Evidence map›Paper›PMID 32515799›Full record

ArticleJAMA network open2020

Association of Electronic Health Record Use With Physician Fatigue and Efficiency.

Saif Khairat, Cameron Coleman, Paige Ottmar, Dipika Irene Jayachander, Thomas Bice, Shannon S Carson

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 72 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 4 pooled it
12.3field-weighted citation impact, top 1% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

72 citing papers in PubMed, 4 syntheses or guidelines pooled it, 105 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Trial
  7. A Two-Level, Multidimensional Framework for Understanding and Treating Clinician Fatigue.Health care analysis : HCA : journal of health philosophy and policy · 2026
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  8. Observational
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  16. Observer: creation of a novel multimodal dataset for outpatient care research.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
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  19. Review
  20. Article

12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Saif KhairatCarolina Health Informatics Program, University of North Carolina at Chapel Hill.
Cameron ColemanDepartment of Preventive Medicine, University of North Carolina at Chapel Hill.
Paige OttmarGilling's School of Public Health, University of North Carolina at Chapel Hill.
Dipika Irene JayachanderCarolina Health Informatics Program, University of North Carolina at Chapel Hill.
Thomas BicePulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill.
Shannon S CarsonPulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill.
University of North Carolina at Chapel Hill · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The use of electronic health records (EHRs) is directly associated with physician burnout. An underlying factor associated with burnout may be EHR-related fatigue owing to insufficient user-centered interface design and suboptimal usability. Objective: To examine the association between EHR use and fatigue, as measured by pupillometry, and efficiency, as measured by mouse clicks, time, and number of EHR screens, among intensive care unit (ICU) physicians completing a simulation activity in a prominent EHR. Design, Setting, and Participants: A cross-sectional, simulation-based EHR usability assessment of a leading EHR system was conducted from March 20 to April 5, 2018, among 25 ICU physicians and physician trainees at a southeastern US academic medical center. Participants completed 4 simulation patient cases in the EHR that involved information retrieval and task execution while wearing eye-tracking glasses. Fatigue was quantified through continuous eye pupil data; EHR efficiency was characterized through task completion time, mouse clicks, and EHR screen visits. Data were analyzed from June 1, 2018, to August 31, 2019. Main Outcomes and Measures: Primary outcomes were physician fatigue, measured by pupillometry (with lower scores indicating greater fatigue), and EHR efficiency, measured by task completion times, number of mouse clicks, and number of screens visited during EHR simulation. Results: The 25 ICU physicians (13 women; mean [SD] age, 32.1 [6.1] years) who completed a simulation exercise involving 4 patient cases (mean [SD] completion time, 34:43 [11:41] minutes) recorded a total of 14 hours and 27 minutes of EHR activity. All physician participants experienced physiological fatigue at least once during the exercise, and 20 of 25 participants (80%) experienced physiological fatigue within the first 22 minutes of EHR use. Physicians who experienced EHR-related fatigue in 1 patient case were less efficient in the subsequent patient case, as demonstrated by longer task completion times (r = -0.521; P = .007), higher numbers of mouse clicks (r = -0.562; P = .003), and more EHR screen visits (r = -0.486; P = .01). Conclusions and Relevance: This study reports high rates of fatigue among ICU physicians during short periods of EHR simulation, which were negatively associated with EHR efficiency and included a carryover association across patient cases. More research is needed to investigate the underlying causes of EHR-associated fatigue, to support user-centered EHR design, and to inform safe EHR use policies and guidelines.

Indexed as

Electronic Health RecordsAdultBurnout, ProfessionalCross-Sectional StudiesFatigueHumansMiddle AgedPhysiciansYoung Adult

Identifiers

PMID32515799
PMCPMC7284310
OpenAlexW3033315791

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.