Publications by authors named "N Griffon"
Article Synopsis
- Electronic Health Record (EHR) systems are essential digital tools in clinical practice that store patient health information and can enhance research studies, particularly platform trials, which utilize multiple treatment options under one protocol.
- Despite their potential, challenges like incomplete records and complex eligibility criteria must be addressed for effective use of EHRs in research.
- The EU-PEARL project aims to develop methods and tools for better assessing EHR protocol feasibility, selecting clinical sites, and efficiently pre-screening patients for platform trials, using a consensus-based readiness survey and interoperable queries.
Purpose: Regulatory authorities including the Food and Drug Administration and the European Medicines Agency are encouraging to conduct clinical trials using routinely collected data. The aim of the TransFAIR experimental comparison was to evaluate, within real-life conditions, the ability of the Electronic Health Records to Electronic Data Capture (EHR2EDC) module to accurately transfer from EHRs to EDC systems patients' data of clinical studies in various therapeutic areas.
Methods: A prospective study including six clinical trials from three different sponsors running in three hospitals across Europe has been conducted.
Purpose: To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool.
View Article and Find Full Text PDFThe ReMIAMes project proposes a methodological framework to provide a reliable and reproducible measurement of the frequency of drug-drug interactions (DDI) when performed on real-world data. This framework relies on (i) a fine-grained and contextualized definition of DDIs, (ii) a shared minimum information model to select the appropriate data for the correct interpretation of potential DDIs, (iii) an ontology-based inference module able to handle missing data to classify prescription lines with potential DDIs, (iv) a report generator giving the value of the measurement and explanations when potential false positive are detected due to a lack of available data. All the tools developed are intended to be publicly shared under open license.
View Article and Find Full Text PDFAP-HP Health Data Space (AHDS) to the Test of the Covid-19 Pandemic.
Stud Health Technol Inform
May 2022
Unlabelled: Sharing observational and interventional health data within a common data space enables university hospitals to leverage such data for biomedical discovery and moving towards a learning health system.
Objective: To describe the AP-HP Health Data Space (AHDS) and the IT services supporting piloting, research, innovation and patient care.
Methods: Built on three pillars - governance and ethics, technology and valorization - the AHDS and its major component, the Clinical Data Warehouse (CDW) have been developed since 2015.