Collection of health-economic data alongside clinical trials: is there a future for piggyback evaluations?
OBJECTIVE
The objective of this article is to discuss issues surrounding the conduct of "piggyback evaluations," in which health-economic data are collected within an otherwise typical clinical trial.


METHODS
We review the methodologic literature on piggyback economic evaluations, as well as selected empiric studies. We summarize the challenges encountered in the conduct of these studies, alternative ways of addressing these challenges, and their future role in pharmacoeconomic research.


RESULTS
Piggyback evaluations have certain advantages over other types of pharmacoeconomic studies. An economic evaluation can benefit from the experimental design that maximizes the trial's internal validity, and it is often more practical to collect economic data alongside a trial rather than to fund a stand-alone economic study. However, piggyback evaluations are subject to problems deriving from the competing nature of clinical versus economic study objectives, which can give rise to tension in such fundamental aspects of study design as the selection of study subjects and sites; the extent of protocol-mandated health-care services; and the determination of sample size, length of follow-up, and the study comparator(s). Many solutions have been put forth in the literature to address these challenges.


CONCLUSIONS
Piggyback evaluations can be an appropriate means to measure the economic impact of medical interventions, provided that the methodologic challenges are acknowledged and addressed within the context of each individual study. As long as a desire for patient-level data from clinical trials exists, there will be a need for piggyback economic evaluations in the future.
O'Sullivan
Amy K
AK
Innovus Research (US) Inc., Medford, MA, USA.
Thompson
David
D
Drummond
Michael F
MF
D002985:Clinical Protocols; D003625:Data Collection / Q000379:methods / Q000592:standards / Q000639:trends; D003627:Data Interpretation, Statistical; D004311:Double-Blind Method; D016903:Drug Monitoring; D017850:Economics, Pharmaceutical / Q000458:organization & administration*; D005544:Forecasting; D006295:Health Resources / Q000191:economics / Q000706:statistics & numerical data; D006301:Health Services Needs and Demand; D006302:Health Services Research / Q000458:organization & administration*; D006801:Humans; D015337:Multicenter Studies as Topic; D009937:Organizational Objectives; D010349:Patient Compliance / Q000523:psychology; D018579:Patient Selection; D016032:Randomized Controlled Trials as Topic / Q000639:trends; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards / Q000639:trends; D018401:Sample Size; D013997:Time Factors