€60.69 vs €37.29; P=.008 with a mean difference of €23.66). However, after the intervention costs were included, net savings were only €4.77 per patient [13]. Patients using the RAPP also reported better global Swedish Quality of Recovery compared to patients using paper assessments on postoperative day 7 (28.23, SD 29.97 vs 34.87, SD 30.68; P<.001) and postoperative day 14 (20.12, SD 26.19 vs 21.90, SD 22.40; P=.002) [16]. The study also helped determine that most patient inquiries (62%) occurred 1 to 7 days postsurgery, most commonly related to the surgical wound (43/119, 36%) and pain (33/119, 28%) [14].

mHealth apps can also incentivize patients to improve respiratory mechanics postoperatively. The Go-breath app was tested in 42 patients who received general anesthesia undergoing a robotic or laparoscopic surgery or laparotomy to encourage the improved use of incentive spirometry (IS). Although it is a nice concept, patients who used the Go-breath app did not score statistically higher on the incentive spirometer index (frequency of IS use over two days) compared to patients who did not (113.5 vs 93.2; P=.22) [18].

Mobile apps can also provide a platform for multidisciplinary care in the postcesarean section period. For example, in a feasibility study including 15 patients of an app designed with obstetric anesthesiologists, 80% of patients used the app at least twice to self-monitor for complications and access pain control resources, thus increasing the amount of patient monitoring for common postcesarean complications and pain [17].

Systems-Based Improvement

For anesthesiologists, smartphone apps are a convenient and accessible way to improve patient safety and quality of care [41,42] through medication safety, adverse event rates, guideline adherence, and responsiveness to emergencies.

For example, immediate response to OR emergencies is of utmost importance, with patient safety and outcomes on the line. Anesthesiologists at Vanderbilt have built an extensive iOS platform known as VigiVu to improve responsiveness through real-time OR videos, vital signs, anesthetic interventions, voice and text communication, and electronic medical record access [25]. Rothman et al demonstrated the superior reliability of the app’s push notifications compared to traditional paging systems—only 0.03% of iPhone notification latencies were over 100 seconds compared to 0.6% for third-party paging latencies [28]. Similarly, anesthesiologists at the University of British Columbia developed an iPhone app, telePORT, to support team-based communication and real-time OR monitoring. Initial results showed that telePORT was successfully integrated for OR help requests (4.5 requests per day) and OR monitoring, representing 34% of app visits [22]. The use of smartphone apps in these situations increases patient safety by prioritizing emergency situations and proper resource allocation. Additionally, data collection from patient monitoring and outcomes in mobile apps can also be utilized for both quality improvement and clinical research in the future.

Medication Safety and Adverse Event Reporting

Mobile apps have also been used to increase adverse event reporting through transparent and convenient processes that help further a culture of safety and quality. An iOS and Android adverse event–reporting app was developed at the University of Chicago (see figure 1 in Rubin et al [29] for an example of the iOS interface used to report events). After implementation, median monthly reporting rates for all providers increased from 12 to 20 (P<.001), with same-day reporting increasing by 10% during the intervention period (P=.048) [29]. Similarly, apps have shown efficacy in monitoring global adverse events regarding the administration of newer drugs. Jabaley et al repurposed a calculator app (Anesthesiologist) to distribute a survey regarding adverse drug reactions associated with sugammadex administration. Using the mobile app, the investigators gathered data from 2770 anesthesia providers that had experience administering the drug across 119 countries [24], demonstrating that an app may be used for crowdsourcing and surveilling new drugs. The app survey found that anaphylaxis rates were estimated to be between 0.005%-0.098%, and 22.7% of survey responders reported witnessing any sugammadex-related adverse drug reactions such as bradycardia and incomplete reversal of NMB [24].

Finally, anesthesiologists have historically used smartphones to calculate drug dosages. Baumann et al compared the probability of administering accurate medication dosages in emergency simulations with a dosage calculator app versus without it [21]. The probability of an accurate dose administration was higher in the app group compared to the control group (94%, SD 90-97.8 vs 77.7%, SD 70.9-84.5) [21]. Apps are often used for medication conversion in the outpatient pain management setting as well. For example, there are many opioid conversion applications designed to reduce medication errors. However, these apps should be used cautiously. In a study examining 23 opioid apps, only 50% provided direct references to sources for their conversion ratios, and over 50% had no documented medical professional involvement [23]. The conversion from 1 mg of oral morphine to oral hydromorphone was statistically different between apps with medical professional involvement versus those without (0.24 vs. 0.25; P=.04), demonstrating that there may be varying degrees of reliability for these mobile apps.

Guideline Compliance

Built-in smartphone-based decision support tools can similarly improve adherence to anesthesia guidelines to reduce technical errors. Numerous reports have found that poor application of guideline standards results in worse patient safety outcomes [43-45]. However, guidelines are numerous, lengthy, and cumbersome to follow. In an RCT across eight institutions, 259 anesthesiologists completed a test requiring the application of the American Society of Regional Anesthesia and Pain Medicine (ASRA) guidelines to clinical situations. The intervention group used an electronic decision support tool, ASRA Coags, which was programmed with the latest guidelines and decision logic, and the control group used any other resource. The authors found that the intervention group had a significantly higher score on a clinical scenario knowledge test (92.4 vs 68.0; P<.001) compared to the control group [27], irrespective of training. Together, these studies show the potential for mobile apps to act as a platform for the rapid application of complex guidelines in clinical situations, potentially reducing adverse events, preventing errors, and improving the quality of care.

Mobile apps have also been developed to improve performance in high-stress situations in lieu of posters, flow charts, and checklists. For example, MAX, a handheld cognitive aid app, was used as an intervention in a RCT of 52 anesthesia residents. Results demonstrated that residents performed better technically, as rated by independent observers when using MAX in simulated crises compared to without MAX use (81.6%, SD 11.9 vs 58.6%, 10.8; P<.001). The app also improved leadership (P=.003), problem-solving (P<.001), and resource-using (P=.006) as assessed by the Ottawa Global Rating scale [26].

Medical Education

The landscape of medical education is changing from the traditional model of classroom teaching to models such as the flipped classroom and asynchronous learning. Mobile technology enables asynchronous learning—a time and location-independent learning model—with greater access to online modules, podcasts, and videos. For example, smartphone apps have now been developed for point-of-care learning of regional anesthetic procedures such as the Bier Block [30]. These apps may provide an all-in-one learning center with videos, cognitive aids, dose calculators, self-timers, and evidence-based references readily available at the learner's convenience [30]. Additionally, education apps use gamification or game-design elements to increase user motivation. Linganna et al developed EchoEducator, a mobile app with transesophageal echocardiography image-based content, and tested it against traditional intraoperative teaching amongst 18 anesthesiology residents over two weeks (please see figure 2 in Linganna et al [32] for examples of questions testing pathology and structures as well as the feedback the resident receives). The app group had a greater knowledge increase than the control group (+19.19%, 95% CI 4.14-34.24; P=.02) in an assessment based on the perioperative transesophageal echocardiography exam [32]. Residents also reported that they would recommend the app to others because of its content customizability and convenience.

Another application of mobile apps in medical education is through simulation. For example, iLarynx utilizes the iPhone’s built-in accelerometer to mimic hand movements for fiberoptic intubation. When tested in 20 novice medical students, 80% of students in the standard training group had at least one failed attempt (>120 seconds) of visualizing the carina compared to 20% of students in the iLarynx group (P=.01). There was also continued group improvement in the iLarynx group but not in the standard training group [31].

Current Obstacles and Future Directions

Despite the many functions that mobile technology could fulfill in anesthesia, various obstacles, including low patient participation, privacy and security, provider responsibility, and shifting workplace norms, ultimately impede their comprehensive integration into the clinical environment. For example, preoperative and postoperative monitoring interventions depend on patient interaction and motivation. While there are some reports of high adherence to mobile app interventions [15], other studies show a poorer response rate, especially among the elderly—a large hurdle in app development [20]. Intraoperative apps need to be assessed for ease of use, reliability, and accuracy in the OR and not distract anesthesiologists. Monitoring apps, although promising, need more clinical validation across a range of populations.

More evidence is needed to demonstrate mobile apps can meaningfully improve clinical outcomes moving forward. Large-scale, prospective studies with outcomes data are necessary to provide sufficient evidence for widespread implementation. Investigators should also consider using the mHealth evidence reporting and assessment guidelines, which address the complex nature of mobile technology research [46].

Limitations

Similar to all narrative reviews, this review is limited by the lack of appraisal criteria for included studies. Additionally, only mobile apps derived from the scientific literature have been included. Thus, there are likely mobile applications apps not studied in the literature that were omitted. We have performed a qualitative review of the search and included only studies that fit into the categories we created, thus excluding other studies.

There are additional limitations to the mHealth apps described. Many are often inadequately tested clinically, lack efficacy data, and do not adhere to standard guidelines. Similarly, there are limited guidelines and protocols on how to use the data collected by these apps, despite their potential for engaging a wide population. Future research should explore if patient engagement through smartphone apps may increase efficiency, patient satisfaction, and outcomes during the perioperative period.

Conclusion

With the rapid uptake of smartphones amongst patients and clinicians alike, mobile applications will likely play a larger role within anesthesiology in the future. mHealth apps have novel roles in improving patient care, efficiency, and intraoperative monitoring during surgery. Mobile apps have also been shown to facilitate systems-wide change by creating a culture of improving patient quality and safety. However, as the field of anesthesiology moves forward into the digital health space, demonstrating feasibility is not sufficient; clinicians must critically evaluate mobile app study protocols and rigor. Despite studies with smaller populations and simulated environments, this review still finds emerging evidence that mHealth applications have the potential to significantly improve communication between anesthesiologists, improve workflow efficiency, enhance medical education, and reduce hospitals’ costs in the perioperative arena.