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Academic literature on the topic 'Maison de Santé Pluridisciplinaire (MSP)'
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Journal articles on the topic "Maison de Santé Pluridisciplinaire (MSP)"
Pourrain, Laure, Michel Serin, Anne Dautriche, Fréderic Jacquetin, Christophe Jarny, Isabelle Ballenecker, Mickaël Bahous, and Catherine Sgro. "Gestion des erreurs médicamenteuses en médecine générale : étude en maison de santé pluridisciplinaire." Therapies 73, no. 6 (December 2018): 461–71. http://dx.doi.org/10.1016/j.therap.2018.04.006.
Full textFORAY, A., P. SALLES, B. LAVAL, and C. PLOTTON. "La maison de santé pluriprofessionnelle inscrite dans le paysage des soins primaires. Attentes des usagers du système de santé et des futurs médecins généralistes." EXERCER 35, no. 200 (February 1, 2024): 54–60. http://dx.doi.org/10.56746/exercer.2024.200.54.
Full textBuffet, Sophie, Patrick Vuattoux, François Baudier, Yvette Peseux, Christian Magnin-Feysot, and Jean-Michel Perrot. "Mise en place d'un comité de représentants des usagers dans une maison de santé pluridisciplinaire." Santé Publique 26, no. 4 (2014): 433. http://dx.doi.org/10.3917/spub.144.0433.
Full textCousin, C. "Consultation infirmière : évaluation et prise en charge de la douleur en maison de santé pluridisciplinaire." Douleurs : Evaluation - Diagnostic - Traitement 13 (November 2012): A12. http://dx.doi.org/10.1016/j.douler.2012.08.040.
Full textALLORY, E., M. GESLOT, C. ANGOULVANT, P. GENDRY, JF MOREUL, and A. RAMOND-ROQUIN. "ENGAGEMENT DES USAGERS DANS LES MAISONS DE SANTE PLURIPROFESSIONNELLES ET CARACTERISTIQUES DES MSP ASSOCIEES." EXERCER 34, no. 193 (May 1, 2023): 196–201. http://dx.doi.org/10.56746/exercer.2023.193.196.
Full textMasse, F. "CA-160: Évaluation d'un programme d'éducation thérapeutique du patient diabétique en maison de santé pluridisciplinaire en Martinique." Diabetes & Metabolism 42 (March 2016): A79. http://dx.doi.org/10.1016/s1262-3636(16)30292-0.
Full textMaisonneuve, Hubert, Anaïs Besson, Marianne Follet, Emilie Fuentes, Danielle Stimulak, and Benoit Tudrej. "Histoire d’une maison de santé à Lyon (France). Un exercice coordonné pluridisciplinaire au service de patients complexes." Revue Médicale Suisse 19, no. 826 (2023): 892–97. http://dx.doi.org/10.53738/revmed.2023.19.826.892.
Full textLoussouarn, Christophe, Carine Franc, Yann Videau, and Julien Mousquès. "L’effet combiné de l’exercice en maison de santé pluriprofessionnelle et des paiements à la coordination sur l’activité des médecins généralistes." Revue économique Vol. 74, no. 3 (July 20, 2023): 441–70. http://dx.doi.org/10.3917/reco.743.0441.
Full textVigouroux-Zugasti, Eloria. "Un an après : la gestion organisationnelle de la pandémie SARS-CoV-2 en Maison de Santé Pluridisciplinaire." Revue française des sciences de l’information et de la communication, no. 24 (January 1, 2022). http://dx.doi.org/10.4000/rfsic.12523.
Full textCyrenne-Dussault, Marie, Maude Sirois, Julie St-Pierre, and Jean-Philippe Drouin-Chartier. "Food insecurity in households of children receiving care at a paediatric obesity management clinic in Montreal: Overall prevalence and changes associated with the COVID-19 pandemic." Paediatrics & Child Health, August 3, 2022. http://dx.doi.org/10.1093/pch/pxac072.
Full textDissertations / Theses on the topic "Maison de Santé Pluridisciplinaire (MSP)"
Fruchart, Mathilde. "Réutilisation des données de soins premiers : spécificités, standardisation et suivi de la prise en charge dans les Maisons de Santé Pluridisciplinaires." Electronic Thesis or Diss., Université de Lille (2022-....), 2024. http://www.theses.fr/2024ULILS040.
Full textContext : 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 of the model. An algorithm for assessing persistence with treatment prescribed by the GP and also a dashboard for monitoring performance indicators (ROSP) and practice activity have been developed. Based on the data warehouses of four MHCs, we described the follow-up of diabetic patients. These studies use biological results, consultation and drug prescriptions data in OMOP format. The scripts of these studies and the tools developed can be shared. Conclusion : Primary care data represent a potential for reusing data for research purposes and improving the quality of care. They complement existing databases (hospital, national and social networks) by integrating clinical data from the city. The use of a common data model facilitates the development of tools and the conduct of studies, while enabling their sharing. Studies can be replicated in different centers to compare results