JMIR Publications

ABSTRACT

Background:

In Europe, national disparities in the integration of data linkage into routine public health activities were highlighted.

Objective:

The objective of this systematic review was to describe the use of indirect data linkage in France, focusing on health products and care trajectories.

Methods:

A comprehensive search for all articles published up to 31 March 2021 into PubMed/Medline and Embase databases was realized. To be eligible for inclusion, studies had to be published in English or French, be human studies, peer-reviewed articles, focus on health products or care trajectories and involve the use of linked French data defined as the linking of two or more French data collections at the patient level. Only studies based on use of indirect identifiers are included, i.e. without a unique personal identifier available to easily link the databases. A descriptive analysis of data linkage with quality indicators and adherence to the Bohensky framework for evaluating data linkage studies was realized.

Results:

16 articles were selected. Data linkage was performed at the national level in 7 cases or at the local level in 9 studies. The number of patients included in the different databases and resulting from data linkage, varied greatly, respectively from 713 to up to 75,000 patients and from 210 to up to 31,000 linked patients. The health products covered by the studies included varied drugs and medical devices. The diseases studied were mainly chronic diseases and infections. The objectives of the data linkages were multiples: to estimate the risk of adverse drug reactions in 6 cases, to reconstruct the patient’s care trajectory in 5 cases, to describe therapeutic uses in 2 cases, to evaluate the benefits of treatments in 2 cases and to evaluate treatment adherence in one case. All but one study reported indirect linkage using French claims databases at national or regional level. Registries are the most frequently linked databases with French claims data. No studies have looked at linking with a hospital data warehouse, a clinical trial database or patient self-reported databases. In this review, the deterministic approach was used in 7 studies and the probabilistic linkage in 4 studies. Five studies used linkage with indirect key identifiers but did not specify whether it was a deterministic or a probabilistic approach. The linkage rate, when specified in the study (11/15 studies), was mainly between 80 to 90%. Analysis of the characteristics of matched versus unmatched records to assess the completeness of the linkage or to identify a potential selection bias was used in 26% of cases. Adherence to the Bohensky framework for evaluating data linkage studies showed that the description of the source databases for the linkage was always done, but the completion rate and accuracy of the variables to be linked were not systematically described.

Conclusions:

This review highlights the growing interest in health data linkage in France. Nevertheless, regulatory, technical and human constraints remain major obstacles to their deployment. The volume, variety and validity of the data represent a real challenge and advanced expertise and skills in statistical analysis and artificial intelligence are required to treat this big data. Clinical Trial: Not applicable