Predicting nursing home placement among home- and community-based services program participants

Area of Science:

• Gerontology
• Health Services Research
• Public Health Policy

Background:

• Publicly funded care management programs aim to prevent long-term care placement for high-risk Medicaid beneficiaries.
• Identifying risk factors and effective services is crucial for resource allocation in these programs.

Purpose of the Study:

• Develop a predictive model for long-term nursing home placement risk in a home- and community-based services program.
• Examine individual and program-level factors influencing nursing home placement.

Main Methods:

• Retrospective observational study using deidentified data from the Connecticut Home Care Program for Elders (2005-2010).
• Logistic regression models with random effects analyzed patient characteristics, service utilization, and prior facility admissions.
• Main outcomes: nursing home placement within 180 days or 1 year post-assessment.

Main Results:

• 11.4% of 10,975 participants experienced nursing home placement within a year.
• Risk factors included Alzheimer's disease, money management dependency, living alone, and prior skilled nursing facility stays.
• Personal care assistance services were linked to a 46% reduction in nursing home placement odds (C-statistic: 0.76).

Conclusions:

• A predictive model utilizing home- and community-based service program data demonstrates strong accuracy in identifying long-term nursing home placement risk.
• This model can effectively target high-risk individuals for tailored interventions, optimizing resource allocation and potentially reducing institutionalization.