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Published on: February 8, 2019
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Predicting long-term nursing home transfer from MI choice waiver program.
Xiaoting Wu1, Chenxi Li1, Kathleen Oberst2
1Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, USA.
Summary
Elderly individuals in Michigan
Area of Science:
- Gerontology
- Health Services Research
- Public Health
Background:
- Home and Community-Based Waiver Programs aim to support elderly individuals living at home.
- Identifying risk factors for long-term nursing home placement is crucial for resource allocation and care planning.
- The Michigan Home and Community-Based Waiver Program serves a significant elderly population.
Purpose of the Study:
- To identify demographic and clinical characteristics associated with a high risk of long-term nursing home placement among elderly waiver program participants.
- To inform policy decisions aimed at reducing nursing home admissions for this population.
Main Methods:
- Analysis of data from 8172 waiver clients aged 65 and older between October 1, 2010, and September 30, 2014.
- Utilized a proportional cause-specific hazards regression model to assess risk factors.
- Examined variables including race, history of long-term care use, mental disorders, and dependencies in daily activities.
Main Results:
- White race (HR: 2.76 vs. black, 1.77 vs. other races) was associated with increased risk of long-term nursing home placement.
- History of long-term care use (HR: 1.42), mental disorders (HR: 1.51), bathing dependency (HR: 1.43), and finance management dependency (HR: 1.73) significantly increased the hazard of placement.
- These factors indicate specific vulnerabilities within the waiver program population.
Conclusions:
- Specific characteristics, including race and functional dependencies, are significant predictors of long-term nursing home placement among elderly waiver participants.
- Findings can guide targeted interventions and support services to promote aging in place.
- Policy interventions should consider these risk factors to optimize waiver program effectiveness and reduce nursing home reliance.
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