Search

Can community services be made more effective in reducing nursing home use through their management of their mix and allocation? To test this idea, we used data from the National Long-Term Care Channeling Demonstration to estimate logistic regression models relating the use of various types of community services to nursing home use. We then used these estimates to form an objective function for a mathematical optimization procedure which minimizes total expected population nursing home use as a function of community service use, subject to a total expenditure constraint. We find through this simulated reallocation that, in theory, significant reductions in nursing home use can be produced without increasing total community expenditures.

The cost-effectiveness of community long-term care services as an alternative to nursing home care is discussed using an integrated model utilizing the principles of decision making and marginal cost analysis. The model allows a more general and flexible empirical estimation of the parameters by using individuals as the units of analysis and analyzing the various types of community services separately.

Several studies have looked at nursing home admissions, but most have measured only life-table data rather than individual characteristics as predictors of who is likely to enter a nursing home. Studies summarized in this article have found several predictors, particularly advanced age, to be useful. Only one found that women were at greater risk than men, but having a spouse or roommate reduced risk for both sexes. In general, mental or physical impairments or serious illness affecting the ability to carry out daily activities increased the likelihood of institutionalization. Analysis of 3,332 individuals admitted to nursing homes over a one-year period determined some of the individual characteristics of these patients. Three categories of factors were considered: need, enabling, and predisposing. Need factors included mental and physical disabilities that prevented the person from carrying out daily activities. An enabling factor was the supply of hospital beds in an area. Informal caregiving did not affect probability of admission, but was more likely to be associated with a lower probability of discharge, perhaps due to caregiver burnout. Income did not affect entry, but a higher income was associated with exit from the nursing home. Of the enabling factors, race and ethnicity were important, with blacks and Hispanics less likely to enter a nursing home than whites, either because of different values among those communities, or because of discrimination on the part of nursing homes. Blacks were also less likely to leave, once admitted. Homeowners were more likely to leave, either for financial reasons (heirs not wanting to draw down assets) or because the person had a place to go in the community. The ability to identify these individual and aggregate characteristics associated with greater likelihood of nursing home entry is a useful tool in planning and case management in targeting services to those most at risk, as well as in long-term planning and forecasting. (Consumer Summary produced by Reliance Medical Information, Inc.)