ArticleJournal of the American Medical Informatics Association : JAMIA2021
Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Article
- Toward Child-Centred Artificial Intelligence in Pediatric Emergency Medicine: A Perspective on Clinical Decision Support, Stakeholder Engagement and Education.Pediatric reports · 2026Article
- Clinicians' Reactions to Point-of-Care Advertising in Electronic Health Records.Therapeutic innovation & regulatory science · 2026Article
- Assessing the quality of AI-generated and physician-written discharge summaries: evaluation of an EHR-integrated tool in a Dutch academic hospital.EBioMedicine · 2026Article
- Healthcare provider burden reduction and estimated cost savings realized with electronic case reporting implementation across 3 healthcare organizations.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Predicting Electronic Health Record Usability: Scoping Review of Adoption Models, Metrics, and Future Directions.JMIR human factors · 2026Article
- Variation in Measures of Electronic Health Record Use Outside Scheduled Hours: A Cross-Sectional Study of Academic Primary Care Physicians.Applied clinical informatics · 2026Article
- Nested order panels for adult primary care modestly improves ordering efficiency among high utilizers.JAMIA open · 2026Article
- Artificial intelligence-generated encounter summaries: early insights from ambulatory clinicians at a large academic health system.JAMIA open · 2025Article
- Electronic health record activity changes around new decision support implementation: monitoring using audit logs and topic modeling.JAMIA open · 2025Article
- EHR Use in Inpatient Physicians: Patterns and Predictors.Applied clinical informatics · 2025Article
- Electronic Health Record Time Allocation Among Primary Care Clinicians at the Veterans Health Administration Using Virtual Observations.Journal of general internal medicine · 2025Article
- Surprisingly Helpful: The Introduction of Portal Practice Slots to Address the Inbasket Explosion.Journal of general internal medicine · 2025Article
- Does autotext usage decrease documentation time among resident physicians? A retrospective analysis of electronic health record usage data.JAMIA open · 2025Article
- Analyzing Physician In Basket Burden and Efficiency Using K-Means Clustering.Applied clinical informatics · 2025Article
- Article
- Addressing Note Bloat: Solutions for Effective Clinical Documentation.Journal of the American College of Emergency Physicians open · 2025Article
- Learning health system research as a catalyst for promoting physician wellness: EHR InBasket Spring cleaning and team-based compassion practice.Learning health systems · 2025Article
- Cumulated time to chart closure: a novel electronic health record-derived metric associated with clinician burnout.JAMIA open · 2024Article
- Quantifying EHR and Policy Factors Associated with the Gender Productivity Gap in Ambulatory, General Internal Medicine.Journal of general internal medicine · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time. MATERIALS AND
methodsA cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time.
resultsFive out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month -0.01 hours; practicing cardiology -1.30 hours; medical subspecialties -0.89 hours (except gastroenterology, P = .002); neurology/psychiatry -2.60 hours; obstetrics/gynecology -1.88 hours; pediatrics -1.05 hours (P = .001); sports/physical medicine and rehabilitation -3.25 hours; and surgical specialties -3.65 hours.
conclusionsFor every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.
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