Confidence and Validity of Data

As in any other scientific endeavor, the validation of the database is as important as its interpretation; pharmacoeconomic variables require two degrees of confidence, i.e. in the accuracy and the validity of what has been measured.

Consider two opposite examples of pharmacoe-conomic measurement. In one case, patients could describe their impression of the impact of an intervention on their quality of life (QOL) following completion of a 2 week, open-label course of treatment. At the other extreme, a randomized, controlled trial (RCT), using a double-blind, placebo-controlled protocol and a 12 month follow-up in several hundred patients, could use a statistically validated QOL instrument. The results of the latter would probably inspire more confidence than the 'informal' scenario, all other things being equal. However, it does not mean that the answers given using the informal method are wrong, it simply requires an appreciation of the trade-offs involved in how data is collected. Furthermore, the former method might be of more use than the latter in exploratory pharmaceconomic research condicted in the earliest stages of drug development.

The RCT design, while often held as the gold standard, also has other problems. It is more costly, more time consuming, and not always ethical (12 months of placebo?). Some types of outcomes, such as compliance, do not lend themselves to double-blind designs because such designs mask one of the effects being measured. RCTs generally strive to maintain high levels of internal validity at the risk of reducing external validity. Biases to internal validity affect the accuracy of the results of the study, as they apply to those who participated in the study (e.g. patient selection bias, cross-over bias, and errors in measurement of outcomes). Biases to external validity affect how well the results may be generalized to the public at large. Obviously, the choice of study design must take potential biases into account. These factors are somewhat analogous for pharmacoeconomic and traditional clinical research.

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