Navigating time and uncertainty in health technology appraisal: would a map help?
Health care systems are increasingly under pressure to provide funding for innovative technologies. These technologies tend to be characterized by their potential to make valued contributions to patient health in areas of relative unmet need, high acquisition costs and great uncertainty in the evidence base on their actual impact on health. Decision makers are increasingly interested in linking reimbursement strategies to the degree of uncertainty in the evidence base and as a result, reimbursement for innovative technologies is frequently linked to some form of patient access or risk sharing scheme. However, current methods of economic evaluation provide only highly aggregate information on the distribution of risk between payers, patents and manufacturers. Reimbursement agencies would benefit from more detailed information on how uncertainty is distributed between costs and benefits; and over the short, medium and long term; to facilitate the assessment of the fairness of risk sharing under alternative payment strategies. In this paper we introduce the Net Benefit Probability Map as a method for providing decision makers with a less aggregate description of the distribution of costs, benefits and uncertainty over time, using data that is generated by standard probabilistic sensitivity analyses. We then show how it can be useful to decision makers considering (a) Only with Research Reimbursement decisions; (b) the use of differential discount rates; and (c) Patient access schemes.
|Date of creation:||2012|
|Date of revision:|
|Publication status:||Published in final form in Pharmacoeconomics, 2013, 31(9), pp.731-7.|
|Contact details of provider:|| Phone: Charles Thackrah Building, 101 Clarendon Road, LEEDS LS9 2LJ|
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- Peter S Hall & Richard Edlin & Samer Kharroubi & Walter Gregory & Christopher McCabe, 2011. "Expected Net Present Value of Sample Information: from burden to investment," Working Papers 1101, Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds.
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