This Article Full Text (PDF) All Versions of this Article: 0272989X07312724v1 28/3/287    most recent References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Philips, Z. Articles by Palmer, S. Search for Related Content PubMed PubMed Citation Articles by Philips, Z. Articles by Palmer, S. Social Bookmarking                         What's this?

The Half-Life of Truth: What Are Appropriate Time Horizons for Research Decisions?

Centre for Health Economics, University of York, UK, che-teehta{at}york.ac.uk

Karl Claxton, DPhil

Centre for Health Economics, University of York, UK

Stephen Palmer, MSc

Centre for Health Economics, University of York, UK

Purpose. To evaluate alternative approaches taken to estimate the population that could benefit from research and to demonstrate that explicitly modeling future change leads to more appropriate estimates of the expected value of information (EVI). Methods. Existing approaches to estimating the population typically focus on the time horizon for decisions, employing seemingly arbitrary estimates of the appropriate horizon. These approaches implicitly use the time horizon as a proxy for future changes in technologies, prices, and information. Different approaches to quantifying the time horizon are explored, in the context of a stylized model, to demonstrate the impact of uncertainty in this estimate on EVI. An alternative approach is developed that explicitly models future changes in technologies, prices, and information and that demonstrates the impact on EVI estimates. Results. Explicitly modeling future changes means that the EVI for the decision problem may increase or decrease over time, but the EVI for the group of parameters that can be evaluated by current research tends to decline. The finite and infinite time horizons for the decision problem represent special cases (e.g., price shock or no changes, respectively). This type of analysis can be used to inform policy decisions relating to the timing of research. Conclusions. The value of information depends on future changes in technologies, prices, and evidence. Finite time horizons for decision problems can be seen as a proxy for the complex and uncertain process of future change. A more explicit approach to modeling these changes could provide a more appropriate basis for calculating EVI, but this raises a number of significant methodological and technical challenges.

Key Words: value of information • priority setting • research decisions.

This version was published on June 1, 2008

Medical Decision Making, Vol. 28, No. 3, 287-299 (2008)
DOI: 10.1177/0272989X07312724


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				S. Griffin, K. Claxton, and M. Sculpher Decision analysis for resource allocation in health care J Health Serv Res Policy, October 1, 2008; 13(suppl_3): 23 - 30. [Abstract] [Full Text] [PDF]