Abstract

Patient characteristics are modeled to predict long-term care placement. Data are derived from a random digit dial survey of individuals who had a relative receiving long-term care in Michigan. Multiple logistic regression was used to develop a model to predict selection of long-term care setting. Total activities of daily living contributed significantly to the model. One unit increases in activities of daily living increased the odds of selecting home care over nursing home care. Medical conditions did not contribute to the model, suggesting that in some cases meeting the needs of medical condition management may be possible through quality home care services. Respondents also reported higher satisfaction with care received at home compared to respondents with relatives in nursing homes. Because home-help/care funding is not as available, some people may be choosing nursing homes rather than home care despite higher satisfaction levels for care received at home.