Cost-utility analysis (CUA) is widely used for health technology assessment; however, concerns exist that cost-utility analysts may suggest higher cost-effectiveness thresholds (CETs) to compensate for technologies of relatively lower value.
We explored whether selection of a CUA study’s CET was endogenous to estimated incremental cost-effectiveness ratios (ICERs).
We systematically reviewed the US cost-effectiveness literature between 2000 and 2017 where studies with explicit CET and ICERs were included. We classified the ratio of studies hypothesized to analyze cost-effective technologies at low CETs (i.e., less than $100,000/quality-adjusted life-year [QALY]) vs higher CETs (i.e., $100,000–$150,000/QALY) relative to their ICER, using a Chi square test to examine whether technologies that were cost effective at high CETs would still be cost effective at lower thresholds. We also performed fixed-effects linear regression exploring the associations between ICERs and reported CETs over time.
Among 317 ICERs reviewed: (A) 185 had an ICER < $50,000/QALY; (B) 53 had $50,000 ≤ ICER, < $100,000; (C) 20 had $100,000 ≤ ICER < $150,000; and (D) 59 had an ICER ≥ $150,000. Chi square testing showed a strong association (p < 0.001) between estimated ICER values and chosen CET, illustrating a lack of independence between the two. The regression analysis indicated that CETs have a baseline value of $52,000 and grow by $0.37 for each dollar increase in the estimated ICER.
Cost-effectiveness thresholds represent the hypothesis tests of typical CUAs. Our analysis highlights that most CUAs that cite high CETs also result in greater ICERs for the novel interventions that they investigate; thus, these interventions would otherwise not have been cost effective at lower CETs. Selection of a CET may come after the ICER is calculated to infer value that suits a hypothesis.
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William Padula is supported by a grant from the National Institutes of Health Office of Extramural Research (KL2 TR001854).
Conflicts of interest/competing interests
William Padula is a consultant for Monument Analytics and is on the scientific advisory board for Molnlycke Healthcare. Charles Phelps is a consultant for Merck, Pfizer, and Audentes Therapeutics. Hui-Han Chen has no conflicts of interest to declare.
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Our data are openly available in the published literature through MEDLINE. We have organized these data for public access in the Electronic Supplementary Material provided (Table e1), which aggregate data used for analysis in this study.
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Padula, W.V., Chen, HH. & Phelps, C.E. Is the Choice of Cost-Effectiveness Threshold in Cost-Utility Analysis Endogenous to the Resulting Value of Technology? A Systematic Review. Appl Health Econ Health Policy 19, 155–162 (2021). https://doi.org/10.1007/s40258-020-00606-4