Abstract
We identified client characteristics related to nursing home entry for 3,316 residents of six continuing care retirement communities with a longitudinal dataset that follows an initially healthy entry cohort for up to 15 years. The Cox Proportional Hazards Model was used for the analysis of survival data that includes censored data. We calculated hazard indices for residents with different characteristics to show the independent effect of these variables on the probability of nursing home entry. Seven variables emerged as statistically significant covariates: sex, marital status, roommate status, entry year into the community, entry age into the community, number of hospitalizations, and community of residence. The community of residence, which in large part reflects system effects on nursing home entry, was found to be the single most important variable explaining variance in the data. Tobit analysis was used to examine the factors associated with multiple nursing home entries and total days per year spent in a nursing home. With a few exceptions, most of the variables listed above were also significant correlates of multiple entries and total days per year spent in a nursing home.
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