ArticleJournal of the American Medical Informatics Association : JAMIA2017
The electronic health record audit file: the patient is waiting.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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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, 1 synthesis or guideline pooled it.
- Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- Article
- An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results.JAMIA open · 2021Article
- Studying Workflow and Workarounds in Electronic Health Record-Supported Work to Improve Health System Performance.Annals of internal medicine · 2020Review
- Attributing Patients to Pediatric Residents Using Electronic Health Record Features Augmented with Audit Logs.Applied clinical informatics · 2020Article
- The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study.JMIR medical informatics · 2020Article
- Learning Tasks of Pediatric Providers from Electronic Health Record Audit Logs.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study.JMIR medical informatics · 2019Article
- Automatic Detection of Front-Line Clinician Hospital Shifts: A Novel Use of Electronic Health Record Timestamp Data.Applied clinical informatics · 2019Article
- Secondary use of electronic health record data for clinical workflow analysis.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Using EHR audit trail logs to analyze clinical workflow: A case study from community-based ambulatory clinics.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe describe how electronic health record (EHR) audit files can be used to understand how time is spent in primary care (PC). MATERIALS/
methodsWe used audit file data from the Geisinger Clinic to quantify elements of the clinical workflow and to determine how these times vary by patient and encounter factors. We randomly selected audit file records representing 36 437 PC encounters across 26 clinic locations. Audit file data were used to estimate duration and variance of: (1) time in the waiting room, (2) nurse time with the patient, (3) time in the exam room without a nurse or physician, and (4) physician time with the patient. Multivariate modeling was used to test for differences by patient and by encounter features.
resultsOn average, a PC encounter took 54.6 minutes, with 5 minutes of nurse time, 15.5 minutes of physician time, and the remaining 62% of the time spent waiting to see a clinician or check out. Older age, female sex, and chronic disease were associated with longer wait times and longer time with clinicians. Level of service and numbers of medications, procedures, and lab orders were associated with longer time with clinicians. Late check-in and same-day visits were associated with shorter wait time and clinician time.
conclusionsThis study provides insights on uses of audit file data for workflow analysis during PC encounters. DISCUSSION: Scalable ways to quantify clinical encounter workflow elements may provide the means to develop more efficient approaches to care and improve the patient experience.
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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.