The role of resource allocation models in selecting clinical preventive services.

OBJECTIVE: To demonstrate the potential value and current limitations of using resource allocation models for selecting health services. DESIGN: To identify the most efficient mix of preventive services that could be offered by a managed care organization (MCO) for a fixed budget, an optimization model (greatest number of life years saved) and a cost-effectiveness model (rank order of most to least cost effective) were developed. Because of the lack of cost-effectiveness analyses that met the study criteria, only 9 preventive services were selected to demonstrate each model. PATIENTS AND METHODS: The 2 models were applied to a hypothetical managed care population of 100,000 enrollees with age, sex, and risk distribution similar to that of the US population. Data for the input variables were obtained from cost-effectiveness studies of 9 preventive services. Model variables included the target population, percent of enrollees who received the preventive service, the cost of the preventive service, life years saved, and cost-effectiveness ratios. RESULTS: The models demonstrated that efficient allocation of finite resources can be achieved. When budgets are limited, different premises between the 2 models may yield different health consequences. However, as the budgets were increased, results from the 2 models were more closely aligned. CONCLUSIONS: Resource allocation models have the potential for assisting MCOs in selecting a set of preventive services that will maximize population health. Before this potential can be fully realized, additional methodological development and cost-effectiveness studies are needed. The use of resource allocation should be examined for selecting all healthcare services.