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Training medical students and residents in the use of electronic health records: a systematic review of the literature.

ABSTRACT: OBJECTIVE:Our objectives were to identify educational interventions designed to equip medical students or residents with knowledge or skills related to various uses of electronic health records (EHRs), summarize and synthesize the results of formal evaluations of these initiatives, and compare the aims of these initiatives with the prescribed EHR-specific competencies for undergraduate and postgraduate medical education. MATERIALS AND METHODS:We conducted a systematic review of the literature following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) guidelines. We searched for English-language, peer-reviewed studies across 6 databases using a combination of Medical Subject Headings and keywords. We summarized the quantitative and qualitative results of included studies and rated studies according to the Best Evidence in Medical Education system. RESULTS:Our search yielded 619 citations, of which 11 studies were included. Seven studies involved medical students, 3 studies involved residents, and 1 study involved both groups. All interventions used a practical component involving entering information into a simulated or prototypical EHR. None of the interventions involved extracting, aggregating, or visualizing clinical data for panels of patients or specific populations. DISCUSSION:This review reveals few high-quality initiatives focused on training learners to engage with EHRs for both individual patient care and population health improvement. In comparing these interventions with the broad set of electronic records competencies expected of matriculating physicians, critical gaps in undergraduate and postgraduate medical education remain. CONCLUSIONS:With the increasing adoption of EHRs and rise of competency-based medical education, educators should address the gaps in the training of future physicians to better prepare them to provide high quality care for their patients and communities.

SUBMITTER: Rajaram A

PROVIDER: S-EPMC7647236 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Training medical students and residents in the use of electronic health records: a systematic review of the literature.

Rajaram Akshay A Hickey Zachary Z Patel Nimesh N Newbigging Joseph J Wolfrom Brent B

Journal of the American Medical Informatics Association : JAMIA 20200101 1

<h4>Objective</h4>Our objectives were to identify educational interventions designed to equip medical students or residents with knowledge or skills related to various uses of electronic health records (EHRs), summarize and synthesize the results of formal evaluations of these initiatives, and compare the aims of these initiatives with the prescribed EHR-specific competencies for undergraduate and postgraduate medical education.<h4>Materials and methods</h4>We conducted a systematic review of th ...[more]

PMID: 31592531

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Project description:BACKGROUND:An electronic health record (EHR) is the state-of-the-art method for ensuring all data concerning a given patient are up to date for use by multidisciplinary hospital teams. Therefore, medical students need to be trained to use health information technologies within this environment from the early stages of their education. OBJECTIVE:As little is known about the effects of specific training within the medical curriculum, this study aimed to develop a course module and evaluate it to offer best practice teaching for today's students. Moreover, we looked at the acceptance of new technologies such as EHRs. METHODS:Fifth-year medical students (N=104) at the University of Tübingen took part in a standardized two-day training procedure about the advantages and risks of EHR use. After the training, students performed their own EHR entries on hypothetical patient cases in a safe practice environment. In addition, questionnaires-standardized and with open-ended questions-were administered to assess students' experiences with a new teaching module, a newly developed EHR simulator, the acceptance of the health technology, and their attitudes toward it before and after training. RESULTS:After the teaching, students rated the benefit of EHR training for medical knowledge significantly higher than before the session (mean 3.74, SD 1.05). However, they also had doubts about the long-term benefit of EHRs for multidisciplinary coworking after training (mean 1.96, SD 0.65). The special training with simulation software was rated as helpful for preparing students (88/102, 86.2%), but they still did not feel safe in all aspects of EHR. CONCLUSIONS:A specific simulated training on using EHRs helped students improve their knowledge and become more aware of the risks and challenges of such a system. Overall, students welcomed the new training module and supported the integration of EHR teaching into the medical curriculum. Further studies are needed to optimize training modules and make use of long-term feedback opportunities a simulated system offers.

Project description:Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real-world evidence for assessing device safety and tracking device-related patient outcomes over time. However, distilling this evidence remains challenging, as information is fractured across clinical notes and structured records. Modern machine learning methods for machine reading promise to unlock increasingly complex information from text, but face barriers due to their reliance on large and expensive hand-labeled training sets. To address these challenges, we developed and validated state-of-the-art deep learning methods that identify patient outcomes from clinical notes without requiring hand-labeled training data. Using hip replacements-one of the most common implantable devices-as a test case, our methods accurately extracted implant details and reports of complications and pain from electronic health records with up to 96.3% precision, 98.5% recall, and 97.4% F1, improved classification performance by 12.8-53.9% over rule-based methods, and detected over six times as many complication events compared to using structured data alone. Using these additional events to assess complication-free survivorship of different implant systems, we found significant variation between implants, including for risk of revision surgery, which could not be detected using coded data alone. Patients with revision surgeries had more hip pain mentions in the post-hip replacement, pre-revision period compared to patients with no evidence of revision surgery (mean hip pain mentions 4.97 vs. 3.23; t?=?5.14; p?<?0.001). Some implant models were associated with higher or lower rates of hip pain mentions. Our methods complement existing surveillance mechanisms by requiring orders of magnitude less hand-labeled training data, offering a scalable solution for national medical device surveillance using electronic health records.

Project description:BackgroundInformation and communication technology (ICT) has transformed the health care field worldwide. One of the main drivers of this change is the electronic health record (EHR). However, there are still open issues and challenges because the EHR usually reflects the partial view of a health care provider without the ability for patients to control or interact with their data. Furthermore, with the growth of mobile and ubiquitous computing, the number of records regarding personal health is increasing exponentially. This movement has been characterized as the Internet of Things (IoT), including the widespread development of wearable computing technology and assorted types of health-related sensors. This leads to the need for an integrated method of storing health-related data, defined as the personal health record (PHR), which could be used by health care providers and patients. This approach could combine EHRs with data gathered from sensors or other wearable computing devices. This unified view of patients' health could be shared with providers, who may not only use previous health-related records but also expand them with data resulting from their interactions. Another PHR advantage is that patients can interact with their health data, making decisions that may positively affect their health.ObjectiveThis work aimed to explore the recent literature related to PHRs by defining the taxonomy and identifying challenges and open questions. In addition, this study specifically sought to identify data types, standards, profiles, goals, methods, functions, and architecture with regard to PHRs.MethodsThe method to achieve these objectives consists of using the systematic literature review approach, which is guided by research questions using the population, intervention, comparison, outcome, and context (PICOC) criteria.ResultsAs a result, we reviewed more than 5000 scientific studies published in the last 10 years, selected the most significant approaches, and thoroughly surveyed the health care field related to PHRs. We developed an updated taxonomy and identified challenges, open questions, and current data types, related standards, main profiles, input strategies, goals, functions, and architectures of the PHR.ConclusionsAll of these results contribute to the achievement of a significant degree of coverage regarding the technology related to PHRs.

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Training medical students and residents in the use of electronic health records: a systematic review of the literature.

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Training medical students and residents in the use of electronic health records: a systematic review of the literature.

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