ArticleJournal of the American Medical Informatics Association : JAMIA2020
Are specific elements of electronic health record use associated with clinician burnout more than others?
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
63 citing papers in PubMed, 4 syntheses or guidelines pooled it, 98 citations in OpenAlex.
- Electronic health records-related determinants of healthcare professionals' burnout and mitigation strategies: systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Digital compassion fatigue and digital empathy in healthcare: mapping the evidence and informing a human-centered clinical framework.Frontiers in psychology · 2026Pooled it
- Measuring Documentation Burden in Healthcare.Journal of general internal medicine · 2024Pooled it
- Exploring the relationship between electronic health records and provider burnout: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Physician Factors Associated With Burnout During System-Wide Electronic Health Record Implementation: A Prospective Repeated Cross-Sectional Study of Acute and Post-Acute Care Physicians.Journal of evaluation in clinical practice · 2026Article
- The use of objective EHR-and schedule-based clinical workload and EHR use measures in predicting inpatient pediatric provider burnout.JAMIA open · 2026Article
- Mapping the generative era: a bibliometric and specialty-focused analysis of large language models in healthcare.Visual computing for industry, biomedicine, and art · 2026Article
- Examining aspects of job satisfaction associated with burnout and factors related to turnover intention in genetic counselors.Journal of genetic counseling · 2026Article
- Copy Tools in the Electronic Health Record: Perceptions, Implications, and Future Directions.JMIR medical informatics · 2025Article
- Article
- Protected Time for Electronic Health Record Work and Physician Productivity.JAMA network open · 2025Article
- The Development and Evaluation of a Retrieval-Augmented Generation Large Language Model Virtual Assistant for Postoperative Instructions.Bioengineering (Basel, Switzerland) · 2025Article
- Unsupervised Large Language Models to Identify Topics in Cancer Center Patient Portal Messages.JCO clinical cancer informatics · 2025Article
- Primary care physicians' experiences with inbox triage.JAMIA open · 2025Article
- Exploring Provider Perceptions and Attitudes toward Copy-Paste and Copy-Forward in Clinical Documentation.Applied clinical informatics · 2025Article
- Qualitative Verification of Machine Learning-Based Burnout Predictors in Primary Care Physicians: An Exploratory Study.Applied clinical informatics · 2025Article
- A systematic review of early evidence on generative AI for drafting responses to patient messages.npj health systems · 2025Article
- National trends in oncology specialists' EHR inbox work, 2019-2022.Journal of the National Cancer Institute · 2025Article
- Primary care staff members' experiences with managing electronic health record inbox messages.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Providing effective feedback for training: Is there a role for informatics?Journal of pediatric gastroenterology and nutrition · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data. MATERIALS AND
methodsWe combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics.
resultsClinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039). DISCUSSION: High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, "patient calls" encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being.
conclusionsOur results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.