• Define the different elements of pharmacoeconomic analysis: costs, benefits, perspective, cost-effectiveness plane, ECHO model, utility weights and quality-adjusted life years (QALYS), and discounting.
• Identify the different pharmacoeconomic analyses available: cost-minimization analysis, cost–benefit analysis, cost-effectiveness analysis, and cost–utility analysis.
• Know the elements of a decision model: decision nodes, chance nodes, and terminal nodes.
• Identify and interpret the results of a one-way sensitivity analysis, two-way sensitivity analysis, and probabilistic sensitivity analysis, and cost-effectiveness acceptability curve.
• Determine why pharmacoeconomics is needed when utilizing pharmacogenomics in clinical practice.

Economics is the study of choosing a strategy amid limited resources or scarcity.1 In health care, there is limited resources for all the medical needs of patients. Therefore, a formal evaluation into the costs and benefits of drugs, interventions, and programs needs to be assessed in order to efficiently and equitably distribute limited resources. Pharmacoeconomics is the quantitative assessment of the costs and benefits associated with a treatment strategy.2 Similar to traditional economics, pharmacoeconomics assess the choices that a decision maker selects and the cascading costs and outcomes associated with that choice. What distinguishes pharmacoeconomics from traditional economics is the assessment of health weighted by costs. In economics, decision makers are only interested in the overall costs associated with a choice or strategy, whereas, in pharmacoeconomics, costs are weighed by the benefits or outcomes associated with the treatment strategy. Treatment strategy can be a health care program to prevent chronic disease, it could represent a new molecular entity (NME) entering the market, or it can represent a new diagnostic test that can improve outcomes or avoid adverse events. In either case, pharmacoeconomics provides a scientific and quantitative method for estimating the value of a treatment strategy weighted by the costs. There are many facets within pharmacoeconomics, of which one of the most promising is pharmacogenomic evaluation.

Costs of whole genome testing have decreased exponentially since 2008, 5 years after the first draft of the human genome was sequenced by the US Department of Energy and the National Institutes of Health (Table 10–1).3 It took 13 years for the first draft to be officially completed, which cost over $13 billion.3 It is estimated that by 2013, whole genome testing could cost as little as$100 as prices of reagents drop and the speed of sequencing technology grows.4 Currently, it is unknown how whole genome testing will affect the application of pharmacogenomics into clinical practice. Regardless, the information due to the advancements made through the Human Genome Project (HGP) has given us a basis by which we continue to understand how genetics affects disease, traits, and metabolism of medications. Obviously it is not feasible to test every patient's genome. Therefore, methods are used to scan known areas of the genome for variations and are usually limited to scanning hundreds or thousands of base pairs. This type of technology allows for quicker and less costly method to identify mutations.

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