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

Author:

Melnick Edward R1ORCID,Ong Shawn Y1,Fong Allan2ORCID,Socrates Vimig3ORCID,Ratwani Raj M2,Nath Bidisha1,Simonov Michael1,Salgia Anup4,Williams Brian5,Marchalik Daniel6,Goldstein Richard5,Sinsky Christine A7

Affiliation:

1. Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA

2. MedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA

3. Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, Connecticut, USA

4. Northeast Ohio Medical University and Cerner Corporation, Kansas City, Missouri, USA

5. Northeast Medical Group, Yale-New Haven Health, Stratford, Connecticut, USA

6. Department of Urology, MedStar Health, Washington, DC, USA

7. Professional Satisfaction and Practice Sustainability, American Medical Association, Chicago, Illinois, USA

Abstract

Abstract 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.

Funder

2 American Medical Association Practice Transformation Initiatives

American Medical Association

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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