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CC BY-NC-ND 4.0 · Appl Clin Inform 2023; 14(05): 944-950
DOI: 10.1055/a-2187-3243
State of the Art/Best Practice Paper

Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings

Deborah R. Levy
1   Department of Veterans Affairs, VA Connecticut Healthcare System, West Haven, Connecticut, United States
2   Section of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States
,
Amanda J. Moy
3   Department of Biomedical Informatics, Columbia University, New York, New York, United States
,
Nate Apathy
4   National Center for Human Factors in Healthcare, MedStar Health Research Institute, Washington, District of Columbia, United States
5   Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Iowa, United States
,
Julia Adler-Milstein
6   Department of Medicine, Center for Clinical Informatics and Improvement Research, University of California, San Francisco, California, United States
,
Lisa Rotenstein
7   Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
8   Harvard Medical School, Boston, Massachusetts, United States
,
Bidisha Nath
9   Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States
,
S. Trent Rosenbloom
10   Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States
,
Thomas Kannampallil
11   Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, United States
12   Institute for Informatics, Data Science, and Biostatistics (I2DB), Washington University School of Medicine, St. Louis, Missouri, United States
,
Rebecca G. Mishuris
7   Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
8   Harvard Medical School, Boston, Massachusetts, United States
13   Digital, Mass General Brigham, Boston, Massachusetts, United States
,
Aram Alexanian
14   Novant Health, Charlotte, North Carolina, United States
,
Amber Sieja
15   Department of General Internal Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States
,
Michelle R. Hribar
16   Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, United States
,
Jigar S. Patel
17   Oracle Corporation, Kansas City, Missouri, United States
,
Christine A. Sinsky
18   American Medical Association, Chicago, Illinois, United States
,
Edward R. Melnick
2   Section of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States
9   Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States
› Author Affiliations Funding This work was supported by the American Medical Association Practice Transformation Initiatives (contract number 19449). D.R.L. is supported by the Department of Veterans Affairs, Veterans Health Administration, Office of Academic Affiliations, Office of Research and Development, with resources and the use of facilities at the VA Connecticut Healthcare System, West Haven, Connecticut (CIN-13-407). E.R.M. reports receiving grants from the National Institute on Drug Abuse and the Agency for Healthcare Research and Quality unrelated to this work.
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Abstract

Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics.

Process We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care.

Conclusion Actionable solutions identified to address core categories of EHR metric implementation challenges include: (1) maintaining broad stakeholder engagement, (2) reaching agreement on standardized measure definitions across vendors, (3) integrating clinician perspectives, and (4) addressing cognitive and EHR burden. Building upon the momentum of this workshop's outputs offers promise for overcoming barriers to implementing EHR use metrics.

Keywords

audit logs - metrics - electronic health records and systems - data validation and verification - ambulatory care/primary care - facilitators and barriers - use, administration, and maintenance

Note

The contents of this manuscript represent the view of the authors and do not necessarily reflect the position or policy of the U.S. Department of Veterans Affairs or the United States Government.


Protection of Human and Animal Subjects

No human subjects were involved in this work.




Publication History

Received: 19 July 2023

Accepted: 30 September 2023

Accepted Manuscript online:
06 October 2023

Article published online:
29 November 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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