Electronic Health Record Design Research Articles

User Personas for a "Better Design" of Nation-Wide EHRs Based on Thorough Expert Evaluation and Field Analysis: Modeling Users as Individuals Plus Family Members for an Enhanced Mapping of Healthcare Situations.

Electronic Health Records (EHRs) are pivotal in prevention, therapy, and care. Their design necessitates the representation of users, activities, context, and technology. Among various participative and ethnographic design methods, user personas are an effective tool for encapsulating users in the design process. Goals and methods: This research focused on the creation of user personas for the design of a nation-wide EHR, specifically the German "elektronische Patientenakte" (ePA). We employed qualitative methods, such as field analysis and expert workshops, to generate, assess, and refine a set of user personas that can cover the complexity of real-life familial care environments. We used an innovative bottom-up approach applying a whole new process for persona generation especially in the context of family management. Results: The research yielded an initial set of five personas that accurately represent fictional user types. Importantly, at least two of these personas encapsulate the unique challenges inherent in family care work. These results provide a foundation for future work, which can utilize these personas for EHR design, as well as for further evaluation and refinement.

Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review.

Through electronic health records (EHRs), musculoskeletal (MSK) therapists such as chiropractors and physical therapists, as well as occupational medicine physicians could collect data on many variables that can be traditionally challenging to collect in managing work-related musculoskeletal disorders (WMSDs). The review's objectives were to explore the extent of research using EHRs in predicting outcomes of WMSDs by MSK therapists. A systematic search was conducted in Medline, PubMed, CINAHL, and Embase. Grey literature was searched. 2156 unique papers were retrieved, of which 38 were included. Three themes were explored, the use of EHRs to predict outcomes to WMSDs, data sources for predicting outcomes to WMSDs, and adoption of standardised information for managing WMSDs. Predicting outcomes of all MSK disorders using EHRs has been researched in 6 studies, with only 3 focusing on MSK therapists and 4 addressing WMSDs. Similar to all secondary data source research, the challenges include data quality, missing data and unstructured data. There is not yet a standardised or minimum set of data that has been defined for MSK therapists to collect when managing WMSD. Further work based on existing frameworks is required to reduce the documentation burden and increase usability. The review outlines the limited research on using EHRs to predict outcomes of WMSDs. It highlights the need for EHR design to address data quality issues and develop a standardised data set in occupational healthcare that includes known factors that potentially predict outcomes to help regulators, research efforts, and practitioners make better informed clinical decisions.

Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters.

Electronic health record (EHR) user interface event logs are fast providing another perspective on the value and efficiency EHR technology brings to health care. Analysis of these detailed usage data has demonstrated their potential to identify EHR and clinical process design factors related to user efficiency, satisfaction, and burnout. This study aimed to analyze the event log data across 26 different health systems to determine the variability of use of a single vendor's EHR based on four event log metrics, at the individual, practice group, and health system levels. We obtained de-identified event log data recorded from June 1, 2018, to May 31, 2019, from 26 health systems' primary care physicians. We estimated the variability in total Active EHR Time, Documentation Time, Chart Review Time, and Ordering Time across health systems, practice groups, and individual physicians. In total, 5,444 physicians (Family Medicine: 3,042 and Internal Medicine: 2,422) provided care in a total of 2,285 different practices nested in 26 health systems. Health systems explain 1.29, 3.55, 3.45, and 3.30% of the total variability in Active Time, Documentation Time, Chart Review Time, and Ordering Time, respectively. Practice-level variability was estimated to be 7.96, 13.52, 8.39, and 5.57%, respectively, and individual physicians explained the largest proportion of the variability for those same outcomes 17.09, 27.49, 17.51, and 19.75%, respectively. The most variable physician EHR usage patterns occurs at the individual physician level and decreases as you move up to the practice and health system levels. This suggests that interventions to improve individual users' EHR usage efficiency may have the most potential impact compared with those directed at health system or practice levels.

The relationship between perceptions of electronic health record usability and clinical importance of social and environmental determinants of health on provider documentation.

Social and environmental determinants of health (SEDH) data in the electronic health record (EHR) can be inaccurate and incomplete. Providers are in a unique position to impact this issue as they both obtain and enter this data, however, the variability in screening and documentation practices currently limits the ability to mobilize SEDH data for secondary uses. This study explores whether providers' perceptions of clinical importance of SEDH or EHR usability influenced data entry by analyzing two relationships: (1) provider charting behavior and clinical consideration of SEDH and (2) provider charting behavior and ease of EHR use in charting. We performed a cross-sectional study using an 11-question electronic survey to assess self-reported practices related to clinical consideration of SEDH elements, EHR usability and SEDH documentation of all staff physicians, identified using administrative listserves, at Penn State Health Hershey Medical Center during September to October 2021. A total of 201 physicians responded to and completed the survey out of a possible 2,478 identified staff physicians (8.1% response rate). A five-point Likert scale from "never" to "always" assessed charting behavior and clinical consideration. Responses were dichotomized as consistent/inconsistent and vital/not vital respectively. EHR usability was assessed as "yes" or "no" responses. Fisher's exact tests assessed the relationship between charting behavior and clinical consideration and to compare charting practices between different SEDHs. Cumulative measures were constructed for consistent charting and ease of charting. A generalized linear mixed model (GLMM) compared SDH and EDH with respect to each cumulative measure and was quantified using odds ratios (OR) and 95% confidence intervals (CI). Our results show that provider documentation frequency of an SEDH is associated with perceived clinical utility as well as ease of charting and that providers were more likely to consistently chart on SDH versus EDH. Nuances in these relationships did exist with one notable example comparing the results of smoking (SDH) to infectious disease outbreaks (EDH). Despite similar percentages of physicians reporting that both smoking and infectious disease outbreaks are vital to care, differences in charting consistency and ease of charting between these two were seen. Taken as a whole, our results suggest that SEDH quality optimization efforts cannot consider physician perceptions and EHR usability as siloed entities and that EHR design should not be the only target for intervention. The associations found in this study provide a starting point to understand the complexity in how clinical utility and EHR usability influence charting consistency of each SEDH element, however, further research is needed to understand how these relationships intersect at various levels in the SEDH data optimization process.

1190. Nudging Away from Alert Fatigue: A Novel Method for Tracking the Impact of Integrated Clinical Decision Support on Meropenem Order Rates

Abstract Background The electronic health record (EHR) has streamlined quality of care and hospital prescribing; however, interruptive alerts and hard restrictions on antibiotic ordering can disrupt clinical workflow, often without significant benefit. This study aimed to determine the impact of permissive restriction on meropenem orders with embedded clinical decision support and prescriber attestation. Methods A quality improvement intervention implemented at Maine Medical Center (MMC, a 700-bed academic medical center) was evaluated through a multisite, quasiexperimental study within MaineHealth Hospitals. The intervention consisted of a provider-facing summary of guideline-directed indications for empiric and culture-directed uses of meropenem attached alongside the EHR order, and a required attestation button. To track meropenem order rates for adult patients prior to (Oct – Dec 2022) and after (Jan – Mar 2023) the intervention, the EHR was configured to fire a “silent” Best Practice Advisory behind-the-scenes when a provider opened the meropenem order. Rates of ordering were also monitored at other sites in MaineHealth, where the intervention was not implemented. The primary endpoint was the rate of “back-out” events, defined as a prescriber beginning a meropenem order but not signing it, and the secondary endpoint was the meropenem administration rate within 24 hours of opening an order. Results A meropenem order was initiated in 824 unique encounters during the study period; following the intervention at MMC, the back-out rate for orders increased from 20.3% (n =291) to 32.7% (n= 147, p = .01), while there was no significant difference during the same period at institutions where the intervention was not implemented (Table 1). The rate of patients who received meropenem within 24 hours following an order being opened decreased from 90.0% pre-intervention to 74.8% post-intervention (p < 0.01). Conclusion This study suggests that simple, non-resource intensive antimicrobial stewardship ‘nudges’ can simultaneously be implemented and monitored through creative EHR design, leading to a reduction in overall completion of meropenem orders and a decrease in inappropriate antibiotic prescribing. Similar interventions can be implemented in all fields of healthcare stewardship. Disclosures All Authors: No reported disclosures

Optimizing electronic blood ordering and supporting administration workflows to improve blood utilization in the pediatric hospital setting.

Red blood cell wastage occurs when blood is discarded rather than transfused, and ineffective ordering results in unnecessary crossmatch procedures. We describe how a multimodal approach to redesigning electronic ordering tools improved blood utilization in a pediatric inpatient setting and how using innovative application of time series data analysis provides insights into intervention effectiveness, which can guide future process improvement cycles. A multidisciplinary team used best practices and Toyota Production System methodology to redesign electronic blood ordering and improve administration processes. We analyzed crossmatch to transfusion ratio and red blood cell wastage time series data extracted from our laboratory information system and electronic health record. We used changepoint analysis to identify statistically discernible breaks in each time series, compatible with known interventions. We performed causal impact analysis on red blood cell wastage time series data to estimate blood wastage avoided due to the interventions. Changepoint analysis estimated an 11% decrease in crossmatch to transfusion ratio and a 77% decrease in red blood cell monthly wastage rate during the intervention period. Causal impact analysis estimated a 61% reduction in expected wastage compared to the scenario if the interventions had not occurred. Our results show that electronic health record design is an important factor in reducing waste and preventing unnecessary crossmatching, and that time series analysis can be a useful tool for evaluating the long-term impact of each stage of intervention in a longitudinal process redesign effort for the purpose of effectively targeting future improvement efforts.

The Impact of Documentation Workflow on the Accuracy of the Coded Diagnoses in the Electronic Health Record

To determine the impact of documentation workflow on the accuracy of coded diagnoses in electronic health records (EHRs). Cross-sectional study. All patients who completed visits at the Casey Eye Institute Retina Division faculty clinic between April 7, 2022 and April 13,2022. Agreement between coded diagnoses and clinical notes. We assessed the rate of agreement between the diagnoses in the clinical notes and the coded diagnosis in the EHR using manual review and examined the impact of the documentation workflow on the rate of agreement in an academic retina practice. In 202 visits by 8 physicians, 78% (range, 22%-100%) had an agreement between the coded diagnoses and the clinical notes. When physicians integrated the diagnosis code entry and note composition, the rate of agreement was 87.9% (range, 62%-100%). For those who entered the diagnosis codes separately from writing notes, the agreement was 44.4% (22%-50%, P < 0.0001). The visit-specific agreement between the coded diagnosis and the progress note can vary widely by workflow. The workflow and EHR design may be an important part of understanding and improving the quality of EHR data. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Common contributing factors of diagnostic error: A retrospective analysis of 109 serious adverse event reports from Dutch hospitals

IntroductionAlthough diagnostic errors have gained renewed focus within the patient safety domain, measuring them remains a challenge. They are often measured using methods that lack information on decision-making processes given...

A guide to mitigating audit log-related risk in medical professional liability cases.

Following the American Recovery and Reinvestment Act in 2009, use of electronic health records (EHRs) has become ubiquitous. Accordingly, one should expect most medical professional liability cases to involve review of patient records produced from EHRs. When questions arise regarding who was involved in care of a patient, what they knew and when, or the meaning, completeness, integrity, validity, timeliness, confidentiality, accuracy, or legitimacy of data, or ways that the EHR's user interface or automated clinical decision support tools may have contributed to the alleged events, one often turns to the EHR and its audit log. This manuscript discusses lines of defense incorporated into the design, development, implementation, and use of EHRs to ensure their integrity and the types of EHR transaction logs (e.g., audit log) that exist. Using these logs can help one answer questions that often arise in medical malpractice cases. Finally, there are "best practices" surrounding EHR audit logs that health care organizations should implement. When used appropriately, EHRs and their audit logs provide another source of information to help hospital risk managers, legal counsel, and EHR expert witnesses to investigate adverse incidents and, if needed, prosecute or defend clinicians and/or health care organizations involved in the patient's care.

Involving Health Care Professionals in the Development of Electronic Health Records: Scoping Review.

Electronic health records (EHRs) are a promising approach to document and map (complex) health information gathered in health care worldwide. However, possible unintended consequences during use, which can occur owing to low usability or the lack of adaption to existing workflows (eg, high cognitive load), may pose a challenge. To prevent this, the involvement of users in the development of EHRs is crucial and growing. Overall, involvement is designed to be very multifaceted, for example, in terms of the timing, frequency, or even methods used to capture user preferences. Setting, users and their needs, and the context and practice of health care must be considered in the design and subsequent implementation of EHRs. Many different approaches to user involvement exist, each requiring a variety of methodological choices. The aim of the study was to provide an overview of the existing forms of user involvement and the circumstances they need and to provide support for the planning of new involvement processes. We conducted a scoping review to provide a database for future projects on which design of inclusion is worthwhile and to show the diversity of reporting. Using a very broad search string, we searched the PubMed, CINAHL, and Scopus databases. In addition, we searched Google Scholar. Hits were screened according to scoping review methodology and then examined, focusing on methods and materials, participants, frequency and design of the development, and competencies of the researchers involved. In total, 70 articles were included in the final analysis. There was a wide range of methods of involvement. Physicians and nurses were the most frequently included groups and, in most cases, were involved only once in the process. The approach of involvement (eg, co-design) was not specified in most of the studies (44/70, 63%). Further qualitative deficiencies in the reporting were evident in the presentation of the competences of members of the research and development teams. Think-aloud sessions, interviews, and prototypes were frequently used. This review provides insights into the diversity of health care professionals' involvement in the development of EHRs. It provides an overview of the different approaches in various fields of health care. However, it also shows the necessity of considering quality standards in the development of EHRs together with future users and the need for reporting this in future studies.

Informing Visual Display Design of Electronic Health Records: A Human Factors Cross-Industry Perspective

Background Despite their prevalence, poorly designed electronic health records (EHRs) are common, and research shows poor design consequences include clinician burnout, diagnostic error, and even patient harm. One of the major difficulties of EHR design is the visual display of information, which aims to present information in an easily digestible form for the user. High-risk industries like aviation, automotive, and nuclear have guidelines for visual displays based on human factors principles for optimized design. Purpose In this study, we reviewed the visual display guidelines from three high-risk industries—automotive, aviation, nuclear—for their applicability to EHR design and safety. Methods Human factors experts extracted guidelines related to visual displays from automotive, aviation, and nuclear human factors guideline documents. Human factors experts and a clinical expert excluded guidelines irrelevant to EHR. Human factors experts used a modified reflexive thematic analysis to group guidelines into meaningful topics. Disagreements were discussed until a consensus was reached. Results A total of 449 guidelines were extracted from the industry documents, and 283 (63.0%) were deemed relevant to EHRs. By industry, 12 of 44 (27.3%) automotive industry guidelines were relevant, 43 of 115 (37.4%) aviation industry guidelines were relevant, and 228 of 290 (78.6%) nuclear industry guidelines were relevant. Guidelines were grouped into six categories: alphanumeric; color, brightness, contrast, and luminance; comprehension; design characteristics; symbols, pictograms, and icons; and tables, figures, charts, and lists. Conclusion Our analysis identified visual display guidelines organized around six topics from the automotive, aviation, and nuclear industries to inform EHR design. Multiple stakeholders, including EHR vendors, healthcare facilities, and policymakers, can apply these guidelines to design new EHRs and optimize EHRs already in use.

Online Supplement to “Informing Visual Display Design of Electronic Health Records: A Human Factors Cross-Industry Perspective”

This supplementary material has been provided by the authors to give readers additional information about their work.

City‐wide medication use process standardization and implementation of intravenous patient‐controlled analgesia consensus recommendations at an academic medical center

AbstractIntroductionIndianapolis Coalition for Patient Safety, Inc. (ICPS) identified practice variation across participating health‐systems related to intravenous Patient‐Controlled Analgesia (PCA) in 2018. No evidence‐based published recommendations were available to provide optimization for the medication use process during this evaluation, leading to development of an ad hoc interdisciplinary group to address gaps.ObjectivesPrimary objectives were to operationalize safe use of PCA and evaluate implementation of ICPS PCA consensus recommendations at an academic medical center by assessing PCA prescribing patterns following policy and electronic health record (EHR) changes. Secondary objectives focused on markers of adoption changes and employee engagement.MethodsICPS formed an interdisciplinary, diverse group of content experts representing six health‐systems to review current PCA processes. Significant variations were identified, and a gap‐analysis was completed to develop consensus recommendations. To evaluate implementation of these recommendations, a retrospective pre‐/post‐analysis was completed of patients at a safety‐net, academic medical center from March 2021 to July 2022 who received an order for PCA. Prescribing patterns and electronic documentation were analyzed.ResultsThe ICPS PCA Safety Summit developed 45 consensus recommendations addressing the following PCA medication use processes: ordering, patient assessment, administration, EHR design, documentation tools, smart pump drug library settings, policies, adverse event monitoring, and education. Evaluation included a total of 155 patients. The ordered total number of morphine milligram equivalent (MME) potentially available per day to a patient from PCA, electronic documentation of opioid tolerance, and PCA smart infusion pump review all significantly improved post‐implementation.ConclusionCity‐wide standardization and development of PCA consensus guidelines filled a gap in practice to provide direction and optimization for the medication use process surrounding these high‐alert medications. Organizational results following implementation provide evidence that using new EHR order sets and incorporating opioid tolerance resulted in more intentional PCA prescribing and more thorough electronic nursing documentation.

Equity and bias in electronic health records data

Embedded pragmatic clinical trials (ePCTs) are conducted during routine clinical care and have the potential to increase knowledge about the effectiveness of interventions under real world conditions. However, many pragmatic trials rely on data from the electronic health record (EHR) data, which are subject to bias from incomplete data, poor data quality, lack of representation from people who are medically underserved, and implicit bias in EHR design. This commentary examines how the use of EHR data might exacerbate bias and potentially increase health inequities. We offer recommendations for how to increase generalizability of ePCT results and begin to mitigate bias to promote health equity.

Eliciting Insights From Chat Logs of the 25X5 Symposium to Reduce Documentation Burden: Novel Application of Topic Modeling.

Addressing clinician documentation burden through "targeted solutions" is a growing priority for many organizations ranging from government and academia to industry. Between January and February 2021, the 25 by 5: Symposium to Reduce Documentation Burden on US Clinicians by 75% (25X5 Symposium) convened across 2 weekly 2-hour sessions among experts and stakeholders to generate actionable goals for reducing clinician documentation over the next 5 years. Throughout this web-based symposium, we passively collected attendees' contributions to a chat functionality-with their knowledge that the content would be deidentified and made publicly available. This presented a novel opportunity to synthesize and understand participants' perceptions and interests from chat messages. We performed a content analysis of 25X5 Symposium chat logs to identify themes about reducing clinician documentation burden. The objective of this study was to explore unstructured chat log content from the web-based 25X5 Symposium to elicit latent insights on clinician documentation burden among clinicians, health care leaders, and other stakeholders using topic modeling. Across the 6 sessions, we captured 1787 messages among 167 unique chat participants cumulatively; 14 were private messages not included in the analysis. We implemented a latent Dirichlet allocation (LDA) topic model on the aggregated dataset to identify clinician documentation burden topics mentioned in the chat logs. Coherence scores and manual examination informed optimal model selection. Next, 5 domain experts independently and qualitatively assigned descriptive labels to model-identified topics and classified them into higher-level categories, which were finalized through a panel consensus. We uncovered ten topics using the LDA model: (1) determining data and documentation needs (422/1773, 23.8%); (2) collectively reassessing documentation requirements in electronic health records (EHRs) (252/1773, 14.2%); (3) focusing documentation on patient narrative (162/1773, 9.1%); (4) documentation that adds value (147/1773, 8.3%); (5) regulatory impact on clinician burden (142/1773, 8%); (6) improved EHR user interface and design (128/1773, 7.2%); (7) addressing poor usability (122/1773, 6.9%); (8) sharing 25X5 Symposium resources (122/1773, 6.9%); (9) capturing data related to clinician practice (113/1773, 6.4%); and (10) the role of quality measures and technology in burnout (110/1773, 6.2%). Among these 10 topics, 5 high-level categories emerged: consensus building (821/1773, 46.3%), burden sources (365/1773, 20.6%), EHR design (250/1773, 14.1%), patient-centered care (162/1773, 9.1%), and symposium comments (122/1773, 6.9%). We conducted a topic modeling analysis on 25X5 Symposium multiparticipant chat logs to explore the feasibility of this novel application and elicit additional insights on clinician documentation burden among attendees. Based on the results of our LDA analysis, consensus building, burden sources, EHR design, and patient-centered care may be important themes to consider when addressing clinician documentation burden. Our findings demonstrate the value of topic modeling in discovering topics associated with clinician documentation burden using unstructured textual content. Topic modeling may be a suitable approach to examine latent themes presented in web-based symposium chat logs.

Examining Pediatric Resident Electronic Health Records Use During Prerounding: Mixed Methods Observational Study

Electronic health records (EHRs) play a substantial role in modern health care, especially during prerounding, when residents gather patient information to inform daily care decisions of the care team. The effective use of the EHR system is crucial for efficient and frustration-free prerounding. Ideally, the system should be designed to support efficient user interactions by presenting data effectively and providing easy navigation between different pages. Additionally, training on the system should aim to make user interactions more efficient by familiarizing the users with best practices that minimize interaction time while using the full potential of the system's capabilities. However, formal training on EHR systems often falls short of providing residents with all the necessary EHR-related skills, leading to the adoption of inefficient practices and the underuse of the system's full range of capabilities. This study aims to examine the efficiency of EHR use during prerounding among pediatric residents, assess the effect of experience level on EHR use, and identify areas for improvement in EHR design and training. A mixed methods approach was used, involving a self-reported survey and video analysis of prerounding practices of the entire population of pediatric residents from a large teaching hospital in the South Atlantic Region. The residents were stratified by experience level by postgraduate year. Data were collected on the number of pages accessed, duration of prerounding, task completion rates, and effective use of data sources. Observational and qualitative data complemented the quantitative analysis. Our study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guidelines, ensuring completeness and transparency of reporting. Of the 30 pediatric residents, 20 were included in the analyses; of these, 16 (80%) missed at least 1 step during prerounding. Although more experienced residents on average omitted fewer steps, 4 (57%) of the 7 most experienced residents still omitted at least 1 step. On average, residents took 6.5 minutes to round each patient and accessed 21 pages within the EHR during prerounding; no statistically significant differences were observed between experience levels for prerounding times (P=.48) or number of pages accessed (P=.92). The use of aggregated data pages within the EHR system neither seem to improve prerounding times nor decrease the number of pages accessed. The findings suggest that EHR design should be improved to better support user needs, and hospitals should adopt more effective training programs to familiarize residents with the system's capabilities. We recommend implementing prerounding checklists and providing ongoing EHR training programs for health care practitioners. Despite the generalizability of limitations of our study in terms of sample size and specialization, it offers valuable insights for future research to investigate the impact of EHR use on patient outcomes and satisfaction, as well as identify factors that contribute to efficient and effective EHR usage.

Using Clinical Data Visualizations in Electronic Health Record User Interfaces to Enhance Medical Student Diagnostic Reasoning: Randomized Experiment.

In medicine, the clinical decision-making process can be described using the dual-process theory consisting of the fast, intuitive "System 1," commonly seen in seasoned physicians, and the slow, deliberative "System 2," associated with medical students. System-1-type diagnostic reasoning is thought to be less cognitively burdensome, thereby reducing physician error. To date, limited literature exists on inducing System-1-type diagnosis in medical students through cognitive heuristics, particularly while using modern electronic health record (EHR) interfaces. In this experimental pilot study, we aimed to (1) attempt to induce System-1-type diagnostic reasoning in inexperienced medical students through the acquisition of cognitive user interface heuristics and (2) understand the impact of clinical patient data visualizations on students' cognitive load and medical education. The participants were third- and fourth-year medical students recruited from the University of Pittsburgh School of Medicine who had completed 1+ clinical rotations. The students were presented 8 patient cases on a novel EHR, featuring a prominent data visualization designed to foster at-a-glance rapid case assessment, and asked to diagnose the patient. Half of the participants were shown 4 of the 8 cases repeatedly, up to 4 times with 30 seconds per case (Group A), and the other half of the participants were shown cases twice with 2 minutes per case (Group B). All participants were then asked to provide full diagnoses of all 8 cases. Finally, the participants were asked to evaluate and elaborate on their experience with the system; content analysis was subsequently performed on these user experience interviews. A total of 15 students participated. The participants in Group A scored slightly higher on average than those in Group B, with a mean percentage correct of 76% (95% CI 0.68-0.84) versus 69% (95% CI 0.58-0.80), and spent on average 50% less time per question than Group B diagnosing patients (13.98 seconds vs 19.13 seconds, P=.03, respectively). When comparing the novel EHR design to previously used EHRs, 73% (n=11) of participants rated the new version on par or higher (3+/5). Ease of use and intuitiveness of this new system rated similarly high (mean score 3.73/5 and 4.2/5, respectively). In qualitative thematic analysis of poststudy interviews, most participants (n=11, 73%) spoke to "pattern-recognition" cognitive heuristic strategies consistent with System 1 decision-making. These results support the possibility of inducing type-1 diagnostics in learners and the potential for data visualization and user design heuristics to reduce cognitive burden in clinical settings. Clinical data presentation in the diagnostic reasoning process is ripe for innovation, and further research is needed to explore the benefit of using such visualizations in medical education.

Identifying a Clinical Informatics or Electronic Health Record Expert Witness for Medical Professional Liability Cases.

The health care field is experiencing widespread electronic health record (EHR) adoption. New medical professional liability (i.e., malpractice) cases will likely involve the review of data extracted from EHRs as well as EHR workflows, audit logs, and even the potential role of the EHR in causing harm. Reviewing printed versions of a patient's EHRs can be difficult due to differences in printed versus on-screen presentations, redundancies, and the way printouts are often grouped by document or information type rather than chronologically. Simply recreating an accurate timeline often requires experts with training and experience in designing, developing, using, and reviewing EHRs and audit logs. Additional expertise is required if questions arise about data's meaning, completeness, accuracy, and timeliness or ways that the EHR's user interface or automated clinical decision support tools may have contributed to alleged events. Such experts often come from the sociotechnical field of clinical informatics that studies the design, development, implementation, use, and evaluation of information and communications technology, specifically, EHRs. Identifying well-qualified EHR experts to aid a legal team is challenging. Based on literature review and experience reviewing cases, we identified seven criteria to help in this assessment. The criteria are education in clinical informatics; clinical informatics knowledge; experience with EHR design, development, implementation, and use; communication skills; academic publications on clinical informatics; clinical informatics certification; and membership in informatics-related professional organizations. While none of these criteria are essential, understanding the breadth and depth of an individual's qualifications in each of these areas can help identify a high-quality, clinical informatics expert witness.

Measurement and automation of workflows for improved clinician interaction: upgrading EHRs for 21st century healthcare value.

In this editorial, we highlight 5 manuscripts that address aspects of clinician interaction with the electronic health record (EHR). A Perspective describes the efforts of the Office of the National Coordinator for Health Information Technology (ONC) in establishing priorities for workflow automation in healthcare settings.1 A second Perspective summarizes a panel sponsored by the American College of Medical Informatics (ACMI) at the 2021 AMIA Symposium that examined a provocative question: Are EHRs dumbing down clinicians?2 Three manuscripts focus on what can be learned from EHR audit log data.3–5 First, Zayas-Cabán et al1 describe how the ONC led a multidisciplinary effort of stakeholders from industrial engineering, computer science, and finance to investigate automation in health care. They define automation as “the creation and application of technology to monitor and control the delivery of products and services.”6 The process of key informant interviews, focus groups, and a review of pertinent literature identified 6 priorities and their related strategies for advancing workflow automation. These priorities focused on leveraging high quality, interoperable data, and engaging clinicians in the EHR design, implementation, and evaluation processes. Then, relevant, and effective workflows could be identified that add value, not a burden, in clinician processes. The supporting strategies revolved around education, convening multiple interested parties, prioritizing appropriate workflows, and using policies and the market to incentivize automated solutions' development, testing, and evaluation. Examples of priority workflows for automation include reimbursement and prior authorizations, medication reconciliation, care management for newly diagnosed patients, and public health and adverse event reporting. The goal is to upgrade EHR technology to increase efficiency, improve health outcomes, and deliver more value for patients, caregivers, clinicians, and staff involved in healthcare. These priorities and strategies provide some solutions to the inadequacies of EHRs as outlined by Melton et al.2

Electronic Health Records That Support Health Professional Reflective Practice: a Missed Opportunity in Digital Health

A foundational component of digital health involves collecting and leveraging electronic health data to improve health and wellbeing. One of the central technologies for collecting these data are electronic health records (EHRs). In this commentary, the authors explore intersection between digital health and data-driven reflective practice that is described, including an overview of the role of EHRs underpinning technology innovation in healthcare. Subsequently, they argue that EHRs are a rich but under-utilised source of information on the performance of health professionals and healthcare teams that could be harnessed to support reflective practice and behaviour change. EHRs currently act as systems of data collection, not systems of data engagement and reflection by end users such as health professionals and healthcare organisations. Further consideration should be given to supporting reflective practice by health professionals in the design of EHRs and other clinical information systems.