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Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization

An Analytic Approach

Bibliographic Data

ID9103296
AuthorsNicholas K Schiltz (0000-0003-0122-6477, Department of Epidemiology & Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH, corresponding author), D F Warner (0000-0002-8658-2237, University of Nebraska–Lincoln), Jiayang Sun (0000-0002-0870-7014, Department of Epidemiology & Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH, corresponding author), Paul M Bakaki (0000-0002-3482-2884, Department of Epidemiology & Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH, corresponding author), Avi Dor (0000-0003-4475-4333, Department of Health Policy and Management, George Washington University Milken Institute School of Public Health, Washington, DC), Charles W Given (0000-0001-7478-2621, Michigan State University), Kurt C Stange (0000-0002-2189-0191, Department of Epidemiology & Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH, corresponding author), Siran M Koroukian (0000-0002-8106-9581, Department of Epidemiology & Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH, corresponding author)
Year2017
Volume55
Issue3
Pages276-284
Publication date2017-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000000660
PMID27753745
OpenAlexW2528917343
LanguageEN
Citations received9
References cited22

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

Activities of daily living · Disease · Environmental health · Health care · Multimorbidity · Physical therapy · Population · Quartile · Chronic Disease Management Strategies · Demography · Diabetes Management and Education · Medicine · Primary Care and Health Outcomes · Gerontology

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Unique citing works9
Citations per year1,13
Citation span2018 - 2023 (6)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 9

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