Search

Objectives: Our study explores whether, and how, different methodological choices are associated with different health technology assessment (HTA) outcomes. We focus on the Federal Joint Committee (Gemeinsamer Bundesausschuss, G-BA) in Germany and the National Institute for Health and Care Excellence (NICE) in England. Both agencies may be considered as exemplars for the application of the principles of evidence-based medicine and the logic of cost-effectiveness, respectively. Methods: We extracted data from all publically available G-BA appraisals until April 2015, as well as all NICE single technology appraisals completed during this period. We compared HTA results for matched condition-intervention pairs by G-BA and NICE, and explored other factors including therapeutic area, clinical effectiveness and cost-effectiveness. Results: NICE issued guidance for 88 technologies (125 subgroups) and recommended 67/88 technologies (99/125 subgroups). G-BA completed 105 appraisals (226 subgroups) and determined additional benefit for 64/105 appraisals (90/226 subgroups). We identified 37 matched pairs; for 24/37 drugs, evaluations diverged. NICE recommended 78% (29/37) of technologies appraised, whereas G-BA confirmed additional benefit for 57% (21/37) only (p < 0.05). Conclusions: NICE evaluates new drugs more favorably than G-BA. However, our analysis suggests differences by therapeutic area. Results indicate that different methods are associated with systematic differences in HTA outcomes. [ABSTRACT FROM AUTHOR]

INTRODUCTION:Among economists, there is widespread agreement that the monetary valuation of health gains should reflect the preferences of those who will be affected by resource allocation decisions. In the context of Health Technology Assessments (HTAs), this view implies a need for reliable empirical estimates of the value of statistical life year (VSLY), which should provide a useful point of reference for cost benefit analyses.METHODS:We conducted a systematic review of the literature on the economic value of a statistical life (VSL). We searched in the EconBiz and EconLit databases for studies, which reported VSL estimates based on original research and were published between 1995 and 2015. We classified studies by methodology, that is, revealed preference (RP) or stated preference (SP; that is, CV, contingent valuation, or DCE (discrete choice experiment) approach, and by regional origin of data. We transformed VSL estimates into VSLY expressed in year 2014 Euros, using life expectancy tables for the populations studied, a real discount rate of 3 percent, national Consumer Price Indices for inflating, and purchasing power parities for currency conversion. In addition, we calculated ratios of VSLY to gross domestic product (GDP) per capita.RESULTS:Our search yielded 120 studies appropriate for inclusion. From these, we extracted a total of 132 VSL estimates (RP, n = 60; SP, n = 72). The median VSLY was 6.4 times GDP/capita. Transformed into Euro (2014), the median VSLY was EUR165,000 (mean, EUR217,000). We found significant differences by regional source of data (North American, median EUR272,000; European, EUR158,000) and by method (RP, EUR241,000; SP: CV, EUR117,000; DCE, EUR187,000). VSLY estimates were sensitive to discount rate.CONCLUSIONS:Our data indicate that VSLY estimates based on empirical data exceed benchmarks commonly used in the context of HTAs. However, inter-study variability, methodological limitations, and normative considerations, all suggest to exercise caution before translating this observation into actual policy. [ABSTRACT FROM AUTHOR]

INTRODUCTION:Evaluation of “value for money” is an important component of Health Technology Assessments (HTAs). It is often conceptualized as “cost effectiveness” or cost per (quality-adjusted) life year gained. Whether used in isolation or alongside further drivers of social value (such as priority for younger or more severely impaired patient groups, or for access to effective treatment, even if costly), for example within a multi-criteria decision analysis framework, any reference “value of a statistical life year” (VSLY) should be supported by empirical data capturing the preferences of the population(s) in question. Here we report results based on a systematic review of relevant European economic studies, which were published during the last two decades, that is, from 1995 to 2015.METHODS:Our literature search (using the EconBiz and EconLit databases, supplemented by an analysis of relevant reviews) identified fourty-one European studies providing original data, yielding a total of fourty-eight average estimates for the value of a statistical life (VSL, or fatality prevented). We classified studies by methodology, for example, revealed preference (RP) or stated preference (contingent valuation, CV; discrete choice experiment, DCE) approach. We transformed VSL estimates into VSLY expressed in year 2014 Euros, using the life expectancy of the populations studied, a real discount rate of 3 percent, the national Consumer Price Index (CPI) for inflating, and purchasing power parities for currency conversion. We calculated confidence intervals by means of nonparametric bootstrapping.RESULTS:The median VSLY was EUR158,000 (for RP studies, EUR218,000; DCE, EUR188,000; CV, EUR143,000); we did not identify studies using the human capital approach. Our VSLY estimates showed large heterogeneity, both by methodology and regional origin; thus the differences that we observed did not reach statistical significance.CONCLUSIONS:Our results suggest that the empirical willingness-to-pay for a statistical life year might be substantially higher than benchmarks currently used by the international HTA community. [ABSTRACT FROM PUBLISHER]