Electronic health record use factors linked to efficiency and productivity: an explainable machine learning analysis
Implementing specific EHR use measures with distinct thresholds, such as inbox management and after-hours documentation, could help target interventions to enhance productivity, providing actionable insights to create balanced and efficient work environments that improve patient care and reduce EHR time.
Authors
- Andrew J. Loza (ORCID: https://orcid.org/0000-0002-1754-5133)
- Varada Vivek Khanna
- Huan Li (ORCID: https://orcid.org/0009-0003-0879-9152)
- Edward R Melnick
- Nate C. Apathy
- A Jay Holmgren
Institutions
- University of California, San Francisco (US)
- Yale University (US)
- Yale New Haven Health System (US)
- Department of Health Services (US)
- University of Maryland, College Park (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2026-01-06
- DOI
- https://doi.org/10.1093/jamiaopen/ooag018
- Primary Topic
- Electronic Health Records Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00