%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 27
%N 
%P e68674
%T New Performance Measurement Framework for Realizing Patient-Centered Clinical Decision Support: Qualitative Development Study
%A Dullabh,Prashila
%A Zott,Courtney
%A Gauthreaux,Nicole
%A Swiger,James
%A Lomotan,Edwin
%A Sittig,Dean F
%+ Health Sciences Department, NORC at the University of Chicago, 1828 L Street NW, 9th Floor, Washington, DC, 20036, United States, 1 202 280 9294, dullabh-prashila@norc.org
%K patient-centered
%K measurement
%K health care
%K clinical decision support
%K artificial intelligence
%K AI
%D 2025
%7 30.4.2025
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: Patient-centered clinical decision support (PC CDS) exists on a continuum that reflects the degree to which its knowledge base, data, delivery, and use focus on patient needs and experiences. A new focus on value-based, whole-person care has resulted in broader development of PC CDS technologies, yet there is limited information on how to measure their performance and effectiveness. To address these gaps, there is a need for more measurement guidance to assess PC CDS interventions. Objective: This paper presents a new framework that incorporates patient-centered principles into traditional health IT and clinical decision support (CDS) evaluation frameworks to create a unified guide to PC CDS performance measurement. Methods: We conducted a targeted literature review of 147 sources on health IT, CDS, and PC CDS measurement and evaluation to develop the framework. Sources were reviewed if they included the sociotechnical components relevant to PC CDS, covered the full IT life cycle of PC CDS, and addressed measurement considerations at different user and system levels. We then validated and refined the measurement framework through key informant interviews with 6 experts in measurement, CDS, and clinical informatics. Throughout the framework development, we gathered feedback from a 7-member expert committee on the methods, findings, and the framework’s relevance and application. Results: The PC CDS performance measurement framework includes 6 domains: safe, timely, effective, efficient, equitable, and patient centered. The 6 domains contain 34 subdomains that can be selected to assess performance, depending on the type of PC CDS intervention or the specific research focus. In addition, there are 4 levels of aggregation at which subdomains can be measured (individual, population, organization, or IT system) that account for the multilevel impact of PC CDS. We provide examples of measures and approaches to patient centeredness for each subdomain, followed by 2 illustrative use cases demonstrating the framework application. Conclusions: This framework can be used by researchers, health system leaders, informaticians, and patients to understand the full breadth of performance and impact of PC CDS technology. The framework is significant in that it (1) covers the entire PC CDS life cycle, (2) has a direct focus on the patient, (3) covers measurement at different levels, (4) encompasses 6 independent but related domains, and (5) requires additional research and development to fully characterize all domains and subdomains. As the field of PC CDS matures, researchers and evaluators can build upon the framework to assess which components of PC CDS technologies work; whether PC CDS technologies are being used as anticipated; and whether the intended outcomes of delivering evidence-based, patient-centered care are being achieved. 
%R 10.2196/68674
%U https://www.jmir.org/2025/1/e68674
%U https://doi.org/10.2196/68674