Evidence map›Paper›PMID 42496179›Full record

Observational studyJMIR medical informatics2026

Quantifying and Visualizing Emergency Physician Workflow: Observational Time-Motion Study.

Andrew J Henreid, Kimon L H Ioannides, Joshua M Pevnick, Tara N Cohen, Sam S Torbati, Teryl K Nuckols, Carl T Berdahl

Abstract readObservational Study
In one paragraph

Observational study in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Andrew J HenreidDepartment of Medicine, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, United States, 1 310-423-3141.ORCID 0000-0001-8466-1057
Kimon L H IoannidesDepartment of Emergency Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0002-6384-2235
Joshua M PevnickDepartment of Medicine, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, United States, 1 310-423-3141.ORCID 0000-0003-0621-1485
Tara N CohenDepartment of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0003-2137-6093
Sam S TorbatiDepartment of Emergency Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0001-8424-8764
Teryl K NuckolsDivision of General Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0002-0416-1595
Carl T BerdahlDepartment of Medicine, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, United States, 1 310-423-3141.ORCID 0000-0002-4374-3280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Emergency physicians face considerable workflow challenges in the emergency department (ED) due to unpredictable work environments, frequent interruptions, and mounting documentation requirements, all of which contribute to substantial computer-based work. Excessive time away from direct patient care is increasingly viewed as detrimental to the quality of care, communication, and patient safety. Objective: This study aimed to quantify and visualize how emergency physicians allocate their time during ED shifts, particularly the time spent on the computer. Methods: This cross-sectional observational time-motion study was conducted in a high-volume, urban ED. We used the validated TimeCaT application to continuously track physician activities, including computer use, direct patient care, communication, and all other tasks carried out during the shift. Electronic health record event log data were queried to estimate physicians' computer use after their scheduled shift. The main outcome was the proportion of time spent on each activity. The primary measure was the total minutes of computer use (during and after the shift) per scheduled hour of clinical work. Additionally, we generated data visualizations to illustrate ED workflow-sequencing, task switching, and between-shift variability. Results: We observed 20 emergency physicians for one 8- to 9-hour clinical shift each, generating over 150.0 hours of real-time observation data quantifying physicians' ED workflow. Physicians spent a median of 34.1% of their shift minutes using the computer (156.5, IQR 145.2-179.3 min) and 26.9% with patients (115.2, IQR 102.0-154.1 min). Other activities included 15.9% for verbal communication with staff (73.3, IQR 45.6-96.4 min), 9.5% phone use (41.4, IQR 33.4-59.2 min), 5.5% miscellaneous tasks (24.2, IQR 18.4-30.1 min), 3.9% personal time (16.8, IQR 9.9-25.4 min), 0.7% electrocardiogram review (3.8, IQR 1.4-5.0 min), and 0.4% other procedures (median 1.7, IQR 0.6-6.4 min). Electronic health record log analysis showed that physicians spent an additional median 1.3 (IQR 0.5-2.6) hours using the computer after their scheduled shifts, for a combined 29.8 (IQR 25.6-38.5) minutes on the computer per scheduled hour of their ED shift. Workflow visualizations showed frequent alternation among activity categories and noticeable variability in within-shift fragmentation across physicians. Conclusions: Emergency physicians spent more than one-third of their ED shift working on the computer, which was more time than they spent with patients. They also spent 1 to 2 hours using the computer after their scheduled shift. These findings demonstrate the need for strategies to reduce unnecessary computer use during and after clinical shifts to enhance workflow efficiency and improve patient care.

Indexed as

Emergency Service, HospitalTime and Motion StudiesWorkflowCross-Sectional StudiesElectronic Health RecordsHumansPhysicianscomputersdocumentationefficiencyelectronic health recordsemergency medicinepatient carephysicianstime and motion studiestime managementworkflow

Identifiers

PMID42496179
PMCPMC13397913

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.