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Related Experiment Videos

Using economic analyses for local priority setting : the population cost-impact approach.

Richard F Heller1, Islay Gemmell, Edward C F Wilson

  • 1Evidence for Population Health Unit, Division of Epidemiology and Health Sciences, University of Manchester, Manchester, UK. Dick.Heller@manchester.ac.uk

Applied Health Economics and Health Policy
|June 16, 2006
PubMed
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Population cost-impact analysis offers a new way to assess health interventions for specific communities. This method helps policymakers prioritize interventions based on local costs and benefits, outperforming traditional QALY approaches.

Area of Science:

  • Health economics
  • Public health policy
  • Decision analysis

Background:

  • Standard economic analysis methods may not adequately address local decision-making needs for specific populations.
  • A novel three-step methodology, 'population cost-impact analysis', is introduced to provide a population-specific perspective on intervention costs and benefits.
  • This approach contrasts with the QALY method by obtaining policy-maker preferences in the final step, after quantifying benefits.

Purpose of the Study:

  • To describe and apply the population cost-impact analysis methodology.
  • To compare the effectiveness and cost-impact of beta-blocker use and smoking cessation interventions post-myocardial infarction.
  • To evaluate policy-maker preferences for interventions based on population cost-impact versus QALYs.

Main Methods:

Related Experiment Videos

  • Population cost-impact analysis was applied to beta-blocker use and smoking cessation interventions in a hypothetical English population of 100,000.
  • Intervention impacts were calculated in terms of deaths prevented and life-years gained.
  • Twenty-two public health professionals ranked interventions using provided population cost-impact and QALY data.

Main Results:

  • Implementing best practices for beta-blockers and smoking cessation could prevent 11 and 4 deaths, respectively, in a population of 100,000.
  • The cost per event prevented or life-year gained was lower for beta-blockers compared to smoking cessation.
  • Public health professionals showed a greater inclination to rank interventions based on population cost-impact data over QALYs.

Conclusions:

  • Population cost-impact analysis effectively presents intervention benefits and costs from a specific population's viewpoint, aiding local prioritization.
  • The method allows for the valuation of benefits after quantification, incorporating local prioritization issues.
  • This approach offers a valuable tool for local policymakers by identifying costs and benefits for defined populations.