Exploring Uncertainty in Economic Evaluations of Drugs and Medical Devices: Lessons from the First Review of Manufacturers’ Submissions to the French National Authority for Health

Salah Ghabri (), Françoise F. Hamers and Jean Michel Josselin
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Salah Ghabri: Haute Autorité de Santé (HAS)
Françoise F. Hamers: Haute Autorité de Santé (HAS)
Jean Michel Josselin: University of Rennes 1 and CREM-CNRS

PharmacoEconomics, 2016, vol. 34, issue 6, No 8, 617-624

Abstract: Abstract Objectives The objective of this paper was to evaluate how uncertainty has been accounted for in the cost-effectiveness analyses (CEAs) submitted by manufacturers to the French National Authority for Health (HAS) and to identify recurring concerns in these submissions. Methods We used a cross-sectional design to evaluate manufacturers’ submissions from the beginning of the evaluation process in October 2013 to the end of May 2015 (n = 28). The sources of uncertainty attached to these CEAs were categorized and assessed. Relevant data were extracted independently by two assessors. Results Adherence to the HAS reference case was generally considered to be acceptable. Methodological uncertainty and parameter uncertainty were the sources of uncertainty that were most frequently explored by manufacturers. The quality of reporting of deterministic sensitivity analysis and probabilistic sensitivity analysis varied substantially across submissions, with a frequent lack of justification of the plausible range of parameter point estimates in 12 submissions (43 %). Structural uncertainty was explored much less frequently. Concerns related to omission of either important clinical events or relevant health states or extrapolation of the effects of the technology beyond the time horizon of the clinical trials were identified in 16 submissions (57 %). Conclusions This study presented a characterization of the treatment of uncertainty for the first 28 manufacturers’ submissions to the HAS. This work identified important concerns regarding the exploration of sources of uncertainty. The findings may help manufacturers to improve the quality of their submissions and may provide useful insights for extending guidelines on uncertainty analysis in CEAs submitted to the HAS.

Date: 2016
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DOI: 10.1007/s40273-016-0381-4

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