In this research the author develops a logistic regression model based on data from the Helsinki Heart Study (HHS) to estimate the five-year probability of coronary heart disease (CHD) events in persons with various risk factors. When coupled with information on the prevalence of those risk factors in a population and the costs of CHD therapy, the model can be used to estimate the five-year health and economic outcomes of different drug treatment strategies. Real time analysis can allow the decisionmaker to use the model to immediately evaluate the effects of changing model assumptions or input values such as the costs and the effectiveness of drug therapy and program demographics. Using Gemfibrozil for this exemplary case study, the author applies the National Cholesterol Education Program (NCEP) guidelines to a publicly funded state level program. Approximately 11 percent of the total population between the ages of 40 and 80 years would be treated with the drugs; approximately 8600 CHD events (representing approximately 9 percent of the events expected) would be prevented during the five-year treatment period, and the net cost to the program of following the NCEP guidelines would be about $116 million. By targeting patients using the risk model, and selecting only persons for whom the savings incurred by preventing CHD events offset the costs of drug treatment, we can devise alternate strategies that both provide equivalent health benefit and reduce program net expenditures. One such strategy would result in treating a differently selected group of approximately 11 percent of the total population with the drugs, preventing approximately 14,500 CHD events at a net cost of approximately $37 million. Another strategy that optimizes targeting of the population at risk for CHD achieves health benefits that are similar to the NCEP and demonstrates net program savings of approximately $8 million. These results reflect a five-year drug treatment horizon analogous to the HHS and are denominated in 1988 U.S. dollars. The model supports similar analyses of the consequences of therapy with the other pharmaceutical products currently available for dislipidemia therapy and can be readily expanded to include new pharmacologic treatments introduced in the future.