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      Determining the efficiency path to universal health coverage: cost-effectiveness thresholds for 174 countries based on growth in life expectancy and health expenditures

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      The Lancet Global Health
      Elsevier BV

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          Updating cost-effectiveness--the curious resilience of the $50,000-per-QALY threshold.

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            Country-Level Cost-Effectiveness Thresholds: Initial Estimates and the Need for Further Research

            Background Cost-effectiveness analysis can guide policymakers in resource allocation decisions. It assesses whether the health gains offered by an intervention are large enough relative to any additional costs to warrant adoption. When there are constraints on the health care system’s budget or ability to increase expenditures, additional costs imposed by interventions have an “opportunity cost” in terms of the health foregone because other interventions cannot be provided. Cost-effectiveness thresholds (CETs) are typically used to assess whether an intervention is worthwhile and should reflect health opportunity cost. Nevertheless, CETs used by some decision makers—such as the World Health Organization that suggested CETs of 1 to 3 times the gross domestic product (GDP) per capita—do not. Objectives To estimate CETs based on opportunity cost for a wide range of countries. Methods We estimated CETs based on recent empirical estimates of opportunity cost (from the English National Health Service), estimates of the relationship between country GDP per capita and the value of a statistical life, and a series of explicit assumptions. Results CETs for Malawi (the country with the lowest income in the world), Cambodia (with borderline low/low-middle income), El Salvador (with borderline low-middle/upper-middle income), and Kazakhstan (with borderline high-middle/high income) were estimated to be $3 to $116 (1%–51% GDP per capita), $44 to $518 (4%–51%), $422 to $1967 (11%–51%), and $4485 to $8018 (32%–59%), respectively. Conclusions To date, opportunity-cost-based CETs for low-/middle-income countries have not been available. Although uncertainty exists in the underlying assumptions, these estimates can provide a useful input to inform resource allocation decisions and suggest that routinely used CETs have been too high.
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              Thresholds for the cost–effectiveness of interventions: alternative approaches

              Abstract Many countries use the cost–effectiveness thresholds recommended by the World Health Organization’s Choosing Interventions that are Cost–Effective project (WHO-CHOICE) when evaluating health interventions. This project sets the threshold for cost–effectiveness as the cost of the intervention per disability-adjusted life-year (DALY) averted less than three times the country’s annual gross domestic product (GDP) per capita. Highly cost–effective interventions are defined as meeting a threshold per DALY averted of once the annual GDP per capita. We argue that reliance on these thresholds reduces the value of cost–effectiveness analyses and makes such analyses too blunt to be useful for most decision-making in the field of public health. Use of these thresholds has little theoretical justification, skirts the difficult but necessary ranking of the relative values of locally-applicable interventions and omits any consideration of what is truly affordable. The WHO-CHOICE thresholds set such a low bar for cost–effectiveness that very few interventions with evidence of efficacy can be ruled out. The thresholds have little value in assessing the trade-offs that decision-makers must confront. We present alternative approaches for applying cost–effectiveness criteria to choices in the allocation of health-care resources.
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                Author and article information

                Journal
                The Lancet Global Health
                The Lancet Global Health
                Elsevier BV
                2214109X
                June 2023
                June 2023
                : 11
                : 6
                : e833-e842
                Article
                10.1016/S2214-109X(23)00162-6
                37202020
                6558ea21-02e2-427f-8542-c5d5422fb2c4
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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