Journal of Medical Internet Research

Use of routinely recorded electronic health records (EHR) data is increasingly common, especially in epidemiological research. However, data must be processed and prepared for secondary use, and decisions made during this process could significantly impact research outcomes. A demonstration of the extent of these consequences is necessary.

Video consultations (VC) have proven to be a useful tool to enhance access to medical care for patients. During the COVID-19 pandemic, the use of VC has risen sharply. However, since (the end of) the pandemic, they have only been used to a limited extent by insured individuals in the German statutory health insurance (SHI).

Health research requires high-quality data, and population-based health research comes with specific opportunities and challenges for data collection. Electronic data capture can mitigate some of the challenges of working with large populations in multiple, sometimes difficult-to-reach, locations. This viewpoint paper aims to describe experiences during the implementation of two mixed methods studies in Vietnam, Nepal, and Indonesia, focusing on understanding lived experiences of the COVID-19 pandemic across 3 countries and understanding knowledge and behaviors related to antibiotic use in Vietnam. We present the opportunities, challenges, and solutions arising through using Research Electronic Data Capture (REDCap) for designing, collecting, and managing data. Electronic data capture using REDCap made it possible to collect data from large populations in different settings. Challenges related to working in multiple languages, unstable internet connections, and complex questionnaires with nested forms. Some data collectors lacked the digital skills to comfortably use REDCap. To overcome these challenges, we included regular team meetings, training, supervision, and automated error-checking procedures. The main types of errors that remained were incomplete and duplicate records due to disruption during data collection. However, with immediate access to data, we were able to identify and troubleshoot these problems quickly, while data collection was still in progress. By detailing our lessons learned—such as the importance of iterative testing, regular intersite meetings, and customized modifications—we provide a roadmap for future projects to boost productivity, enhance data quality, and effectively conduct large-scale population-based research. Our suggestions will be beneficial for research teams working with electronic data capture for population-based data.

With the vast development of technology and the evolving needs of patients and health care providers, electronic medical records (EMRs) have become a cornerstone for health information. However, different institutions have used different EMR systems. Our study investigates the potential benefits of implementing an integrated and common platform, known as the Next Generation Electronic Medical Record (NGEMR) in Singapore. The NGEMR allows improved data sharing between health care facilities and can promote better coordination between primary care and specialist care doctors to access patients’ records from the same database.

Stress is a key transdiagnostic factor in the onset and recurrence of psychiatric disorders. Virtual reality (VR) in mental health care, particularly virtual natural environments, shows promising results in promoting relaxation, as evidenced by tools such as VRelax. While initial studies have demonstrated the efficacy of VRelax, further implementation in routine mental health care requires a systematic exploration of its use by patients. Understanding these perspectives can help tailor VR tools to meet the needs of users better and enhance their effectiveness in clinical settings.

Over 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile health education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence chatbots provide tailored support, and a Discrete Choice Experiment can help in understanding user preferences to improve chatbot design.

Electronic prescription (EP) systems are supported by health authorities worldwide, and most European countries have started implementing or have fully implemented such systems. However, few studies have explored how EP systems affect the work of health care professionals (HCPs) across institutions and levels in health and care services.

Mesenteric malperfusion (MMP) is an uncommon but devastating complication of acute aortic dissection (AAD) that combines 2 life-threatening conditions—aortic dissection and acute mesenteric ischemia. The complex pathophysiology of MMP poses substantial diagnostic and management challenges. Currently, delayed diagnosis remains a critical contributor to poor outcomes because of the absence of reliable individualized risk assessment tools.

The success of eHealth relies on interorganizational collaboration (IOC) throughout the development, evaluation, and implementation phases of eHealth deployment. This IOC is complex, as it involves a diversity of organizations from different sectors, such as technological, academic, health care, and governmental organizations, collaborating to deploy eHealth. Between these organizations, organizational boundaries, defined as the demarcation of an organization from its environment, arise. When these boundaries are perceived as aligned and enable complementarity, IOC is facilitated. By contrast, misalignment of organizational boundaries can hinder IOC. A dialogical learning mechanism, defined as a learning process that occurs when boundaries hinder IOC, can support learning how to navigate such boundaries. However, it is difficult to determine whether and when organizational boundaries facilitate or hinder IOC, and which dialogical learning mechanisms can be used to address these challenges during eHealth deployment. Previous literature presents the barriers and facilitators of IOC during eHealth deployment only for subsets of organizations or specific phases, leaving their generic versus phase specific applicability uncharted.

The global push to scale up telemedicine services is challenged by complex, multilevel, multifaceted implementation and a lack of consensus on what the evidence-based essential building blocks of implementation are.

Medical reports, particularly radiology findings, are often written for professional communication, making them difficult for patients to understand. This communication barrier can reduce patient engagement and lead to misinterpretation. Artificial intelligence (AI), especially large language models such as ChatGPT, offers new opportunities for simplifying medical documentation to improve patient comprehension.

Social media offers promising, low-cost, and accessible ways to promote adolescent health within their daily routines. Platforms such as Instagram engage users through interactive features—including quizzes, question stickers, and polls—that encourage participation and behavior change. However, risks such as addiction potential and exposure to harmful content highlight the need for carefully designed interventions.