Economic Issues

Economic Issues: Personalized medicine and drugs promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings attained by eliminating costs associated with failed treatment. One common method used to determine the economic effectiveness and impacts of this field are health claims on data for analyzing the potential value of pharmacogenomic testing in clinical practice. For example, in a set study, a model of alternate clinical strategies was evaluated using asthma patients' data from a retrospective health claims database to determine a potential cost offset. The likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy was estimated. The annualized per patient costs distributions was compared under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none.

RESULTS:

In the Test All strategy, more patients fall into lower cost ranges of the distribution. In the base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice.

CONCLUSIONS:

A general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. It is suggested that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.