Development and Validation of the Modified Patient-Centered Medical Home Assessment for the Comprehensive Primary Care Initiative

被引:5
作者
Poznyak, Dmitriy [1 ]
Peikes, Deborah N. [1 ]
Wakar, Breanna A. [2 ]
Brown, Randall S. [1 ]
Reid, Robert J. [3 ,4 ]
机构
[1] Mathematica Policy Res, 600 Alexander Pk Dr, Princeton, NJ 08540 USA
[2] Mathematica Policy Res, Washington, DC USA
[3] Univ Toronto, Trillium Hlth Partners, Mississauga, ON, Canada
[4] Univ Toronto, Inst Hlth Policy Management & Evaluat, Mississauga, ON, Canada
关键词
Psychometrics; survey research and questionnaire design; quality of care; patient safety; quality improvement; report cards; CONFIRMATORY FACTOR-ANALYSIS; MEASUREMENT INVARIANCE;
D O I
10.1111/1475-6773.12673
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
ObjectiveTo describe the modified Patient-Centered Medical Home Assessment (M-PCMH-A) survey module developed to track primary care practices' care delivery approaches over time, assess whether its underlying factor structure is reliable, and produce factor scores that provide a more reliable summary measure of the practice's care delivery than would a simple average of question responses. Data Sources/Study SettingSurvey data collected from diverse practices participating in the Comprehensive Primary Care (CPC) initiative in 2012 (n=497) and 2014 (n=493) and matched comparison practices in 2014 (n=423). Study DesignConfirmatory factor analysis. Data CollectionThirty-eight questions organized in six domains: Access and Continuity of Care, Planned Care for Chronic Conditions and Preventive Care, Risk-Stratified Care Management, Patient and Caregiver Engagement, Coordination of Care across the Medical Neighborhood, and Continuous Data-Driven Improvement. Principal FindingsConfirmatory factor analysis suggested using seven factors (splitting one domain into two), reassigning two questions to different domain factors, and removing one question, resulting in high reliability, construct validity, and stability in all but one factor. The seven factors together formed a single higher-order factor summary measure. Factor scores guard against potential biases from equal weighting. ConclusionsThe M-PCMH-A can validly and reliably track primary care delivery across practices and over time using factors representing seven key components of care as well as an overall score. Researchers should calculate factor loadings for their specific data if possible, but average scores may be suitable if they cannot use factor analysis due to resource or sample constraints.
引用
收藏
页码:944 / 973
页数:30
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