Subscribe to RSS
DOI: 10.1055/a-2187-3243
Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings
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.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 maintenanceNote
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/)
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
-
References
- 1 Sinsky CA, Rule A, Cohen G. et al. Metrics for assessing physician activity using electronic health record log data. J Am Med Inform Assoc 2020; 27 (04) 639-643
- 2 Rule A, Melnick ER, Apathy NC. Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures. J Am Med Inform Assoc 2022; 30 (01) 144-154
- 3 Levy DR, Sloss EASA, Chartash D. et al. Reflections on the Documentation Burden Reduction AMIA Plenary Session through the Lens of 25 × 5. Appl Clin Inform 2023; 14 (01) 11-15
- 4 Melnick ER, Ong SY, Fong A. et al. Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis. J Am Med Inform Assoc 2021; 28 (07) 1383-1392
- 5 Melnick ER, Sinsky CA, Krumholz HM. Implementing measurement science for electronic health record use. JAMA 2021; 325 (21) 2149-2150
- 6 Kannampallil T, Adler-Milstein J. Using electronic health record audit log data for research: insights from early efforts. J Am Med Inform Assoc 2022; 30 (01) 167-171
- 7 Tran B, Lenhart A, Ross R, Dorr DA. Burnout and EHR use among academic primary care physicians with varied clinical workloads. AMIA Jt Summits Transl Sci Proc 2019; 2019: 136-144
- 8 Arndt BG, Micek MA, Rule A, Shafer CM, Baltus JJ, Sinsky CA. Refining vendor-defined measures to accurately quantify EHR workload outside time scheduled with patients. Ann Fam Med 2023; 21 (03) 264-268
- 9 Melnick ER, Nielson JA, Finnell JT. et al. Delphi consensus on the feasibility of translating the ACEP clinical policies into computerized clinical decision support. Ann Emerg Med 2010; 56 (04) 317-320
- 10 Nasa P, Jain R, Juneja D. Delphi methodology in healthcare research: how to decide its appropriateness. World J Methodol 2021; 11 (04) 116-129
- 11 Rossetti SC, Rosenbloom S, Levy DR. et al. 25 × 5 symposium drives ongoing efforts to reduce documentation burden on U.S. clinicians: final summary report 2021 . Accessed December 5, 2021 at: https://www.dbmi.columbia.edu/wp-content/uploads/2021/12/25×5-Summary-Report.pdf or https://brand.amia.org/m/dbde97860f393e1/original/25×5-Summary-Report.pdf
- 12 Hobensack M, Levy DR, Cato K. et al. 25 × 5 Symposium to reduce documentation burden: report-out and call for action. Appl Clin Inform 2022; 13 (02) 439-446
- 13 Baxter SL, Apathy NC, Cross DA, Sinsky C, Hribar MR. Measures of electronic health record use in outpatient settings across vendors. J Am Med Inform Assoc 2021; 28 (05) 955-959
- 14 Overhage JM, McCallie Jr D. Physician time spent using the electronic health record during outpatient encounters: a descriptive study. Ann Intern Med 2020; 172 (03) 169-174
- 15 Holmgren AJ, Downing NL, Bates DW. et al. Assessment of electronic health record use between US and non-US health systems. JAMA Intern Med 2021; 181 (02) 251-259
- 16 Moy AJ, Aaron L, Cato KD. et al. Characterizing multitasking and workflow fragmentation in electronic health records among emergency department clinicians: using time-motion data to understand documentation burden. Appl Clin Inform 2021; 12 (05) 1002-1013
- 17 Chen Y, Adler-Milstein J, Sinsky CA. Measuring and maximizing undivided attention in the context of electronic health records. Appl Clin Inform 2022; 13 (04) 774-777
- 18 Senathirajah Y, Kaufman DR, Cato KD, Borycki EM, Fawcett JA, Kushniruk AW. Characterizing and visualizing display and task fragmentation in the electronic health record: mixed methods design. JMIR Human Factors 2020; 7 (04) e18484