Type 2 diabetics followed up by family physicians: Treatment sequences and changes over time in weight and glycated hemoglobin

Boullenger, Léna; Quindroit, Paul; Legrand, Bertrand; Balcaen, Thibaut; Calafiore, Matthieu; Rochoy, Michaël; Beuscart, Jean-Baptiste; Chazard, Emmanuel

doi:10.1016/j.pcd.2022.07.002

Cited by 3 publications

(1 citation statement)

References 44 publications

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“…It includes data from a consultation with a General Practitioner (GP), prescriptions for drug and laboratory results. The reuse of primary care data is increasingly being addressed, but only a few retrospective studies were conducted with this kind of data [4,5]. The French project PriCaDa aims to reuse primary care data to improve GP practices in collaboration with the multidisciplinary health centre (MHC) in Wattrelos, in North of France.…”

Section: Introductionmentioning

confidence: 99%

Description of a French Population of Diabetics Treated Followed up by General Practitioners

Fruchart¹,

Lamer²,

Lemaître

et al. 2023

Caring Is Sharing – Exploiting the Value in Data for Health and Innovation

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In France, the prevalence of treated diabetes has been estimated at 4.6%, or more than 3 million people and 5.2% in Northern France. The reuse of primary care data allows to study outpatient clinical data such as laboratory results and drug prescriptions, which are not documented in claims and hospital databases. In this study, we selected the population of treated diabetics from the Wattrelos primary care data warehouse, in North of France. Firstly, we studied the laboratory results of diabetics by identifying whether the recommendations of the French National Authority for Health (HAS) were respected. In a second step, we studied the prescriptions of diabetics by identifying the oral hypoglycemic agents treatments and insulins treatments. The diabetic population represents 690 patients of the health care center. The recommendations on labortatory are respected for 84% of diabetics. The majority of diabetics are treated with oral hypoglycemic agents 68.6%. As recommended by the HAS, metformin is the first-line treatment in the diabetic population.

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Section: Introductionmentioning

confidence: 99%

Description of a French Population of Diabetics Treated Followed up by General Practitioners

Fruchart¹,

Lamer²,

Lemaître

et al. 2023

Caring Is Sharing – Exploiting the Value in Data for Health and Innovation

View full text Add to dashboard Cite

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Transforming Primary Care Data Into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study

Fruchart,

Quindroit,

Jacquemont

et al. 2024

JMIR Med Inform

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Background Patient-monitoring software generates a large amount of data that can be reused for clinical audits and scientific research. The Observational Health Data Sciences and Informatics (OHDSI) consortium developed the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize electronic health record data and promote large-scale observational and longitudinal research. Objective This study aimed to transform primary care data into the OMOP CDM format. Methods We extracted primary care data from electronic health records at a multidisciplinary health center in Wattrelos, France. We performed structural mapping between the design of our local primary care database and the OMOP CDM tables and fields. Local French vocabularies concepts were mapped to OHDSI standard vocabularies. To validate the implementation of primary care data into the OMOP CDM format, we applied a set of queries. A practical application was achieved through the development of a dashboard. Results Data from 18,395 patients were implemented into the OMOP CDM, corresponding to 592,226 consultations over a period of 20 years. A total of 18 OMOP CDM tables were implemented. A total of 17 local vocabularies were identified as being related to primary care and corresponded to patient characteristics (sex, location, year of birth, and race), units of measurement, biometric measures, laboratory test results, medical histories, and drug prescriptions. During semantic mapping, 10,221 primary care concepts were mapped to standard OHDSI concepts. Five queries were used to validate the OMOP CDM by comparing the results obtained after the completion of the transformations with the results obtained in the source software. Lastly, a prototype dashboard was developed to visualize the activity of the health center, the laboratory test results, and the drug prescription data. Conclusions Primary care data from a French health care facility have been implemented into the OMOP CDM format. Data concerning demographics, units, measurements, and primary care consultation steps were already available in OHDSI vocabularies. Laboratory test results and drug prescription data were mapped to available vocabularies and structured in the final model. A dashboard application provided health care professionals with feedback on their practice.

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Transforming Primary Care Data into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study (Preprint)

Fruchart,

Quindroit,

Jacquemont

et al. 2023

Preprint

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BACKGROUND Patient monitoring software generates a large amount of data that can be reused for clinical audits and scientific research. The Observational Health Data Sciences and Informatics (OHDSI) consortium developed the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize electronic health record (EHR) data and promote large-scale observational and longitudinal research. Primary care data have not previously been mapped and integrated into the OMOP CDM. OBJECTIVE To transform primary care data into the OMOP CDM. METHODS We extracted primary care data from the EHRs at a multidisciplinary healthcare center in Wattrelos (France). We performed structural mapping between the design of our local primary care database and the OMOP CDM tables and fields. Local French vocabularies concepts were mapped to OHDSI standard vocabularies. To validate the implementation of primary care data into the OMOP CDM, we applied a set of queries. A practical application was achieved through the development of a dashboard. RESULTS Data from 18,395 patients were implemented into the OMOP CDM, corresponding to 592,226 consultations over a period of 20 years. 18 OMOP CDM tables were implemented. 17 local vocabularies were identified as being related to primary care and corresponded to the patient characteristics (sex, location, year of birth, and race), units of measurement, biometric measures, laboratory test results, medical histories, drug prescriptions. During semantic mapping, 10,221 primary care concepts were mapped to standard OHDSI concepts. Five queries were used to validate the OMOP CDM by comparing the results obtained after completion of the transformations with the results obtained in the source software. Lastly, a prototype dashboard was developed to visualize the activity of the health center, the laboratory test results, and the drug prescription data. CONCLUSIONS Primary care data have been implemented into the OMOP CDM format. Data concerning demographics, units, measurements, and primary care consultation steps were already available in OHDSI vocabularies. Laboratory test results and drug prescription data were mapped to available vocabularies and structured in the final model. A dashboard application provides healthcare professionals with feedback on their practice.

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Type 2 diabetics followed up by family physicians: Treatment sequences and changes over time in weight and glycated hemoglobin

Cited by 3 publications

References 44 publications

Description of a French Population of Diabetics Treated Followed up by General Practitioners

Description of a French Population of Diabetics Treated Followed up by General Practitioners

Transforming Primary Care Data Into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study

Transforming Primary Care Data into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study (Preprint)

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