Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization: an Analytic Approach
Published Date:Mar 2017
Source:Med Care. 55(3):276-284.
Pubmed Central ID:PMC5309172
Funding:KL2 TR000440/TR/NCATS NIH HHS/United States
R21 HS023113/HS/AHRQ HHS/United States
U48 DP005030/DP/NCCDPHP CDC HHS/United States
UL1 TR000439/TR/NCATS NIH HHS/United States
Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood.
To identify specific combinations of chronic conditions, functional limitations, and geriatric syndromes associated with direct medical costs and inpatient utilization.
Retrospective cohort study using the Health and Retirement Study (2008–2010) linked to Medicare claims. Analysis used machine learning techniques: classification and regression trees (CART) and random forest.
A population-based sample of 5,771 Medicare-enrolled adults age 65 and older in the United States.
Main covariates: self-reported chronic conditions (measured as none, mild, or severe), geriatric syndromes, and functional limitations. Secondary covariates: demographic, social, economic, behavioral, and health status measures. Outcomes: Medicare expenditures in the top quartile and inpatient utilization.
Median annual expenditures were $4,354, and 41% were hospitalized within two-years. The tree model shows some notable combinations: 64% of those with self-rated poor health plus ADL and IADL disabilities had expenditures in the top quartile. Inpatient utilization was highest (70%) in those age 77 – 83 with mild to severe heart disease plus mild to severe diabetes. Functional limitations were more important than many chronic diseases in explaining resource use.
The multimorbid population is heterogeneous and there is considerable variation in how specific combinations of morbidity influence resource use. Modeling the conjoint effects of chronic conditions, functional limitations, and geriatric syndromes can advance understanding of groups at greatest risk and inform targeted tailored interventions aimed at cost-containment.
Supporting Files:No Additional Files
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