Abstract
BACKGROUND:
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.
OBJECTIVE:
The objective was to identify specific combinations of
chronic conditions, functional limitations, and geriatric syndromes associated
with direct medical costs and inpatient utilization.
DESIGN:
Retrospective cohort study using the Health and
Retirement Study (2008-2010) linked to Medicare claims. Analysis used
machine-learning techniques: classification and regression trees and random
forest.
SUBJECTS:
A population-based sample of 5771 Medicare-enrolled
adults aged 65 and older in the United States.
MEASURES:
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.
RESULTS:
Median annual expenditures were $4354, and 41% were
hospitalized within 2 years. The tree model shows some notable combinations:
64% of those with self-rated poor health plus activities of daily living and
instrumental activities of daily living disabilities had expenditures in the
top quartile. Inpatient utilization was highest (70%) in those aged 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.
CONCLUSIONS:
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.