A systems model of the cost impact of new HIV/AIDS therapies: Applications of a Markov process

The primary objectives of this research were to (1) estimate survival functions and the natural history of patients infected with human immunodeficiency virus who are using antiretroviral medication with a protease inhibitor and those who are under treatment protocols without protease inhibitors, and (2) estimate average lifetime treatment costs of infected patients for both drug regimens. A secondary objective was to provide a step by step discussion of the applicability of a Markov process in modeling survival and cost profiles of acquired immunodeficiency syndrome, a complex set of diseases, to managed care organizations. Data used in this study were collected using two techniques: expert physician panel interviews and a literature search. The transition rates for patients moving from one disease state to another were obtained from both sources. Cost estimates were calculated predominantly from published literature. The fundamental matrix solution of a Markov chain model was used to estimate survival functions, natural history profiles, and lifetime costs of therapy for HIV-infected patients. The research was conducted from the perspective of a managed health care organization. Results indicated that protease inhibitors significantly improved overall survival of infected patients by deterring the progression of disease and onset of various opportunistic infections. Lifetime costs of treatment, however, were substantially higher for treatment protocols using protease inhibitors as one of the components of recommended combination retroviral therapy. Estimates obtained from this study also indicated that unless significant reductions in high resource intensive events such as hospitalization can be achieved, protease inhibitors might not be cost efficient in treating HIV-infected patients. Lastly, this research showed that Markov modeling techniques can offer valuable benchmarks for both clinical and economic decision making in planning disease intervention to improve health outcomes and evaluate costs