Good practices for clinical data warehouse implementation: a case study in France

TL;DR

This case study examines the implementation of Clinical Data Warehouses in French hospitals, highlighting key practices, challenges, and guidelines for improving governance, standardization, and data quality to enhance research and patient care.

Contribution

It provides a comprehensive analysis of French CDWs, offering practical guidelines for governance, standardization, and data quality to support research and routine care improvements.

Findings

14 hospitals have operational CDWs

5 hospitals are experimenting with CDWs

Implementation of CDWs accelerated after 2020

Abstract

Real World Data (RWD) bears great promises to improve the quality of care. However, specific infrastructures and methodologies are required to derive robust knowledge and brings innovations to the patient. Drawing upon the national case study of the 32 French regional and university hospitals governance, we highlight key aspects of modern Clinical Data Warehouses (CDWs): governance, transparency, types of data, data reuse, technical tools, documentation and data quality control processes. Semi-structured interviews as well as a review of reported studies on French CDWs were conducted in a semi-structured manner from March to November 2022. Out of 32 regional and university hospitals in France, 14 have a CDW in production, 5 are experimenting, 5 have a prospective CDW project, 8 did not have any CDW project at the time of writing. The implementation of CDW in France dates from 2011 and accelerated in the late 2020. From this case study, we draw some general guidelines for CDWs. The actual orientation of CDWs towards research requires efforts in governance stabilization, standardization of data schema and development in data quality and data documentation. Particular attention must be paid to the sustainability of the warehouse teams and to the multi-level governance. The transparency of the studies and the tools of transformation of the data must improve to allow successful multi-centric data reuses as well as innovations in routine care.