ArticleJournal of the American Medical Informatics Association : JAMIA2024
Guidance for reporting analyses of metadata on electronic health record use.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
15 citing papers in PubMed.
- Ambient AI Scribes and Emergency Department Documentation Burden: Retrospective Cohort Study.JMIR AI · 2026Article
- Predicting Electronic Health Record Usability: Scoping Review of Adoption Models, Metrics, and Future Directions.JMIR human factors · 2026Article
- Hybrid Ambient Clinical Documentation and Physician Performance: Work Outside of Work, Documentation Delay, and Financial Productivity.Journal of general internal medicine · 2026Article
- Utilization of Generative AI-drafted Responses for Managing Patient-Provider Communication.NPJ digital medicine · 2025Article
- A Measurement Science Framework to Optimize CDS for Opioid Use Disorder Treatment in the ED.Applied clinical informatics · 2025Article
- Trends in electronic health record metadata use for management purposes.Learning health systems · 2025Article
- Narrative Review of Electronic Health Record Systems in Anesthesia: Benefits, Risks, and Medico-Legal Considerations in the United States of America.Journal of medical systems · 2025Review
- How Data Analytics Can Be Leveraged to Enhance Graduate Clinical Skills Education.Journal of graduate medical education · 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
- Unlocking inpatient workload insights with electronic health record event logs.Journal of hospital medicine · 2025Article
- Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata.npj health systems · 2025Review
- Accounting for taste: preferences mediate the relationship between documentation time and ambulatory physician burnout.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Consistency is key: documentation distribution and efficiency in primary care.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- A Scalable and Extensible Logical Data Model of Electronic Health Record Audit Logs for Temporal Data Mining (RNteract): Model Conceptualization and Formulation.JMIR nursing · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
introductionResearch on how people interact with electronic health records (EHRs) increasingly involves the analysis of metadata on EHR use. These metadata can be recorded unobtrusively and capture EHR use at a scale unattainable through direct observation or self-reports. However, there is substantial variation in how metadata on EHR use are recorded, analyzed and described, limiting understanding, replication, and synthesis across studies. RECOMMENDATIONS: In this perspective, we provide guidance to those working with EHR use metadata by describing 4 common types, how they are recorded, and how they can be aggregated into higher-level measures of EHR use. We also describe guidelines for reporting analyses of EHR use metadata-or measures of EHR use derived from them-to foster clarity, standardization, and reproducibility in this emerging and critical area of research.
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What OpenQuestion holds
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.