Valuing Meta-Health Effects for Use in Economic Evaluations to Inform Reimbursement Decisions: A Review of the Evidence
- Publication Type:
- Journal Article
- Citation:
- PharmacoEconomics, 2017, 35 (3), pp. 347 - 362
- Issue Date:
- 2017-03-01
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| rdal_pharmacoeconomics.pdf | Published Version | 780.07 kB |
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© 2016, Springer International Publishing Switzerland. Objective: This review explores the evidence from the literature regarding how meta-health effects (effects other than health resulting from the consumption of health care) are valued for use in economic evaluations. Methods: A systematic review of the published literature (the EMBASE, MEDLINE, PsycINFO, CINAHL, EconLit and SocINDEX databases were searched for publications in March 2016, plus manual searching) investigated the associations between study methods and the resulting values for meta-health effects estimated for use in economic evaluations. The review considered which meta-health effects were being valued and how this differed by evaluation approach, intervention investigated, source of funds and year of publication. Detailed reasons for differences observed between values for comparable meta-health effects were explored, accounting for the method of valuation. Results: The search of the literature revealed 71 studies of interest; 35% involved drug interventions, with convenience, information and process of care the three meta-health effects most often investigated. Key associations with the meta-health effects were the evaluation method, the intervention, and the source of funds. Relative values for meta-health effects ranged from 0.9% to 68% of the overall value reported in a study. For a given meta-health effect, the magnitude of the effect evaluated and how the meta-health effect was described and framed relative to overall health explained the differences in relative values. Conclusions: Evidence from the literature shows variability in how meta-health effects are being measured for use in economic evaluations. Understanding the sources of that variability is important if decision makers are to have confidence in how meta-health effects are valued.
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