University of Bordeaux, Inserm U1219, Bordeaux Population Health Research Center, Team AHead, Department of Medical Pharmacology, CHU de Bordeaux, 33000 Bordeaux, France.
Inserm, Team PEPSS (Pharmacologie en Population, Cohortes, Biobanques), Department of Clinical Pharmacology, CIC 1436, Toulouse University Hospital, 31000 Toulouse, France.
Therapie. 2023 Nov-Dec;78(6):679-689. doi: 10.1016/j.therap.2023.01.009. Epub 2023 Jan 28.
The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendations when using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.
法国的健康保险数据仓库命名为 SNDS,是世界上最大的医管数据库之一,能够基于前瞻性收集的真实数据进行强大的药物流行病学研究。除了强有力的药理学理论基础的绝对必要性外,还考虑了提高药物流行病学研究质量的建议。这些指南强调了准确定义研究人群、结局和暴露的重要性,特别是对于基于医管数据库进行的研究。由于 SNDS 的结构和记录数据的性质,在进行研究时,遵守某些指南,特别是那些关于特定人群或结局的识别以及风险期或暴露期的定义的指南,可能具有一定难度。本文的目的是根据 SNDS 的特点,为使用该数据库进行药物流行病学研究提供建议。从这个丰富但复杂的数据仓库中进行可靠的研究需要具有 SNDS 和药理学推理方面的深厚知识的研究人员的专业知识。