4.6 Review

Examining Equity Effects of Health Interventions in Cost-Effectiveness Analysis: A Systematic Review

Journal

VALUE IN HEALTH
Volume 24, Issue 1, Pages 136-143

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jval.2020.10.010

Keywords

distributional cost-effectiveness analysis; equity-informative cost-effectiveness analysis; equity weighting

Funding

  1. Institute for Healthcare Policy and Innovation (IHPI) Health Services Research Summer Student Fellowship
  2. Susan B. Meister Child Health Evaluation and Research (CHEAR) Center at the University of Michigan

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The study found that the number of applications of equity-informative cost-effectiveness analysis (CEA) is increasing, primarily evaluating disease prevention interventions, with equity impact analysis being the most common, and socioeconomic status and race/ethnicity being the most frequently used equity criteria. The majority of studies reported greater value in interventions after considering their distributional effects.
Objective: This systematic review aims to catalogue and describe published applications of equity-informative costeffectiveness analysis (CEAs). Methods: Following PRISMA guidelines, we searched Medline for English-language, peer-reviewed CEAs published on or before August 2019. We included CEAs that evaluated 2 or more alternatives; explicitly mentioned equity as a consideration or decision-making principle; and applied an equity-informative CEA method to analyze or examine at least 1 equity criterion in an applied CEA. We extracted data on selected characteristics and analyzed reporting quality using the CHEERS checklist. Results: Fifty-four articles identified through a search and bibliography reviews met the inclusion criteria. All articles were published on or after 2010, with 80% published after 2015. Most studies evaluated primary prevention interventions in disease areas such as cancer, infectious diseases, and cardiovascular disease. Equity impact analysis alone was the most common equity informative CEA (56%), followed by equity impact analysis with financial protection effects (30%). At least 11 different equity criteria have been used in equity-informative CEAs; socioeconomic status and race/ethnicity were used most frequently. Seventy-eight percent of studies reported finding greater value in an intervention after examining its distributional effects. Conclusion: The number of equity-informative CEAs is increasing, and the wide range of equity criteria, diseases, interventions, settings, and populations represented suggests that broad application of these methods is feasible but will require further refinement. Inclusion of equity into CEAs may shift the value of evaluated interventions and can provide crucial additional information for decision makers.

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