Metrics for assessing physician activity using electronic health record log data

Christine A Sinsky¹, Adam Rule², Genna Cohen³, Brian G Arndt⁴, Tait D Shanafelt⁵, Christopher D Sharp^{5

6}, Sally L Baxter^{7

8}, Ming Tai-Seale⁹, Sherry Yan¹⁰, You Chen¹¹, Julia Adler-Milstein¹², Michelle Hribar²

Affiliations

¹ Department of Medicine, American Medical Association, Chicago, Illinois, USA.
² Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Oregon, USA.
³ Department of Medicine, Mathematica, Washington, DC, USA.
⁴ Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA.
⁵ Division of Hematology, Department of Medicine, Stanford University, Stanford, California, USA.
⁶ Division of General Internal Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
⁷ Department of Biomedical Informatics, University of California, San Diego, San Diego, California, USA.
⁸ Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, San Diego, California, USA.
⁹ Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
¹⁰ Department of Medicine, Sutter Health, Walnut Creek, California, USA.
¹¹ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
¹² Department of Medicine, University of California, San Francisco, San Francisco, California, USA.

PMID: 32027360
PMCID: PMC7075531
DOI: 10.1093/jamia/ocz223

Metrics for assessing physician activity using electronic health record log data

Christine A Sinsky et al. J Am Med Inform Assoc. 2020.

. 2020 Apr 1;27(4):639-643.

doi: 10.1093/jamia/ocz223.

Authors

Affiliations

¹ Department of Medicine, American Medical Association, Chicago, Illinois, USA.
² Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Oregon, USA.
³ Department of Medicine, Mathematica, Washington, DC, USA.
⁴ Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA.
⁵ Division of Hematology, Department of Medicine, Stanford University, Stanford, California, USA.
⁶ Division of General Internal Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
⁷ Department of Biomedical Informatics, University of California, San Diego, San Diego, California, USA.
⁸ Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, San Diego, California, USA.
⁹ Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
¹⁰ Department of Medicine, Sutter Health, Walnut Creek, California, USA.
¹¹ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
¹² Department of Medicine, University of California, San Francisco, San Francisco, California, USA.

PMID: 32027360
PMCID: PMC7075531
DOI: 10.1093/jamia/ocz223

Abstract

Electronic health record (EHR) log data have shown promise in measuring physician time spent on clinical activities, contributing to deeper understanding and further optimization of the clinical environment. In this article, we propose 7 core measures of EHR use that reflect multiple dimensions of practice efficiency: total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention. We also illustrate sample use cases for these measures for multiple stakeholders. Finally, standardization of EHR log data measure specifications, as outlined here, will foster cross-study synthesis and comparative research.

Keywords: EHR log data; metric; operational efficiency; time studies, burnout.

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References

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Metrics for assessing physician activity using electronic health record log data

Affiliations

Metrics for assessing physician activity using electronic health record log data

Authors

Affiliations

Abstract

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources