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Decision analysis for resource allocation in health care

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JournalJournal of Health Services Research & Policy
DatePublished - Oct 2008
Issue numberSuppl 3
Volume13
Number of pages8
Pages (from-to)23-30
Original languageEnglish

Abstract

This paper addresses the use of economic evaluation to inform resource allocation decisions within health care systems about which interventions to reimburse and whether additional research should be funded. A social decision-making view of economic evaluation, that is to maximize health gains subject to an exogenous budget constraint, is adopted.

A brief overview of the components of an economic evaluation is presented. Particular attention is paid to how uncertainty is inherent to decisions about resource allocation, the consequences of that uncertainty and how it can be incorporated informatively into economic evaluation. A Bayesian approach to uncertainty is used as it meets the needs of social decision-making, allowing analysts to quantify the probability that an intervention is cost-effective given the available evidence and to quantify the expected value of further research.

The discussion covers methods to represent parameter and structural uncertainty and considers the role of formal elicitation of expert judgements. The association between decisions to approve interventions for reimbursement and decisions about future research funding, and how value of information analysis can be used to formalize this link, is explained.

Recent developments in the UK highlight the evolving policy environment for economic evaluation, such as the Cooksey report on the funding of UK health research, the review of the Pharmaceutical Price Regulation Scheme by the Office of Fair Trading and the update of the methodological guidelines issued by the National Institute for Health and Clinical Excellence. The paper concludes by describing ongoing methodological work designed to meet the challenges of undertaking decision analysis for resource allocation in health care. Journal of Health Services Research & Policy Vol 13 Suppl 3, 2008: 23-30 (C) The Royal Society of Medicine Press Ltd 2008

    Research areas

  • CLINICAL-TRIAL DESIGN, EXPECTED VALUE, MODELS, INFORMATION, UNCERTAINTY, RATIOS, VALUES

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