Online Program

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Wednesday, January 8
Wed, Jan 8, 10:30 AM - 12:15 PM
West Coast Ballroom
Quasi-Experimental Methods in Health Policy

WITHDRAWN - A Bayesian difference-in-differences framework for measuring the impact of primary care redesign on diabetes outcomes (307790)

Brad Carlin, Counterpoint Statistical Consulting 
Caroline Carlin, University of Minnesota  
Eric Frazer Lock, University of Minnesota 
*James Paul Normington, University of Minnesota  
Kevin Peterson, University of Minnesota 

Keywords: Primary care redesign, difference-in-differences, patient-centered medical home, Bayesian hierarchical modeling, diabetes, errors in covariates

Although national measures of the quality of diabetes care delivery demonstrate improvement, progress has been slow. In 2008, the Minnesota legislature endorsed the patient-centered medical home (PCMH) as the preferred model for primary care redesign. In this work, we investigate the effect of PCMH-related clinic redesign and resources on diabetes outcomes from 2008 to 2012 among Minnesota clinics certified as PCMHs by 2011 by using a Bayesian framework for a continuous difference-in-differences model. Data from the Physician Practice Connections-Research Survey were used to assess a clinic's maturity in primary care transformation, and diabetes outcomes were obtained from the MN Community Measurement (MNCM) program. These data have several characteristics that must be carefully considered from a modeling perspective, including the inability to match patients over time, the potential for dynamic confounding, and the hierarchical structure of clinics. An ad-hoc analysis suggests a significant correlation between PCMH-related clinic redesign and resources on diabetes outcomes, but this effect is not detected after accounting for different sources of variability and confounding.