A Bayesian Difference-in-Difference Framework for the Impact of Primary Care Redesign on Diabetes Outcomes.
James NormingtonEric F LockCaroline CarlinKevin PetersonBradley CarlinPublished in: Statistics and public policy (Philadelphia, Pa.) (2019)
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; however, this effect is not detected after properly accounting for different sources of variability and confounding. Supplementary materials for this article are available online.
Keyphrases
- primary care
- glycemic control
- type diabetes
- cardiovascular disease
- healthcare
- quality improvement
- end stage renal disease
- general practice
- chronic kidney disease
- electronic health record
- newly diagnosed
- ejection fraction
- mental health
- emergency department
- cross sectional
- big data
- peritoneal dialysis
- weight loss
- machine learning
- patient reported outcomes
- climate change
- drinking water
- ionic liquid