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      Can requests for real-world evidence by the French HTA body be planned? An exhaustive retrospective case–control study of medicinal products appraisals from 2016 to 2021

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          Abstract

          Objectives

          In France, decisions for pricing and reimbursement for medicinal products are based on appraisals performed by the National authority for health ( Haute Autorité de Santé (HAS)). During the appraisal process, additional real-world evidence can be requested as “Post-Registration Studies” (PRS) when there are uncertainties in evidence that could be resolved by additional data collection. To facilitate PRS planning, a retrospective exploratory analysis was conducted to identify the characteristics of medicinal products associated with a PRS request.

          Methods

          This analysis encompassed all appraisals finalized between January 1, 2016 and December 31, 2021 and compared products for which the appraisal led to a PRS request with those that did not.

          Results

          Six hundred positive opinions for reimbursement were identified, with a PRS request present in 17 percent (n = 103) of cases. The independent characteristics associated with a PRS request were a mild or moderate clinical benefit score, a major to moderate or minor clinical added value score, previous availability under an early access program, and certain therapeutic areas (neurology, pulmonology, and endocrinology). These findings suggest two different profiles of PRS requests: (i) products for which there is uncertainty in the size of the clinical benefit and (ii) innovative products for which a substantial benefit is expected but uncertainties persist.

          Conclusions

          These results will assist health technology developers to better anticipate data generation to promptly address uncertainties identified by HAS. It may also help HAS and other assessment agencies to work together to improve postlaunch evidence generation according to the characteristics of the medicinal products.

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          Most cited references26

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          Adjusting for multiple testing--when and how?

          Multiplicity of data, hypotheses, and analyses is a common problem in biomedical and epidemiological research. Multiple testing theory provides a framework for defining and controlling appropriate error rates in order to protect against wrong conclusions. However, the corresponding multiple test procedures are underutilized in biomedical and epidemiological research. In this article, the existing multiple test procedures are summarized for the most important multiplicity situations. It is emphasized that adjustments for multiple testing are required in confirmatory studies whenever results from multiple tests have to be combined in one final conclusion and decision. In case of multiple significance tests a note on the error rate that will be controlled for is desirable.
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            Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France.

            In 1999, French legislators asked health insurance funds to develop a système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) [national health insurance information system] in order to more precisely determine and evaluate health care utilization and health care expenditure of beneficiaries. These data, based on almost 66 million inhabitants in 2015, have already been the subject of numerous international publications on various topics: prevalence and incidence of diseases, patient care pathways, health status and health care utilization of specific populations, real-life use of drugs, assessment of adverse effects of drugs or other health care procedures, monitoring of national health insurance expenditure, etc. SNIIRAM comprises individual information on the sociodemographic and medical characteristics of beneficiaries and all hospital care and office medicine reimbursements, coded according to various systems. Access to data is controlled by permissions dependent on the type of data requested or used, their temporality and the researcher's status. In general, data can be analyzed by accredited agencies over a period covering the last three years plus the current year, and specific requests can be submitted to extract data over longer periods. A 1/97th random sample of SNIIRAM, the échantillon généraliste des bénéficiaires (EGB), representative of the national population of health insurance beneficiaries, was composed in 2005 to allow 20-year follow-up with facilitated access for medical research. The EGB is an open cohort, which includes new beneficiaries and newborn infants. SNIIRAM has continued to grow and extend to become, in 2016, the cornerstone of the future système national des données de santé (SNDS) [national health data system], which will gradually integrate new information (causes of death, social and medical data and complementary health insurance). In parallel, the modalities of data access and protection systems have also evolved. This article describes the SNIIRAM data warehouse and its transformation into SNDS, the data collected, the tools developed in order to facilitate data analysis, the limitations encountered, and changing access permissions.
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              The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology.

              The French health care system is based on universal coverage by one of several health care insurance plans. The SNIIRAM database merges anonymous information of reimbursed claims from all these plans, linked to the national hospital-discharge summaries database system (PMSI) and the national death registry. It now covers 98.8% of the French population, over 66 million persons, from birth (or immigration) to death (or emigration), making it possibly the world's largest continuous homogeneous claims database. The database includes demographic data; health care encounters such as physician or paramedical visits, medicines, medical devices, and lab tests (without results); chronic medical conditions (ICD10 codes); hospitalisations with ICD10 codes for primary, linked and associated diagnoses, date and duration, procedures, diagnostic-related groups, and cost coding; date but currently not cause of death. The power of the database is correlatively great, and its representativeness is near perfect, since it essentially includes the whole country's population. The main difficulty in using the database, beyond its sheer size and complexity, is the administrative process necessary to access it. Recent legislative advances are making this easier. EGB (Echantillon Généraliste de Bénéficiaires) is the 1/97th random permanent representative sample of SNIIRAM, with planned 20-year longitudinal data (10 years at this time). Access time is 1 to 3 months, but its power is less (780 000 subjects). This is enough to study common issues with older drugs but may be limited for new products or rare events.
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                Author and article information

                Journal
                Int J Technol Assess Health Care
                Int J Technol Assess Health Care
                THC
                International Journal of Technology Assessment in Health Care
                Cambridge University Press (New York, USA )
                0266-4623
                1471-6348
                2024
                17 May 2024
                : 40
                : 1
                : e33
                Affiliations
                [ 1 ]HTA Department, Haute Autorité de Santé , La Plaine Saint-Denis, France
                [ 2 ]Scientific Board and Chairman of the Transparency Committee, Haute Autorité de Santé , La Plaine Saint-Denis, France
                [ 3 ]CHU de Bordeaux, Pharmacoepidemiology and Appropriate use of Medicine Team, Public Health Department, Clinical Pharmacology Unit Bordeaux , Nouvelle-Aquitaine, France
                [ 4 ] University of Bordeaux, INSERM , BPH, U1219, Team AHeaD Talence, Aquitaine, France
                [ 5 ]CHU de Bordeaux, Regional center for pharmacovigilance Public Health Department, Clinical Pharmacology Unit Bordeaux , Nouvelle-Aquitaine, France
                [ 6 ] Université de Tours, UMR U1246 Sphere, Inserm Tours , Centre-Val de Loire, France
                Author notes
                Corresponding author: Judith Fernandez; Email: j.fernandez@ 123456has-sante.fr
                Author information
                https://orcid.org/0000-0003-3923-7139
                https://orcid.org/0000-0002-6064-5957
                Article
                S0266462324000291
                10.1017/S0266462324000291
                11569913
                38757153
                a3285564-561d-40da-a519-690b608784ff
                © The Author(s) 2024

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.

                History
                : 07 August 2023
                : 19 March 2024
                : 26 April 2024
                Page count
                Tables: 3, References: 53, Pages: 8
                Categories
                Assessment

                Health & Social care
                real-world data,real-world evidence,life-cycle assessment,postlaunch evidence generation,health technology assessment

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