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UNDERSTANDING AND ANTICIPATING LAG-TIME BIAS IN COST-EFFECTIVENESS STUDIES: THE ROLE OF TIME IN COST-EFFECTIVENESS ANALYSIS

Published online by Cambridge University Press:  30 March 2015

Gijs van de Wetering
Affiliation:
Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
Marcel Olde Rikkert
Affiliation:
Department of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands
Gert Jan van der Wilt
Affiliation:
Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands [email protected]
Eddy Adang
Affiliation:
Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands [email protected]

Abstract

Background: Timely provision of information on the cost-effectiveness of innovations in health care becomes more and more important, resulting in increasing pressure on researchers to provide proof of cost-effectiveness in a short time frame. However, most of these innovations require considerable time and effort to optimally implement leading to a biased “steady state” cost-effectiveness outcome. As decision makers in health care predominantly have a short-term focus, the discrepancy between short-term study outcomes and long-term cost-effectiveness may very well lead to misguided decisions about the adoption of innovations in health care.

Methods: Factors such as learning effects, capacity constraints, and delayed time to benefit are all related to a short-run timeframe and result in inefficiencies during the implementation of an innovation. These factors and the mechanisms by which they influence the cost-effectiveness outcome are explained for three different types of healthcare innovations.

Results: As standard cost-effectiveness analysis assumes costs and effects to behave constant and representative for an innovation's entire economic lifetime, resulting cost-effectiveness outcomes might give a biased, and often overly pessimistic, reflection of the actual cost-effectiveness of an innovation. This is further amplified by the fact that short-run inefficiencies are most prevalent and impactful during an innovation's earliest stage of operation.

Conclusions: This study advocates to carefully take into account the different factors contributing to lag-time bias in the design and analysis of cost-effectiveness studies, and to communicate potential biases due to short-run inefficiencies to all stakeholders involved in the decision making process.

Type
Methods
Copyright
Copyright © Cambridge University Press 2015 

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