ArticleHealth services research2024
The role of organizations in shaping physician use of electronic health records.
Article in Health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Measuring Documentation Burden in Healthcare.Journal of general internal medicine · 2024Pooled it
- Computable phenotypes for research using real-world data: experiences from the NIH pragmatic trials collaboratory.JAMIA open · 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
- Electronic health record use factors linked to efficiency and productivity: an explainable machine learning analysis.JAMIA open · 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
- Behavioral Phenotypes in Electronic Health Record Use by Primary Care Providers: a Cluster Analysis.Journal of general internal medicine · 2025Article
- A Preliminary Conceptual Framework of Clinical Documentation Burden: Exploratory Factor Analysis Investigating Usability, Effort, and Perceived Burden among Health Care Providers.Applied clinical informatics · 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
- 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
- Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters.Applied clinical informatics · 2024Article
- The role of organizations in shaping physician use of electronic health records.Health services research · 2024Article
- More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.Annals of family medicineArticle
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.
Funding
Abstract
objectiveThe aim of the study was to (1) characterize organizational differences in primary care physicians' electronic health record (EHR) behavior; (2) assess within-organization consistency in EHR behaviors; and (3) identify whether organizational consistency is associated with physician-level efficiency. DATA SOURCES: EHR metadata capturing averaged weekly measures of EHR time and documentation composition from 75,124 US primary care physicians across 299 organizations between September 2020 and May 2021 were taken. EHR time measures include active time in orders, chart review, notes, messaging, time spent outside of scheduled hours, and total EHR time. Documentation composition measures include note length and percentage use of templated text or copy/paste. Efficiency is measured as the percent of visits with same-day note completion. STUDY
designAll analyses are cross-sectional. Across-organization differences in EHR use and documentation composition are presented via 90th-to-10th percentile ratios of means and SDs. Multilevel modeling with post-estimation variance partitioning assesses the extent of an organizational signature-the proportion of variation in our measures attributable to organizations (versus specialty and individual behaviors). We measured organizational internal consistency for each measure via organization-level SD, which we grouped into quartiles for regression. Association between internally consistent (i.e., low SD) organizational EHR use and physician-level efficiency was assessed with multi-variable OLS models. DATA COLLECTION: Extraction from Epic's Signal platform used for measuring provider EHR efficiency. PRINCIPAL
findingsEHR time per visit for physicians at a 90th percentile organization is 1.94 times the average EHR time at a 10th percentile organization. There is little evidence, on average, of an organizational signature. However, physicians in organizations with high internal consistency in EHR use demonstrate increased efficiency. Physicians in organizations with the highest internal consistency (top quartile) have a 3.77 percentage point higher same-day visit closure rates compared with peers in bottom quartile organizations (95% confidence interval: 0.0142-0.0612).
conclusionsResults suggest unrealized opportunities for organizations and policymakers to support consistency in how physicians engage in EHR-supported work.
Indexed as
Identifiers
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.