Abstract

This study examined the optimization of formulary decisions concerning the selection of therapeutic options for reimbursement. It sought to identify an appropriate procedure to facilitate formulary decision making and guide healthcare policy in satisfying multiple therapeutic objectives representing an acceptable level of healthcare outcomes to be achieved with respect to the values and preferences of stakeholders. Multiattribute decomposition measurement and goal-programming methods were combined to optimize the selection of antiretroviral agents used in the treatment of HIV-1 infection. The case study method employed focused specifically on the antiretroviral treatment of an asymptomatic, treatment-naive HIV infected population with regard to the achievement of defined therapeutic objectives, and subject to clinical management decision constraints. The research questions were studied through the development and validation of a goal programming formulary decision model specific to the selection of evidence-based antiretroviral pharmacotherapy aimed at optimizing health outcomes through formulary reimbursement policies. The optimization of health outcomes was defined in terms of maximizing the achievement of therapeutic objectives. This study identified an optimal formulary selection reimbursement policy, determined its corresponding funding requirements, and quantified the tradeoffs made in defining the patient-specific optimal therapeutic selection under conditions of unrestricted cost-based reimbursement. The study also examined the potential impact of restricted drug formulary reimbursement policies on the maximal achievement of therapeutic objectives and related health outcomes by quantifying the magnitude and extent of tradeoffs required to compensate for shifting optimal solutions when progressively restricted cost-based constraints on reimbursement were introduced.