ArticleApplied clinical informatics2024
Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters.
Article in Applied clinical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Computable phenotypes for research using real-world data: experiences from the NIH pragmatic trials collaboratory.JAMIA open · 2026Article
- Challenges in Identifying Heart Failure Diagnoses from the Electronic Health Record.Journal of cardiac failure - intersections · 2026Article
- Electronic Strategies for Tailored Exercise to Prevent Falls: Evaluating Implementation in Primary Care.Applied clinical informatics · 2026Article
- Work outside of work: after-hours use of the electronic medical record among residents at an academic veterinary teaching hospital.Frontiers in veterinary science · 2026Article
- Typing Proficiency among Physicians in Internal Medicine: A Pilot Study of Speed and Performance.Applied clinical informatics · 2025Article
- EHR Use in Inpatient Physicians: Patterns and Predictors.Applied clinical informatics · 2025Article
- Development and Evaluation of Clinical Decision Support for Immigrant Child Health Screening in Primary Care.Applied clinical informatics · 2025Article
- A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation.NPJ digital medicine · 2025Article
- Digital supervision in the clinical learning environment: Characterizing teamwork in the electronic health record.Journal of hospital medicine · 2025Article
- Emerging Domains for Measuring Health Care Delivery With Electronic Health Record Metadata.Journal of medical Internet research · 2025Review
- Consistency is key: documentation distribution and efficiency in primary care.Journal of the American Medical Informatics Association : JAMIA · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectronic 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.
objectiveThis 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.
methodsWe 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.
resultsIn 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.
conclusionThe 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.
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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 Socratic graph.