Novel Nonproprietary Measures of Ambulatory Electronic Health Record Use Associated with Physician Work Exhaustion

Background  Accumulating evidence indicates an association between physician electronic health record (EHR) use after work hours and occupational distress including burnout. These studies are based on either physician perception of time spent in EHR through surveys which may be prone to bias or by utilizing vendor-defined EHR use measures which often rely on proprietary algorithms that may not take into account variation in physician''s schedules which may underestimate time spent on the EHR outside of scheduled clinic time. The Stanford team developed and refined a nonproprietary EHR use algorithm to track the number of hours a physician spends logged into the EHR and calculates the Clinician Logged-in Outside Clinic (CLOC) time, the number of hours spent by a physician on the EHR outside of allocated time for patient care. Objective  The objective of our study was to measure the association between CLOC metrics and validated measures of physician burnout and professional fulfillment. Methods  Physicians from adult outpatient Internal Medicine, Neurology, Dermatology, Hematology, Oncology, Rheumatology, and Endocrinology departments who logged more than 8 hours of scheduled clinic time per week and answered the annual wellness survey administered in Spring 2019 were included in the analysis. Results  We observed a statistically significant positive correlation between CLOC ratio (defined as the ratio of CLOC time to allocated time for patient care) and work exhaustion (Pearson''s r  = 0.14; p  = 0.04), but not interpersonal disengagement, burnout, or professional fulfillment. Conclusion  The CLOC metrics are potential objective EHR activity-based markers associated with physician work exhaustion. Our results suggest that the impact of time spent on EHR, while associated with exhaustion, does not appear to be a dominant factor driving the high rates of occupational burnout in physicians.     

Interaction Time with Electronic Health Records: A Systematic Review

Background  The amount of time that health care clinicians (physicians and nurses) spend interacting with the electronic health record is not well understood. Objective  This study aimed to evaluate the time that health care providers spend interacting with electronic health records (EHR). Methods  Data are retrieved from Ovid MEDLINE(R) and Epub Ahead of Print, In-Process and Other Non-Indexed Citations and Daily, (Ovid) Embase, CINAHL, and SCOPUS. Study Eligibility Criteria  Peer-reviewed studies that describe the use of EHR and include measurement of time either in hours, minutes, or in the percentage of a clinician''s workday. Papers were written in English and published between 1990 and 2021. Participants  All physicians and nurses involved in inpatient and outpatient settings. Study Appraisal and Synthesis Methods  A narrative synthesis of the results, providing summaries of interaction time with EHR. The studies were rated according to Quality Assessment Tool for Studies with Diverse Designs. Results  Out of 5,133 de-duplicated references identified through database searching, 18 met inclusion criteria. Most were time-motion studies (50%) that followed by logged-based analysis (44%). Most were conducted in the United States (94%) and examined a clinician workflow in the inpatient settings (83%). The average time was nearly 37% of time of their workday by physicians in both inpatient and outpatient settings and 22% of the workday by nurses in inpatient settings. The studies showed methodological heterogeneity. Conclusion  This systematic review evaluates the time that health care providers spend interacting with EHR. Interaction time with EHR varies depending on clinicians'' roles and clinical settings, computer systems, and users'' experience. The average time spent by physicians on EHR exceeded one-third of their workday. The finding is a possible indicator that the EHR has room for usability, functionality improvement, and workflow optimization.     

Defining Data Migration Across Multidisciplinary Ambulatory Clinics Using Participatory Design

Objective  This study aimed to develop an institutional approach for defining data migration based on participatory design principles. Methods  We outline a collaborative approach to define data migration as part of an electronic health record (EHR) transition at an urban hospital with 20 ambulatory clinics, based on participatory design. We developed an institution-specific list of data for migration based on physician end-user feedback. In this paper, we review the project planning phases, multidisciplinary governance, and methods used. Results  Detailed data migration feedback was obtained from 90% of participants. Depending on the specialty, requests for historical laboratory values ranged from 2 to as many as 145 unique laboratory types. Lookback periods requested by physicians varied and were ultimately assigned to provide the most clinical data. This clinical information was then combined to synthesize an overall proposed data migration request on behalf of the institution. Conclusion  Institutions undergoing an EHR transition should actively involve physician end-users and key stakeholders. Physician feedback is vital for developing a clinically relevant EHR environment but is often difficult to obtain. Challenges include physician time constraints and overall knowledge about health information technology. This study demonstrates how a participatory design can serve to improve the clinical end-user''s understanding of the technical aspects of an EHR implementation, as well as enhance the outcomes of such projects.     

Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings

Background  Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider clinical activity. Objective  The aim of our study was to validate audit-log based EHR times using observed EHR-times extracted from screen recordings of EHR usage in the inpatient setting. Methods  This study was conducted in a 36-bed pediatric intensive care unit (PICU) at Lucile Packard Children''s Hospital Stanford between June 11 and July 14, 2020. Attending physicians, fellow physicians, hospitalists, and advanced practice providers with ≥0.5 full-time equivalent (FTE) for the prior four consecutive weeks and at least one EHR session recording were included in the study. Citrix session recording player was used to retrospectively review EHR session recordings that were captured as the provider interacted with the EHR. Results  EHR use patterns varied by provider type. Audit-log based total EHR time correlated strongly with both observed total EHR time ( r  = 0.98, p  < 0.001) and observed active EHR time ( r  = 0.95, p  < 0.001). Each minute of audit-log based total EHR time corresponded to 0.95 (0.87–1.02) minutes of observed total EHR time and 0.75 (0.67–0.83) minutes of observed active EHR time. Results were similar when stratified by provider role. Conclusion  Our study found inpatient audit-log based EHR time to correlate strongly with observed EHR time among pediatric critical care providers. These findings support the use of audit-log based EHR-time as a surrogate measure for inpatient provider EHR use, providing an opportunity for researchers and other stakeholders to leverage EHR audit-log data in measuring clinical activity and tracking outcomes of workflow improvement efforts longitudinally and across provider groups.     

Data Quality of Chemotherapy-Induced Nausea and Vomiting Documentation

Objective  The objective of the study was to characterize the completeness and concordance of the electronic health record (EHR) documentation of cancer symptoms among multidisciplinary health care professionals. Methods  We examined the EHRs of children, adolescents, and young adults who received highly emetogenic chemotherapy and characterized the completeness and concordance of chemotherapy-induced nausea and vomiting (CINV) documentation by clinician type and by the International Classification of Diseases 10th Revision (ICD-10) coding choice. Results  The EHRs of 127 patients, comprising 870 patient notes, were abstracted and reviewed. A CINV assessment was documented by prescribers in 75% of patients, and by nurses in 58% of patients. Of the 60 encounters where both prescribers and nurses documented, 72% agreed on the presence/absence of CINV. Conclusion  Most patients receiving highly emetogenic chemotherapy had a documented assessment of CINV; however, many had incomplete or discordant documentation of CINV from different providers by role, implying the importance of incorporating pragmatic knowledge of EHR documentation patterns among multidisciplinary health professionals for EHR phenotyping and clinical decision support systems directed toward cancer-related symptom management.     

Physician Specialty and Variations in Adoption of Electronic Health Records

Objective

Efforts to promote adoption of electronic health records (EHRs) have focused on primary care physicians, who are now expected to exchange data electronically with other providers, including specialists. However, the variation of EHR adoption among specialists is underexplored.

Methods

We conducted a retrospective cross-sectional study to determine the association between physician specialty and the prevalence of EHR adoption, and a retrospective serial cross-sectional study to determine the association of physician specialty and the rate of EHR adoption over time. We used the 2005–2009 National Ambulatory Medical Care Survey. We considered fourteen specialties, and four definitions of EHR adoption (any EHR, basic EHR, full EHR, and a novel definition of EHR sophistication). We used multivariable logistic regression, and adjusted for several covariates (geography, practice characteristics, revenue characteristics, physician degree).

Results

Physician specialty was significantly associated with EHR adoption, regardless of the EHR definition, after adjusting for covariates. Psychiatrists, dermatologists, pediatricians, ophthalmologists, and general surgeons were significantly less likely to adopt EHRs, compared to the reference group of family medicine / general practitioners. After adjustment for covariates, these specialties were 44 – 94% less likely to adopt EHRs than the reference group. EHR adoption increased in all specialties, by approximately 40% per year. The rate of EHR adoption over time did not significantly vary by specialty.

Conclusions

Although EHR adoption is increasing in all specialties, adoption varies widely by specialty. In order to insure each individual’s network of providers can electronically share data, widespread adoption of EHRs is needed across all specialties.     

Searching the PDF Haystack: Automated Knowledge Discovery in Scanned EHR Documents

Background  Clinicians express concern that they may be unaware of important information contained in voluminous scanned and other outside documents contained in electronic health records (EHRs). An example is “unrecognized EHR risk factor information,” defined as risk factors for heritable cancer that exist within a patient''s EHR but are not known by current treating providers. In a related study using manual EHR chart review, we found that half of the women whose EHR contained risk factor information meet criteria for further genetic risk evaluation for heritable forms of breast and ovarian cancer. They were not referred for genetic counseling. Objectives  The purpose of this study was to compare the use of automated methods (optical character recognition with natural language processing) versus human review in their ability to identify risk factors for heritable breast and ovarian cancer within EHR scanned documents. Methods  We evaluated the accuracy of the chart review by comparing our criterion standard (physician chart review) versus an automated method involving Amazon''s Textract service (Amazon.com, Seattle, Washington, United States), a clinical language annotation modeling and processing toolkit (CLAMP) (Center for Computational Biomedicine at The University of Texas Health Science, Houston, Texas, United States), and a custom-written Java application. Results  We found that automated methods identified most cancer risk factor information that would otherwise require clinician manual review and therefore is at risk of being missed. Conclusion  The use of automated methods for identification of heritable risk factors within EHRs may provide an accurate yet rapid review of patients'' past medical histories. These methods could be further strengthened via improved analysis of handwritten notes, tables, and colloquial phrases.     

Electronic Task Management System: A Pediatric Institution's Experience

Background  Electronic medical task management systems (ETMs) have been adopted in health care institutions to improve health care provider communication. ETMs allow for the requesting and resolution of nonurgent tasks between clinicians of all craft groups. Visibility, ability to provide close-loop feedback, and a digital trail of all decisions and responsible clinicians are key features of ETMs. An embedded ETM within an integrated electronic health record (EHR) was introduced to the Royal Children''s Hospital Melbourne on April 30, 2016. The ETM is used hospital-wide for nonurgent tasks 24 hours a day. It facilitates communication of nonurgent tasks between clinical staff, with an associated designated timeframe in which the task needs to be completed (2, 4, and 8 hours). Objective  This study aims to examine the usage of the ETM at our institution since its inception. Methods  ETM usage data from the first 3 years of use (April 2016 to April 2019) were extracted from the EHR. Data collected included age of patient, date and time of task request, ward, unit, type of task, urgency of task, requestor role, and time to completion. Results  A total of 136,481 tasks were placed via the ETM in the study period. There were approximately 125 tasks placed each day (24-hour period). The most common time of task placement was around 6:00 p.m. Task placement peaked at approximately 8 a.m., 2 p.m., and 9 p.m.—consistent with nursing shift change times. In total, 63.16% of tasks were placed outside business hours, indicating predominant usage for after-hours task communication. The ETM was most highly utilized by surgical units. The majority of tasks were ordered by nurses for medical staff to complete (97.01%). A significant proportion (98.79%) of tasks was marked as complete on the ETM, indicating closed-loop feedback after tasks were requested. Conclusion  An ETM function embedded in our EHR has been highly utilized in our institution since its introduction. It has multiple benefits for the clinician in the form of efficiencies in workflow and improvement in communication and also workflow management. By allowing collection, tracking, audit, and prioritization of tasks, it also provides a stream of actionable data for quality-improvement activities.     

Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records

Background  Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures). Objective  We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year. Methods  Both eMeasures define the numerator and denominator beginning at the patient level, populations'' specifications, and validated the automated queries. For eCRA, patients who completed a comprehensive or periodic oral evaluation formed the denominator, and patients of any age who received a CRA formed the numerator. The eAoC evaluated the proportion of patients at elevated caries risk who received the corresponding appropriate risk-based preventative treatments. Results  EHR automated queries identified in three sites 269,536 patients who met the inclusion criteria for receiving a CRA. The overall proportion of patients who received a CRA was 94.4% (eCRA). In eAoC, patients at elevated caries risk levels (moderate, high, or extreme) received fluoride preventive treatment ranging from 56 to 93.8%. For patients at high and extreme risk, antimicrobials were prescribed more frequently site 3 (80.6%) than sites 2 (16.7%) and 1 (2.9%). Conclusion  Patient-level data available in the EHRs can be used to implement process-of-care dental eCRA and AoC, eAoC measures identify gaps in clinical practice. EHR-based measures can be useful in improving delivery of evidence-based preventative treatments to reduce risk, prevent tooth decay, and improve oral health.     

An Analysis of Electronic Health Record Work to Manage Asynchronous Clinical Messages among Breast Cancer Care Teams

Objective  Asynchronous messaging is an integral aspect of communication in clinical settings, but imposes additional work and potentially leads to inefficiency. The goal of this study was to describe the time spent using the electronic health record (EHR) to manage asynchronous communication to support breast cancer care coordination. Methods  We analyzed 3 years of audit logs and secure messaging logs from the EHR for care team members involved in breast cancer care at Vanderbilt University Medical Center. To evaluate trends in EHR use, we combined log data into sequences of events that occurred within 15 minutes of any other event by the same employee about the same patient. Results  Our cohort of 9,761 patients were the subject of 430,857 message threads by 7,194 employees over a 3-year period. Breast cancer care team members performed messaging actions in 37.5% of all EHR sessions, averaging 29.8 (standard deviation [SD] = 23.5) messaging sessions per day. Messaging sessions lasted an average of 1.1 (95% confidence interval: 0.99–1.24) minutes longer than nonmessaging sessions. On days when the cancer providers did not otherwise have clinical responsibilities, they still performed messaging actions in an average of 15 (SD = 11.9) sessions per day. Conclusion  At our institution, clinical messaging occurred in 35% of all EHR sessions. Clinical messaging, sometimes viewed as a supporting task of clinical work, is important to delivering and coordinating care across roles. Measuring the electronic work of asynchronous communication among care team members affords the opportunity to systematically identify opportunities to improve employee workload.     

Electronic Health Records in Danish Home Care and Nursing Homes: Inadequate Documentation of Care,Medication, and Consent

Background  Electronic health records (EHRs) are used in long-term care to document the patients'' condition, medication, and care, thereby supporting communication among caregivers and counteracting adverse drug events. However, the use of EHRs in long-term care has lagged behind EHR use in hospitals. In addition, most EHR research focuses on hospitals. Objective  This study gives a countrywide status of the documentation-related risks to patient safety in Danish home care and nursing homes, which are the two main providers of long-term care. Such a status provides a basis for national improvement efforts and international comparisons. Method  The study is based on the reports from 893 inspections of home care and nursing homes by the Danish Patient Safety Authority (Styrelsen for Patientsikkerhed [STPS]). Results  As much as 69% of the inspected institutions document inadequately to an extent that has led to demands (i.e., issues the institution is legally obliged to rectify) or requests (i.e., issues the institution is merely asked to rectify) from STPS. Documentation issues about the patients'' condition and care are present in nearly all institutions that receive demands (97%) and in the majority of those that receive requests (68%). Documentation issues about medication and consent to care are also common, but less so. The predominant risk to patient safety is incomplete documentation. It covers 72% of the documentation issues identified in the institutions that received demands; the remaining risks concern inconsistent (11%), nonexistent (7%), inaccessible (5%), and noncompliant (5%) documentation. The documentation inadequacies are similar for home care and nursing homes. Conclusion  Inadequate EHR documentation is a widespread problem in Danish long-term care. While previous research mainly focuses on how EHR documentation affects patient medication, this study finds that documentation issues about the patients'' condition and care are more prevalent and that issues about their consent are also common.     

Awareness of the Care Team in Electronic Health Records

OBJECTIVE: To support collaboration and clinician-targeted decision support, electronic health records (EHRs) must contain accurate information about patients' care providers. The objective of this study was to evaluate two approaches for care provider identification employed within a commercial EHR at a large academic medical center. METHODS: We performed a retrospective review of EHR data for 121 patients in two cardiology wards during a four-week period. System audit logs of chart accesses were analyzed to identify the clinicians who were likely participating in the patients' hospital care. The audit log data were compared with two functions in the EHR for documenting care team membership: 1) a vendor-supplied module called "Care Providers", and 2) a custom "Designate Provider" order that was created primarily to improve accuracy of the attending physician of record documentation. RESULTS: For patients with a 3-5 day hospital stay, an average of 30.8 clinicians accessed the electronic chart, including 10.2 nurses, 1.4 attending physicians, 2.3 residents, and 5.4 physician assistants. The Care Providers module identified 2.7 clinicians/patient (1.8 attending physicians and 0.9 nurses). The Designate Provider order identified 2.1 clinicians/patient (1.1 attending physicians, 0.2 resident physicians, and 0.8 physician assistants). Information about other members of patients' care teams (social workers, dietitians, pharmacists, etc.) was absent. CONCLUSIONS: The two methods for specifying care team information failed to identify numerous individuals involved in patients' care, suggesting that commercial EHRs may not provide adequate tools for care team designation. Improvements to EHR tools could foster greater collaboration among care teams and reduce communication-related risks to patient safety.     

The Impact of Longer Consultation Time: A Simulation-Based Approach

Background  Maintaining a sufficient consultation length in primary health care (PHC) is a fundamental part of providing quality care that results in patient safety and satisfaction. Many facilities have limited capacity and increasing consultation time could result in a longer waiting time for patients and longer working hours for physicians. The use of simulation can be practical for quantifying the impact of workflow scenarios and guide the decision-making. Objective  To examine the impact of increasing consultation time on patient waiting time and physician working hours. Methods  Using discrete events simulation, we modeled the existing workflow and tested five different scenarios with a longer consultation time. In each scenario, we examined the impact of consultation time on patient waiting time, physician hours, and rate of staff utilization. Results  At baseline scenarios (5-minute consultation time), the average waiting time was 9.87 minutes and gradually increased to 89.93 minutes in scenario five (10 minutes consultation time). However, the impact of increasing consultation time on patients waiting time did not impact all patients evenly where patients who arrive later tend to wait longer. Scenarios with a longer consultation time were more sensitive to the patients'' order of arrival than those with a shorter consultation time. Conclusion  By using simulation, we assessed the impact of increasing the consultation time in a risk-free environment. The increase in patients waiting time was somewhat gradual, and patients who arrive later in the day are more likely to wait longer than those who arrive earlier in the day. Increasing consultation time was more sensitive to the patients'' order of arrival than those with a shorter consultation time.     

Use,Impact, Weaknesses,and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective  Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient''s record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods  We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results  Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient''s record. Conclusion  Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering.     

Impact of Changes in EHR Use during COVID-19 on Physician Trainee Mental Health

Objectives  This article investigates the association between changes in electronic health record (EHR) use during the coronavirus disease 2019 (COVID-19) pandemic on the rate of burnout, stress, posttraumatic stress disorder (PTSD), depression, and anxiety among physician trainees (residents and fellows). Methods  A total of 222 (of 1,375, 16.2%) physician trainees from an academic medical center responded to a Web-based survey. We compared the physician trainees who reported that their EHR use increased versus those whose EHR use stayed the same or decreased on outcomes related to depression, anxiety, stress, PTSD, and burnout using univariable and multivariable models. We examined whether self-reported exposure to COVID-19 patients moderated these relationships. Results  Physician trainees who reported increased use of EHR had higher burnout (adjusted mean, 1.48 [95% confidence interval [CI] 1.24, 1.71] vs. 1.05 [95% CI 0.93, 1.17]; p  = 0.001) and were more likely to exhibit symptoms of PTSD (adjusted mean = 15.09 [95% CI 9.12, 21.05] vs. 9.36 [95% CI 7.38, 11.28]; p  = 0.035). Physician trainees reporting increased EHR use outside of work were more likely to experience depression (adjusted mean, 8.37 [95% CI 5.68, 11.05] vs. 5.50 [95% CI 4.28, 6.72]; p  = 0.035). Among physician trainees with increased EHR use, those exposed to COVID-19 patients had significantly higher burnout (2.04, p  < 0.001) and depression scores (14.13, p  = 0.003). Conclusion  Increased EHR use was associated with higher burnout, depression, and PTSD outcomes among physician trainees. Although preliminary, these findings have implications for creating systemic changes to manage the wellness and well-being of trainees.     

Clinician Perceptions on the Use of Free-Text Communication Orders

Objective  The aim of this study was to investigate (1) why ordering clinicians use free-text orders to communicate medication information; (2) what risks physicians and nurses perceive when free-text orders are used for communicating medication information; and (3) how electronic health records (EHRs) could be improved to encourage the safe communication of medication information. Methods  We performed semi-structured, scenario-based interviews with eight physicians and eight nurses. Interview responses were analyzed and grouped into common themes. Results  Participants described eight reasons why clinicians use free-text medication orders, five risks relating to the use of free-text medication orders, and five recommendations for improving EHR medication-related communication. Poor usability, including reduced efficiency and limited functionality associated with structured order entry, was the primary reason clinicians used free-text orders to communicate medication information. Common risks to using free-text orders for medication communication included the increased likelihood of missing orders and the increased workload on nurses responsible for executing orders. Discussion  Clinicians'' use of free-text orders is primarily due to limitations in the current structured order entry design. To encourage the safe communication of medication information between clinicians, the EHR''s structured order entry must be redesigned to support clinicians'' cognitive and workflow needs that are currently being addressed via the use of free-text orders. Conclusion  Clinicians'' use of free-text orders as a workaround to insufficient structured order entry can create unintended patient safety risks. Thoughtful solutions designed to address these workarounds can improve the medication ordering process and the subsequent medication administration process.     

Electronic Health Record Adoption – Maybe It’s not about the Money: Physician Super-Users,Electronic Health Records and Patient Care

Objective

The slow adoption of electronic health record (EHR) systems has been linked to physician resistance to change and the expense of EHR adoption. This qualitative study was conducted to evaluate benefits, and clarify limitations of two mature, robust, comprehensive EHR Systems by tech-savvy physicians where resistance and expense are not at issue.

Methods

Two EHR systems were examined – the paperless VistA / Computerized Patient Record System used at the Veterans’ Administration, and the General Electric Centricity Enterprise system used at an academic medical center. A series of interviews was conducted with 20 EHR-savvy multiinstitutional internal medicine (IM) faculty and house staff. Grounded theory was used to analyze the transcribed data and build themes. The relevance and importance of themes were constructed by examining their frequency, convergence, and intensity.

Results

Despite eliminating resistance to both adoption and technology as drivers of acceptance, these two robust EHR’s are still viewed as having an adverse impact on two aspects of patient care, physician workflow and team communication. Both EHR’s had perceived strengths but also significant limitations and neither were able to satisfactorily address all of the physicians’ needs.

Conclusion

Difficulties related to physician acceptance reflect real concerns about EHR impact on patient care. Physicians are optimistic about the future benefits of EHR systems, but are frustrated with the non-intuitive interfaces and cumbersome data searches of existing EHRs.     

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Background  Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives  This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods  We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results  We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion  This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.