Evaluation of precision medicine assessment reports of the Belgian healthcare payer to inform reimbursement decisions.

Int J Technol Assess Health Care

Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, Box 521, Leuven, Belgium.

Published: September 2020

Introduction: Precision medicines rely on companion diagnostics to identify patient subgroups eligible for receiving the pharmaceutical product. Until recently, the Belgian public health payer, RIZIV-INAMI, assessed precision medicines and companion diagnostics separately for reimbursement decisions. As both components are considered co-dependent technologies, their assessment should be conducted jointly from a health technology assessment (HTA) perspective. As of July 2019, a novel procedure was implemented accommodating for this joint assessment practice. The aim of this research was to formulate recommendations to improve the assessment in the novel procedure.

Methods: This study evaluated the precision medicine assessment reports of RIZIV-INAMI of the last 5 years under the former assessment procedure. The HTA framework for co-dependent technologies developed by Merlin et al. for the Australian healthcare system was used as a reference standard in this evaluation. Criteria were scored as either present or not present.

Results: Thirteen assessment reports were evaluated. Varying scores between reports were obtained for the domain establishing the co-dependent relationship between diagnostic and pharmaceutical. Domains evaluating the clinical utility of the biomarker and the cost-effectiveness performed poorly, whereas the budget impact and the transfer of trial data to the local setting performed well.

Recommendations: Based on these results we recommend three amendments for the novel procedure. (i) The implementation of the linked evidence approach when direct evidence of clinical utility is not present, (ii) incorporation of a bias assessment tool, and (iii) further specify guidelines for submission and assessment to decrease the variability of reported evidence between assessment reports.

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http://dx.doi.org/10.1017/S0266462320000604DOI Listing

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