| Title: |
Secondary use of primary care data : specificities, standardization and monitoring of care in multidisciplinary health centers ; Réutilisation des données de soins premiers : spécificités, standardisation et suivi de la prise en charge dans les Maisons de Santé Pluridisciplinaires |
| Authors: |
Fruchart, Mathilde |
| Contributors: |
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS); Université de Lille-Centre Hospitalier Régional Universitaire CHU Lille (CHRU Lille); Université de Lille; Antoine Lamer |
| Source: |
https://theses.hal.science/tel-04893586 ; Médecine humaine et pathologie. Université de Lille, 2024. Français. ⟨NNT : 2024ULILS040⟩. |
| Publisher Information: |
CCSD |
| Publication Year: |
2024 |
| Collection: |
LillOA (HAL Lille Open Archive, Université de Lille) |
| Subject Terms: |
Dashboard; Multidisciplinary health center (MHC); Primary care; OMOP common data model; Extract-Transform-Load (ETL); Data reuse; Tableau de bord; Maison de Santé Pluridisciplinaire (MSP); Soins premiers; Modèle de données commun OMOP; Réutilisation des données; [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology |
| Description: |
Context : Reusing healthcare data beyond its initial use helps to improve patient care, facilitate research, and optimize the management of healthcare organizations. To achieve this, data is extracted from healthcare software, transformed and stored in a data warehouse through an extract-transform-load(ETL) process. Common data models, such as the OMOP model, exist to store data in a homogeneous,source-independent format. Data from healthcare claims centralized in the national database (SNDS), hospital, social networks and forums, and primary care are different data sources representative of the patient care pathway. The last data source has not been fully exploited. Objective : The aim of this thesis was to incorporate the specificities of primary care data reuse to implement a data warehouse while highlighting the contribution of primary care to the field of research. Methods : The first step was to extract the primary care data of a multidisciplinary health center (MHC) from the WEDA care software. A primary care data warehouse was implemented using an ETL process. Structural transformation (harmonization of the database structure) and semantic transformation (harmonization of the vocabulary used in the data) were implemented to align the data with the common OMOP data model. A process generalization tool was developed to integrate general practitioners (GP) data from multiple care structures and tested on four MHCs. Subsequently, algorithm for assessing the persistence of a prescribed treatment and dashboards were developed. Thanks to the use of the OMOP model, these tools can be shared with other MHCs. Finally, retrospective studies were conducted on the diabetic population of the four MHCs. Results : Over a period of more than 20 years, data of 117,005 patients from four MHCs wereloaded into the OMOP model using our ETL process optimization tool. These data include biological results from laboratories and GP consultation data. The vocabulary specific to primary care was aligned with the standard concepts ... |
| Document Type: |
doctoral or postdoctoral thesis |
| Language: |
French |
| Relation: |
NNT: 2024ULILS040 |
| Availability: |
https://theses.hal.science/tel-04893586; https://theses.hal.science/tel-04893586v1/document; https://theses.hal.science/tel-04893586v1/file/2024ULILS040.pdf |
| Rights: |
https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.671C8286 |
| Database: |
BASE |