Development of a Common Data Model for a Multisite and Multiyear Study of Virtual Visit Implementation: A Case Study. Issue 4 (9th April 2023)

• Record Type: Journal Article
• Authors: Roblin, Douglas W.; Rubenstein, Kevin B.; Tavel, Heather M.; Goodrich, Glenn K.; Ritzwoller, Debra P.; Certa, Julia M.; Basra, Sundeep S.; Weinfield, Nancy S.; Cromwell, Lee A.; McDonald, Bennett; Davis, Teaniese L.; Gander, Jennifer C.; McCracken, Courtney E.
• Is Part Of: Medical care. Volume 61:Issue 4(2023)supplement 1
• Page Start: S54
• Page End: S61
• Publication Date: 2023-04-09
• Subjects: virtual visits -- electronic health records -- distributed data processing; Economics, Medical -- Periodicals; Insurance, Health -- Periodicals; Santé, Services de -- Administration -- Périodiques; Soins médicaux -- Périodiques; Medical economics -- Periodicals; Health insurance -- Periodicals; Medical economics -- United States -- Periodicals; Health insurance -- United States -- Periodicals; Comprehensive Health Care -- Periodicals; Personal Health Services -- Periodicals; Gezondheidszorg; Économie de la santé -- Périodiques; Santé, Services de -- Périodiques; Health insurance; Medical economics; United States; Periodicals; 362.10973
• DOI: 10.1097/MLR.0000000000001834
• Languages: English
• ISSNs: 0025-7079

Abstract

Abstract : Background/Objective: In multisite studies, a common data model (CDM) standardizes dataset organization, variable definitions, and variable code structures and can support distributed data processing. We describe the development of a CDM for a study of virtual visit implementation in 3 Kaiser Permanente (KP) regions. Methods: We conducted several scoping reviews to inform our study's CDM design: (1) virtual visit mode, implementation timing, and scope (targeted clinical conditions and departments); and (2) extant sources of electronic health record data to specify study measures. Our study covered the period from 2017 through June 2021. Integrity of the CDM was assessed by a chart review of random samples of virtual and in-person visits, overall and by specific conditions of interest (neck or back pain, urinary tract infection, major depression). Results: The scoping reviews identified a need to address differences in virtual visit programs across the 3 KP regionsto harmonize measurement specifications for our research analyses. The final CDM contained patient-level, provider-level, and system-level measures on 7, 476, 604 person-years for KP members aged 19 years and above. Utilization included 2, 966, 112 virtual visits (synchronous chats, telephone visits, video visits) and 10, 004, 195 in-person visits. Chart review indicated the CDM correctly identified visit mode on>96% (n=444) of visits, and presenting diagnosis on >91% (n=482) of visits. Conclusions: Upfront design and implementation of CDMs may be resource intensive. Once implemented, CDMs, like the one we developed for our study, provide downstream programming and analytic efficiencies by harmonizing, in a consistent framework, otherwise idiosyncratic temporal and study site differences in source data.