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Overhage JM, Qeadan F, Choi EHE, Vos D, Kroth PJ. Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters. Appl Clin Inform 2024; 15:212-219. [PMID: 38508654 PMCID: PMC10954376 DOI: 10.1055/s-0044-1782228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 01/30/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Electronic health record (EHR) user interface event logs are fast providing another perspective on the value and efficiency EHR technology brings to health care. Analysis of these detailed usage data has demonstrated their potential to identify EHR and clinical process design factors related to user efficiency, satisfaction, and burnout. OBJECTIVE This study aimed to analyze the event log data across 26 different health systems to determine the variability of use of a single vendor's EHR based on four event log metrics, at the individual, practice group, and health system levels. METHODS We obtained de-identified event log data recorded from June 1, 2018, to May 31, 2019, from 26 health systems' primary care physicians. We estimated the variability in total Active EHR Time, Documentation Time, Chart Review Time, and Ordering Time across health systems, practice groups, and individual physicians. RESULTS In total, 5,444 physicians (Family Medicine: 3,042 and Internal Medicine: 2,422) provided care in a total of 2,285 different practices nested in 26 health systems. Health systems explain 1.29, 3.55, 3.45, and 3.30% of the total variability in Active Time, Documentation Time, Chart Review Time, and Ordering Time, respectively. Practice-level variability was estimated to be 7.96, 13.52, 8.39, and 5.57%, respectively, and individual physicians explained the largest proportion of the variability for those same outcomes 17.09, 27.49, 17.51, and 19.75%, respectively. CONCLUSION The most variable physician EHR usage patterns occurs at the individual physician level and decreases as you move up to the practice and health system levels. This suggests that interventions to improve individual users' EHR usage efficiency may have the most potential impact compared with those directed at health system or practice levels.
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Affiliation(s)
| | - Fares Qeadan
- Department of Public Health Sciences, Loyola University Chicago, Chicago, Illinois, United States
| | - Eun Ho Eunice Choi
- University of New Mexico School of Medicine, Albuquerque, New Mexico, United States
| | - Duncan Vos
- Division of Epidemiology and Biostatistics, Department of Biomedical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, Michigan, United States
| | - Philip J. Kroth
- Department of Biomedical Informatics, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, Michigan, United States
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Levy DR, Moy AJ, Apathy N, Adler-Milstein J, Rotenstein L, Nath B, Rosenbloom ST, Kannampallil T, Mishuris RG, Alexanian A, Sieja A, Hribar MR, Patel JS, Sinsky CA, Melnick ER. Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings. Appl Clin Inform 2023; 14:944-950. [PMID: 37802122 PMCID: PMC10686750 DOI: 10.1055/a-2187-3243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 09/30/2023] [Indexed: 10/08/2023] Open
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.
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Affiliation(s)
- Deborah R Levy
- Department of Veterans Affairs, VA Connecticut Healthcare System, West Haven, Connecticut, United States
- Section of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States
| | - Amanda J Moy
- Department of Biomedical Informatics, Columbia University, New York, New York, United States
| | - Nate Apathy
- National Center for Human Factors in Healthcare, MedStar Health Research Institute, Washington, District of Columbia, United States
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Iowa, United States
| | - Julia Adler-Milstein
- Department of Medicine, Center for Clinical Informatics and Improvement Research, University of California, San Francisco, California, United States
| | - Lisa Rotenstein
- Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
| | - Bidisha Nath
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States
| | - S Trent Rosenbloom
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States
| | - Thomas Kannampallil
- Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, United States
- Institute for Informatics, Data Science, and Biostatistics (I2DB), Washington University School of Medicine, St. Louis, Missouri, United States
| | - Rebecca G Mishuris
- Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
- Digital, Mass General Brigham, Boston, Massachusetts, United States
| | | | - Amber Sieja
- Department of General Internal Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States
| | - Michelle R Hribar
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, United States
| | - Jigar S Patel
- Oracle Corporation, Kansas City, Missouri, United States
| | | | - Edward R Melnick
- Section of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States
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Moy AJ, Withall J, Hobensack M, Yeji Lee R, Levy DR, Rossetti SC, Rosenbloom ST, Johnson K, Cato K. Eliciting Insights From Chat Logs of the 25X5 Symposium to Reduce Documentation Burden: Novel Application of Topic Modeling. J Med Internet Res 2023; 25:e45645. [PMID: 37195741 PMCID: PMC10233429 DOI: 10.2196/45645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/03/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023] Open
Abstract
BACKGROUND Addressing clinician documentation burden through "targeted solutions" is a growing priority for many organizations ranging from government and academia to industry. Between January and February 2021, the 25 by 5: Symposium to Reduce Documentation Burden on US Clinicians by 75% (25X5 Symposium) convened across 2 weekly 2-hour sessions among experts and stakeholders to generate actionable goals for reducing clinician documentation over the next 5 years. Throughout this web-based symposium, we passively collected attendees' contributions to a chat functionality-with their knowledge that the content would be deidentified and made publicly available. This presented a novel opportunity to synthesize and understand participants' perceptions and interests from chat messages. We performed a content analysis of 25X5 Symposium chat logs to identify themes about reducing clinician documentation burden. OBJECTIVE The objective of this study was to explore unstructured chat log content from the web-based 25X5 Symposium to elicit latent insights on clinician documentation burden among clinicians, health care leaders, and other stakeholders using topic modeling. METHODS Across the 6 sessions, we captured 1787 messages among 167 unique chat participants cumulatively; 14 were private messages not included in the analysis. We implemented a latent Dirichlet allocation (LDA) topic model on the aggregated dataset to identify clinician documentation burden topics mentioned in the chat logs. Coherence scores and manual examination informed optimal model selection. Next, 5 domain experts independently and qualitatively assigned descriptive labels to model-identified topics and classified them into higher-level categories, which were finalized through a panel consensus. RESULTS We uncovered ten topics using the LDA model: (1) determining data and documentation needs (422/1773, 23.8%); (2) collectively reassessing documentation requirements in electronic health records (EHRs) (252/1773, 14.2%); (3) focusing documentation on patient narrative (162/1773, 9.1%); (4) documentation that adds value (147/1773, 8.3%); (5) regulatory impact on clinician burden (142/1773, 8%); (6) improved EHR user interface and design (128/1773, 7.2%); (7) addressing poor usability (122/1773, 6.9%); (8) sharing 25X5 Symposium resources (122/1773, 6.9%); (9) capturing data related to clinician practice (113/1773, 6.4%); and (10) the role of quality measures and technology in burnout (110/1773, 6.2%). Among these 10 topics, 5 high-level categories emerged: consensus building (821/1773, 46.3%), burden sources (365/1773, 20.6%), EHR design (250/1773, 14.1%), patient-centered care (162/1773, 9.1%), and symposium comments (122/1773, 6.9%). CONCLUSIONS We conducted a topic modeling analysis on 25X5 Symposium multiparticipant chat logs to explore the feasibility of this novel application and elicit additional insights on clinician documentation burden among attendees. Based on the results of our LDA analysis, consensus building, burden sources, EHR design, and patient-centered care may be important themes to consider when addressing clinician documentation burden. Our findings demonstrate the value of topic modeling in discovering topics associated with clinician documentation burden using unstructured textual content. Topic modeling may be a suitable approach to examine latent themes presented in web-based symposium chat logs.
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Affiliation(s)
- Amanda J Moy
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Jennifer Withall
- School of Nursing, Columbia University, New York, NY, United States
| | - Mollie Hobensack
- School of Nursing, Columbia University, New York, NY, United States
| | - Rachel Yeji Lee
- School of Nursing, Columbia University, New York, NY, United States
| | - Deborah R Levy
- School of Medicine, Yale University, New Haven, CT, United States
- Veteran's Affairs Connecticut Health Care System, Pain, Research, Informatics, Multi-morbidities Education Center, West Haven, CT, United States
| | - Sarah C Rossetti
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
- School of Nursing, Columbia University, New York, NY, United States
| | - S Trent Rosenbloom
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, United States
| | - Kevin Johnson
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, United States
- Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States
| | - Kenrick Cato
- School of Nursing, Columbia University, New York, NY, United States
- Department of Emergency Medicine, Columbia University Irving Medical Center, New York, NY, United States
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, United States
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