The use of economic analyses as they pertain to the practice of medicine has become increasingly commonplace. Driven by both changes to reimbursement incentives and the clinical practice of medicine, these analyses have the potential to answer many of the questions posed by the delivery of health care in a fiscally responsible era. As such, the health economist is faced with the increasingly important role of providing data and insights key to the deliberative process of comparing the costs and benefits of medical care. To this end, health economists rely on a number of tools in the practice of pharmacoeconomics. The most common tool is a cost-effectiveness analysis, which compares the clinical effects of alternative therapies (mortality, morbidity) to their net costs. A relatively new tool to the field of clinical economics, the cost per quality-adjusted life-year has the potential of becoming the gold standard in clinical economics for measuring clinical effects if further refinement to measurement technique is achieved. All of these tools have as their outcome the development of a medical decision model or decision tree. These decision trees have four components: disease outcome states; the probability of transition between disease states; the costs, financial benefits, and effects incurred by patients in each outcome state; and risk groups. Data from a wide range of sources, including randomized clinical trials and retrospective analyses of data collected from clinical practice settings, are drawn upon in the development of decision trees. Although economists can help design these models and document the costs and effects of alternative therapies, it is physicians and consumers who will ultimately have to make the decisions that recognize that spending resources on one disease or risk group decreases the resources available to treat other diseases or risk groups.