Dr. Mullahy examined the use of Multiple Chronic Conditions (MCCs) data as an indicator of individual and population health, functioning, and well-being. He assessed whether this data can be used to establish metrics that will describe the status of, disparities in, and trajectories over time of population health.
- What is the relationship between chronic conditions and combinations of chronic conditions and their outcomes and determinants?
- Can an improved understanding of MCCs and MCC disparities lead to useful population health metrics?
- Develop innovative approaches for using a readily available data source to evaluate changing patterns in population health.
- Equip clinicians, policymakers, and other stakeholders with the information necessary to understand how to address multiple chronic conditions and improve population health.
This study is designed to develop a new measure of health outcomes, with the primary purpose being to devise and implement empirical strategies to summarize the structure of multivariate outcomes like MCCs. MCC outcomes centering on the importance of MCC patterns, as well as how chronic condition count metrics relate to corresponding patterns within the confines of the same empirical methodologies and data.
A variety of metrics and estimated statistical models were considered and assessed simultaneously and coherently in order to provide an analytical framework that accommodates analysis and reporting of a variety of MCC summary measures – patterns, counts, and other MCC-based metrics. This approach created a method for assessing SES disparities, undertaking projections, evaluating covariate-adjustments and computing "marginal effects" of health determinants on MCC outcomes.