Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

J Am Med Inform Assoc. 2021 Jul 14;28(7):1383-1392. doi: 10.1093/jamia/ocab011.


Objective: To derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time.

Materials and methods: A cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time.

Results: Five out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month -0.01 hours; practicing cardiology -1.30 hours; medical subspecialties -0.89 hours (except gastroenterology, P = .002); neurology/psychiatry -2.60 hours; obstetrics/gynecology -1.88 hours; pediatrics -1.05 hours (P = .001); sports/physical medicine and rehabilitation -3.25 hours; and surgical specialties -3.65 hours.

Conclusions: For every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Cross-Sectional Studies
  • Electronic Health Records
  • Feasibility Studies
  • Female
  • Humans
  • Medicine*
  • Physicians*