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1. Attitudes of General Practitioners Toward Prescription of Mobile Health Apps: Qualitative Study

Author

Sarradon-Eck, Aline, Bouchez, Tiphanie, Auroy, Lola, Schuers, Matthieu, and Darmon, David

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundMobile health (mHealth) apps are a potential means of empowering patients, especially in the case of multimorbidity, which complicates patients’ care needs. Previous studies have shown that general practitioners (GPs) have both expectations and concerns regarding patients’ use of mHealth apps that could impact their willingness to recommend the apps to patients. ObjectiveThe aim of this qualitative study is to investigate French GPs’ attitudes toward the prescription of mHealth apps or devices aimed toward patients by analyzing GPs’ perceptions and expectations of mHealth technologies. MethodsA total of 36 GPs were interviewed individually (n=20) or in a discussion group (n=16). All participants were in private practice. A qualitative analysis of each interview and focus group was conducted using grounded theory analysis. ResultsConsidering the value assigned to mHealth apps by participants and their willingness or resistance to prescribe them, 3 groups were defined based on the attitudes or positions adopted by GPs: digital engagement (favorable attitude; mHealth apps are perceived as additional resources and complementary tools that facilitate the medical work, the follow-up care, and the monitoring of patients; and apps increase patients’ compliance and empowerment); patient protection (related to the management of patient care and fear of risks for patients, concerns about patient data privacy and security, doubt about the usefulness for empowering patients, standardization of the medical decision process, overmedicalization, risks for individual freedom, and increasing social inequalities in health); doctor protection (fear of additional tasks and burden, doubt about the actionability of patient-gathered health data, risk for medical liability, dehumanization of the patient-doctor relationship, fear of increased drug prescription, and commodification of patient data). ConclusionsA deep understanding of both the expectations and fears of GPs is essential to motivate them to recommend mHealth apps to their patients. The results of this study show the need to provide appropriate education and training to enhance GPs’ digital skills. Certification of the apps by an independent authority should be encouraged to reassure physicians about ethical and data security issues. Our results highlight the need to overcome technical issues such as interoperability between data collection and medical records to limit the disruption of medical work because of data flow.

Published
2021
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2. Alternative Devices for Heart Rate Variability Measures: A Comparative Test-Retest Reliability Study.

Author

Killian, Jacquelin, Radin, Rachel, Gardner, Cubby, Kasuske, Lalon, Bashirelahi, Kylee, Nathan, Dominic, Keyser, David, Cellucci, Christopher, Darmon, David, and Rapp, Paul

Subjects
HRV, heart rate variability, intraclass correlation coefficients, photoplethysmography, portable heart rate monitor, test–retest reliability
Abstract

Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

Published
2021

3. Large-Scale Communication is More Complex and Unpredictable with Automated Bots

Author

Hilbert, Martin and Darmon, David

Subjects
Basic Behavioral and Social Science, Behavioral and Social Science, Film, Television and Digital Media, Journalism and Professional Writing, Communication and Media Studies, Communication & Media Studies
Abstract

Automated communication bots follow deterministic local rules that either respond to programmed instructions or learned patterns. On the microlevel, their automated and reactive behavior makes certain parts of the communication dynamic more predictable. Studying communicative turns in the editing history of Wikipedia, we find that on the macrolevel, the overall emergent communication process becomes both more complex and less predictable. The increased presence of bots is the main explanatory variable for these seemingly contradictory tendencies. In short, individuals introduce bots to make communication more simple and predictable but end up with a large-scale dynamic that is more complex and more uncertain. We explain our results with the information processing nature of complex systems. The article also serves as a showcase for the use of information-theoretic measures from dynamical systems theory to assess changes in communication dynamics provoked by algorithms.

Published
2020

4. How Complexity and Uncertainty Grew with Algorithmic Trading

Author

Hilbert, Martin and Darmon, David

Subjects
Mathematical Sciences, Physical Sciences, algorithmic trading, complexity, dynamical systems theory, machine learning, predictability, Fluids & Plasmas, Mathematical sciences, Physical sciences
Abstract

The machine-learning paradigm promises traders to reduce uncertainty through better predictions done by ever more complex algorithms. We ask about detectable results of both uncertainty and complexity at the aggregated market level. We analyzed almost one billion trades of eight currency pairs (2007-2017) and show that increased algorithmic trading is associated with more complex subsequences and more predictable structures in bid-ask spreads. However, algorithmic involvement is also associated with more future uncertainty, which seems contradictory, at first sight. On the micro-level, traders employ algorithms to reduce their local uncertainty by creating more complex algorithmic patterns. This entails more predictable structure and more complexity. On the macro-level, the increased overall complexity implies more combinatorial possibilities, and therefore, more uncertainty about the future. The chain rule of entropy reveals that uncertainty has been reduced when trading on the level of the fourth digit behind the dollar, while new uncertainty started to arise at the fifth digit behind the dollar (aka 'pip-trading'). In short, our information theoretic analysis helps us to clarify that the seeming contradiction between decreased uncertainty on the micro-level and increased uncertainty on the macro-level is the result of the inherent relationship between complexity and uncertainty.

Published
2020

5. Computational landscape of user behavior on social media

Author

Darmon, David, Rand, William, and Girvan, Michelle

Subjects
Computer Science - Social and Information Networks, Physics - Physics and Society, Statistics - Applications
Abstract

With the increasing abundance of 'digital footprints' left by human interactions in online environments, e.g., social media and app use, the ability to model complex human behavior has become increasingly possible. Many approaches have been proposed, however, most previous model frameworks are fairly restrictive. We introduce a new social modeling approach that enables the creation of models directly from data with minimal a priori restrictions on the model class. In particular, we infer the minimally complex, maximally predictive representation of an individual's behavior when viewed in isolation and as driven by a social input. We then apply this framework to a heterogeneous catalog of human behavior collected from fifteen thousand users on the microblogging platform Twitter. The models allow us to describe how a user processes their past behavior and their social inputs. Despite the diversity of observed user behavior, most models inferred fall into a small subclass of all possible finite-state processes. Thus, our work demonstrates that user behavior, while quite complex, belies simple underlying computational structures.

Published
2019

9. Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series

Author

Darmon, David

Subjects
Computer Science - Learning, Statistics - Methodology
Abstract

We introduce a method for quantifying the inherent unpredictability of a continuous-valued time series via an extension of the differential Shannon entropy rate. Our extension, the specific entropy rate, quantifies the amount of predictive uncertainty associated with a specific state, rather than averaged over all states. We relate the specific entropy rate to popular `complexity' measures such as Approximate and Sample Entropies. We provide a data-driven approach for estimating the specific entropy rate of an observed time series. Finally, we consider three case studies of estimating specific entropy rate from synthetic and physiological data relevant to the analysis of heart rate variability.

Published
2016

11. Les auteurs

Author

Aubin-Auger, Isabelle, primary, Barais, Marie, additional, Bardet, Jean-Didier, additional, Bayen, Marc, additional, Bègue, Cyril, additional, Benedini, Élise, additional, Binder, Philippe, additional, Blœdé, François, additional, Bouchez, Tiphanie, additional, Bourgueil, Yann, additional, Boussageon, Rémy, additional, Canévet, Jean-Paul, additional, Carbonnel, François, additional, Casanova, Ludovic, additional, Chambe, Juliette, additional, Chamboredon, Benoît, additional, Chanelière, Marc, additional, Chapron, Anthony, additional, Charuel, Élodie, additional, de Chefdebien, Marine, additional, Clément, Renaud, additional, Clerc, Pascal, additional, Coindard, Guillaume, additional, Compagnon, Laurence, additional, Cordonnier, Pauline, additional, Darmon, David, additional, Devillers, Louise, additional, Dibao-Dina, Clarisse, additional, Ducloyer, Mathilde, additional, Duhoux, Bérengère, additional, Dupouy, Julie, additional, Durrieu, Florence, additional, Erpeldinger, Sylvie, additional, Escourrou, Émile, additional, Ferrat, Émilie, additional, Fiquet, Laure, additional, Flora, Luigi, additional, Flori, Marie, additional, François, Mathilde, additional, Frappé, Paul, additional, Freyens, Anne, additional, Gaboreau, Yoann, additional, Ghasarossian, Christian, additional, de La Londe, Julie Gilles, additional, Girard, Pauline, additional, Gocko, Xavier, additional, Haller, Dagmar M., additional, Huas, Caroline, additional, Imbert, Patrick, additional, Jami, Alain, additional, Jeanmougin, Pauline, additional, Jego-Sablier, Maeva, additional, Joseph, Jean-Philippe, additional, Jouannin, Adeline, additional, Kapassi, Amar, additional, Kermiche, François, additional, Kinouani, Shérazade, additional, Khouani, Jérémy, additional, Lamort-Bouché, Marion, additional, Laporte, Catherine, additional, Lebeau, Jean-Pierre, additional, Le Breton, Julien, additional, Letrilliart, Laurent, additional, Liard, Roxane, additional, Maynié-François, Christine, additional, Mazalovic, Katia, additional, Mercier, Alain, additional, Meury Abraham, Pierrette, additional, Mignot, Stéphanie, additional, Million, Élodie, additional, Mitilian, Eva, additional, Monney, Yhan, additional, Moreau, Alain, additional, Moussaoui, Sohela, additional, Paradis, Sabrina, additional, Paumier, Françoise, additional, Perdrix, Corinne, additional, Pouchain, Denis, additional, Ramond-Roquin, Aline, additional, Rat, Cédric, additional, Renard, Vincent, additional, Rossignol, Louise, additional, Bugat, Marie-Eve Rougé, additional, Rousseau, Anne, additional, Rousseau, Rosalie, additional, Ruelle, Yannick, additional, Salmon, Emeline, additional, Sanchez, Delphine, additional, Schuers, Matthieu, additional, Sidorkiewicz, Stéphanie, additional, Tudrej, Benoit, additional, Vandendriessche, Juliette, additional, Vartanian, Cyrille, additional, Virot, Grégoire, additional, Vorilhon, Philippe, additional, Waldner-Combernoux, Anne, additional, and Zabawa, Claire, additional

Published
2022
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12. Followers Are Not Enough: A Question-Oriented Approach to Community Detection in Online Social Networks

Author

Darmon, David, Omodei, Elisa, and Garland, Joshua

Subjects
Computer Science - Social and Information Networks, Physics - Physics and Society
Abstract

Community detection in online social networks is typically based on the analysis of the explicit connections between users, such as "friends" on Facebook and "followers" on Twitter. But online users often have hundreds or even thousands of such connections, and many of these connections do not correspond to real friendships or more generally to accounts that users interact with. We claim that community detection in online social networks should be question-oriented and rely on additional information beyond the simple structure of the network. The concept of 'community' is very general, and different questions such as "whom do we interact with?" and "with whom do we share similar interests?" can lead to the discovery of different social groups. In this paper we focus on three types of communities beyond structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that the communities obtained in the three weighted cases are highly different from each other, and from the communities obtained by considering only the unweighted structural network. Our results confirm that asking a precise question is an unavoidable first step in community detection in online social networks, and that different questions can lead to different insights about the network under study., Comment: 22 pages, 4 figures, 1 tables

Published
2014
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13. Injecting Domain Knowledge in Electronic Medical Records to Improve Hospitalization Prediction

Author

Gazzotti, Raphaël, Faron-Zucker, Catherine, Gandon, Fabien, Lacroix-Hugues, Virginie, Darmon, David, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor

Published
2019
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14. Understanding the Predictive Power of Computational Mechanics and Echo State Networks in Social Media

Author

Darmon, David, Sylvester, Jared, Girvan, Michelle, and Rand, William

Subjects
Computer Science - Social and Information Networks, Computer Science - Learning, Physics - Physics and Society, Statistics - Applications, Statistics - Machine Learning
Abstract

There is a large amount of interest in understanding users of social media in order to predict their behavior in this space. Despite this interest, user predictability in social media is not well-understood. To examine this question, we consider a network of fifteen thousand users on Twitter over a seven week period. We apply two contrasting modeling paradigms: computational mechanics and echo state networks. Both methods attempt to model the behavior of users on the basis of their past behavior. We demonstrate that the behavior of users on Twitter can be well-modeled as processes with self-feedback. We find that the two modeling approaches perform very similarly for most users, but that they differ in performance on a small subset of the users. By exploring the properties of these performance-differentiated users, we highlight the challenges faced in applying predictive models to dynamic social data.

Published
2013

15. Management of patients with chronic kidney disease: a French medical centre database analysis.

Author

Ariza, Matthieu, Martin, Steven, Dusenne, Mikaël, Darmon, David, and Schuers, Matthieu

Subjects
CHRONIC kidney failure, MEDICAL databases, CHRONICALLY ill, ELECTRONIC health records, GLOMERULAR filtration rate
Abstract

Objective(s) Chronic kidney disease (CKD) is an insidious disease that requires early nephroprotective measures to delay progression to end-stage kidney disease. The objective of this study was to describe the management of patients with CKD in primary care, including clinical and biological monitoring and prescribed treatments. A retrospective, single-centre study was conducted on adult patients who were treated in the Maison de Neufchâtel (France) between 2012 and 2017 at least once a year. The inclusion criteria were 2 estimated glomerular filtration rate (eGFR) measurements <60 mL/min more than 3 months apart. Two subgroups were constituted according to whether CKD was coded in the electronic medical records (EMRs). Results A total of 291 (6.7%, CI95% 5.9–7.4) patients with CKD were included. The mean eGFR was 51.0 ± 16.4 mL/min. Hypertension was the most frequent health problem reported (n = 93, 32%). Nephrotective agents were prescribed in 194 (66.7%) patients, non-steroidal anti-inflammatory drugs (NSAIDs) in 22 (8%) patients, and proton-pump inhibitors (PPIs) in 147 (47%) patients. CKD coding in EMRs was associated with dosage of natraemia (n = 34, 100%, P < 0.01), albuminuria (n = 20, 58%, P < 0.01), vitamin D (n = 14, 41%, P < 0.001), and phosphorus (n = 11, 32%, P < 0.001). Eighty-one patients (31.5%) with low eGFR without an entered code for CKD were prescribed an albuminuria dosage. Clinical monitoring could not be analysed due to poor coding. Conclusion This pilot study reinforces the hypothesis that CKD is underscreened and undermanaged. More systematic coding of medical information in EMRs and further studies on medical centre databases should improve primary care practices. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Prediction of Elevated Activity in Online Social Media Using Aggregated and Individualized Models

Author

Harada, Jimpei, Darmon, David, Girvan, Michelle, Rand, William, Alhajj, Reda, Series editor, Glässer, Uwe, Series editor, Aggarwal, Charu C., Advisory board, Brantingham, Patricia L., Advisory board, Gross, Thilo, Advisory board, Han, Jiawei, Advisory board, Liu, Huan, Advisory board, Manasevich, Raul, Advisory board, Masys, Anthony J., Advisory board, Morselli, Carlo, Advisory board, Wittek, Rafael, Advisory board, Zeng, Daniel, Advisory board, Missaoui, Rokia, editor, Abdessalem, Talel, editor, and Latapy, Matthieu, editor

Published
2017
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21. The French ecology of medical care. A nationwide population-based cross sectional study.

Author

Laporte, Catherine, Fortin, Frédéric, Dupouy, Julie, Darmon, David, Pereira, Bruno, Authier, Nicolas, Delorme, Jessica, Chenaf, Chouki, Maisonneuve, Hubert, and Schuers, Matthieu

Subjects
MEDICAL geography, MEDICAL care, NATIONAL health insurance, OUTPATIENT services in hospitals, PRIMARY health care
Abstract

Purpose Studies in the United States, Canada, Belgium, and Switzerland showed that the majority of health problems are managed within primary health care; however, the ecology of French medical care has not yet been described. Methods Nationwide, population-based, cross sectional study. In 2018, we included data from 576,125 beneficiaries from the General Sample of Beneficiaries database. We analysed the reimbursement of consultations with (i) a general practitioner (GP), (ii) an outpatient doctor other than a GP, (iii) a doctor from a university or non-university hospital; and the reimbursement of (iv) hospitalization in a private establishment, (v) general hospital, and (vi) university hospital. For each criterion, we calculated the average monthly number of reimbursements reported on 1,000 beneficiaries. For categorical variables, we used the χ2 test, and to compare means we used the z test. All tests were 2-tailed with a P -value < 5% considered significant. Results Each month, on average, 454 (out of 1,000) beneficiaries received at least 1 reimbursement, 235 consulted a GP, 74 consulted other outpatient doctors in ambulatory care and 24 in a hospital, 13 were hospitalized in a public non-university hospital and 10 in the private sector, and 5 were admitted to a university hospital. Independently of age, people consulted GPs twice as much as other specialists. The 13–25-year-old group consulted the least. Women consulted more than men. Individuals covered by complementary universal health insurance had more care. Conclusions Our study on reimbursement data confirmed that, like in other countries, in France the majority of health problems are managed within primary health care. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Risk of Bias Mitigation for Vulnerable and Diverse Groups in Community-Based Primary Health Care Artificial Intelligence Models: Protocol for a Rapid Review

Author

Sasseville, Maxime, primary, Ouellet, Steven, additional, Rhéaume, Caroline, additional, Couture, Vincent, additional, Després, Philippe, additional, Paquette, Jean-Sébastien, additional, Gentelet, Karine, additional, Darmon, David, additional, Bergeron, Frédéric, additional, and Gagnon, Marie-Pierre, additional

Published
2023
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24. Risk of Bias Assessment for Diversity Groups in Community-Based Primary Health Care Artificial Intelligence Systems: A Rapid Review Protocol (Preprint)

Author

Sasseville, Maxime, primary, Ouellet, Steven, additional, Rhéaume, Caroline, additional, Couture, Vincent, additional, Després, Philippe, additional, Paquette, Jean-Sébastien, additional, Gentelet, Karine, additional, Darmon, David, additional, Bergeron, Frédéric, additional, and Gagnon, Marie-Pierre, additional

Published
2023
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25. Risk of Bias Assessment for Diversity Groups in Community-Based Primary Health Care Artificial Intelligence Systems: A Rapid Review Protocol

Author

Paquette, Jean-Sébastien, Després, Philippe, Gentelet, Karine, Gagnon, Marie-Pierre, Sasseville, Maxime, Ouellet, Steven, Couture, Vincent, Rhéaume, Caroline, Bergeron, Frédéric, and Darmon, David

Subjects
health equity, health disparity, algorithms, artificial intelligence, primary care, rapid review, Engineering, Medical Sciences, Sociology, Medicine and Health Sciences, Health Information Technology, Diseases, Computer Engineering, Social and Behavioral Sciences, FOS: Sociology
Abstract

This rapid review is the first step of the larger “Protecting and Engaging Vulnerable Populations in the Development of Predictive Models in Primary Health Care for Inclusive, Diverse and Equitable AI” (PREMIA) project. This work we will be presented results to key stakeholders and we will conduct qualitative data collection to identify and evaluate biases in one AI model conduct interviews with them. Abstract: Background: Current literature identifies several potential benefits of artificial intelligence in primary health care. However, there is a lack of understanding on how the risk of bias is considered in the development of primary health care algorithms and to what extend they perpetuate or introduce potential biases toward groups that could be considered as vulnerable in function of their characteristics (e.g., age, sex, gender identity, sexual orientation, race, ethnicity, religion, physical ability, socioeconomic status, etc.). To the best of our knowledge no reviews are currently available to identify the relevant methods to assess risk of bias in these algorithms. The primary question of this review is which strategies can assess risk of bias in community-based primary health care algorithms toward vulnerable or diversity groups? Objective: To identify 1) relevant methods (e.g., frameworks, tools, checklists, etc.) to assess the risk of bias toward diversity groups in the development and/or deployment of algorithms in community-based primary health care and 2) mitigation interventions deployed to promote and increase equity, diversity and inclusion. This review looks at what attempts to mitigate bias have been documented and which vulnerable or diversity groups have been considered. Methods: A rapid review of the scientific literature in four databases (PubMed, CINAHL, Web of Science and PsychInfo) in the last 5 years. Two reviewers will independently screen the titles and abstracts and the full text of the identified records on the Covidence systematic review software. We will include all studies on methods developed and/or tested to assess risk of bias in algorithms that can be relevant in community-based primary health care settings. Data of selected studies will be extracted using a validated grid and results will be presented using structured narrative summaries. Results: In November 2022 an information specialist developed a specific search strategy based on the main concepts of our primary review question in the most relevant databases (PubMed, CINAHL, Web of Science and PsychInfo) in the last 5 years. We completed the search strategy in December 2022 and 1022 sources were identified. We start the screening phase of titles and abstracts. Conclusions: This review will develop structured summaries of strategies to mitigate bias toward vulnerable populations and diversity groups in artificial intelligence models. This could be useful to researchers and other stakeholders to identify potential sources of bias in algorithms for eventually try to reduce or eliminate them.

Published
2023
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28. Approximate Continuous Time Measures of Information Movement in Complex Extended Networks.

Author

Rapp, Paul E., Cellucci, Christopher J., Gilpin, Claire E., and Darmon, David M.

Subjects
DIFFERENTIAL entropy, TIME measurements, APPROXIMATION theory, DENSITY functional theory, K-nearest neighbor classification, UNCERTAINTY
Abstract

The differential entropy of a continuous waveform is defined over the period spanned by the recording. The time-dependent information dynamics of the observed process are not accessible to this measure. We review here the construction and validation of approximate time-dependent measures of information dynamics. [ABSTRACT FROM AUTHOR]

Published
2023
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40. Innovating in partnership by creating a mobile application decision aid in the doctor-patient relationship: The ApiAppS research

Author

Flora, Luigi, Darmon, David, Darmoni, Stefen Sd, Julien Grosjean, Simon, Christian, Hassanaly, Parina, Dufour, Jean-Charles, Flora, Luigi, Risques, Epidémiologie, Territoire, INformations, Education et Santé (RETINES), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA), Centre d'Innovation du Partenariat avec les Patients et le Public, Faculté de médecine, Université Côte d'Azur (CI3P), Faculté de médecine, Université Côte d'Azur, Direction Collaboration et Partenariat Patient, Faculté de médecine, Université de Montréal (DCPP), Centre d'Etudes des Solidarités Sociales (Ass.1901) (CESOL), Association, Centre National de Ressources et de Résilience [Lille] (CN2R), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), CHERPA, LAPCOS, HEALTHY, Université Côte d'azur, Département d'enseignement et de recherche en médecine générale(DERMG), faculté de médecine, Université Côte d'azur (DERMG), CHU Rouen, Normandie Université (NU), Département d'Informatique Médicale (D2IM), Normandie Université (NU)-Normandie Université (NU), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Silk Informatique, Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U912 INSERM - Aix Marseille Univ - IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), and ANR

Subjects
partenariat patient, patient partnership, interdisciplinary research, autonomie, recherche interdisciplinaire, santé mobile, [SHS] Humanities and Social Sciences, autonomy, Système d’aide à la décision, mobile health, Decision support system, [SHS]Humanities and Social Sciences
Abstract

Context : is article presents a research funded by the French National Research Agency (ANR) on the design of a prescription decision aid for mobile health applications for French general practitioners. Objective and method: This research, proposed by an inter-university consortium, has become an interdisciplinary development in partnership with patients. The article sheds light on both the phases constituted mobilizing in turn, the different researchers, professionals, citizens and patients, the modalities of partnership initiated as well as the results of the research. Conclusion: Among the plethora of mobile health applications on the market, a critical evaluation process was designed to help in the decision to prescribe a mobile application. The methodology mobilized participates in a participatory approach of all the actors of the Care which the patients are today part of, a way of apprehending the complexity which allows to take up the challenges of adhesion of the greatest number., Contexte : cet article présente une recherche financée par l’Agence Nationale de la Recherche (ANR) sur la conception d’une aide à la décision de prescription d’applications mobiles de santé pour les médecins généralistes français. Objectif et méthode : Cette recherche, proposée par un consortium interuniversitaire, est devenue, en cours d’élaboration, interdisciplinaire en partenariat avec les patients. L’article éclaire tant les phases constituées mobilisant à tour de rôle les différents chercheurs, professionnels, citoyens et patients, les modalités de partenariat initiés, que les résultats de la recherche. Conclusion : Parmi la pléthore d’applications mobiles en santé mises sur le marché, un processus d’évaluation critique a été conçu permettant une aide à la décision de prescription d’application mobile. La méthodologie mobilisée participe à une approche participative de tous les acteurs du Soin dont les patients font aujourd’hui partie, une manière d’appréhender la complexité qui permet de relever les défis d’adhésion du plus grand nombre.

Published
2022

43. L’exercice médical à travers les mutations de la société à l’émergence du partenariat de soin avec le patient

Author

Darmon, David, Risques, Epidémiologie, Territoire, INformations, Education et Santé (RETINES), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA), Département d'enseignement et de recherche en médecine générale(DERMG), faculté de médecine, Université Côte d'azur (DERMG), Centre d'Innovation du Partenariat avec les Patients et le Public, Faculté de médecine, Université Côte d'Azur (CI3P), Faculté de médecine, Université Côte d'Azur, 'Cancer, Biomedicine & Society' group (SESSTIM - U1252 INSERM - AMU - UMR 259 IRD), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Flora, Luigi

Subjects
[SHS] Humanities and Social Sciences, ComputingMilieux_MISCELLANEOUS, [SHS]Humanities and Social Sciences
Abstract

International audience

Published
2021

44. ESSAI RANDOMISÉ POUR ÉVALUER L’EFFICACITÉ ET LA SÉCURITÉ DE TRAITEMENTS CHEZ DES PATIENTS AMBULATOIRES ATTEINTS DE COVID-19 AYANT DES FACTEURS DE RISQUE ESSAI COVERAGE FRANCE : PRÉSENTATION DU PROTOCOLE

Author

Onaisi, Racha, Duvignaud, Alexandre, Nguyen Binh, Antoine, Dupouy, Julie, Chastang, Julie, Le Bel, Josselin, Landman, Roland, Naccache, Jean Marc, Lefèvre, Benjamin, Piroth, Lionel, Binquet, C, Makinson, Alain, Darnaud, Thomas, Begue, Cyril, Weiss, Laurence, Richert, Laura, Anglaret, Xavier, Denis, Malvy, Joseph, Jean Philippe, Druais, Pierre Louis, Darmon, David, Ral, Cedric, Lhomme, Edouard, Saint-Lary, Olivier, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Groupe hospitalier Pellegrin, Global Health in the Global South (GHiGS), Institut de Recherche pour le Développement (IRD)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sorbonne Université (SU), Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'investigation clinique de Toulouse (CIC 1436), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Pôle Santé publique et médecine publique [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre hospitalier Saint-Joseph [Paris], Centre Hospitalier Universitaire de Nancy (CHU Nancy), CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre d'Investigation Clinique 1432 (Dijon) - Epidemiologie Clinique/Essais Cliniques (CIC-EC), Université de Bourgogne (UB)-Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Centre Hospitalier Bastia (CHB), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Immunologie humaine, physiopathologie & immunothérapie (HIPI (UMR_S_976 / U976)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Haute Autorité de Santé [Saint-Denis La Plaine] (HAS), Université Côte d'Azur (UCA), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Nantes (UN), Centre de Recherche en Cancérologie et Immunologie Nantes-Angers (CRCINA), Université d'Angers (UA)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, and Dupuis, Christine

Subjects
treatment, [SDV]Life Sciences [q-bio], protocols, trial, Internal, controlled, clinical, [SDV] Life Sciences [q-bio], early, randomized, outpatient, Medicine, General, Covid-19
Abstract

Context. The Covid-19 pandemic is of unprecedented magnitude and has had major social and health consequences. Primary care professionals, mainly general practitioners, ensure the care of most patients with Covid-19. An early-stage treatment administered to patients with risk factors for developing a severe disease could reduce hospitalization and death rates. No treatment is currently validated in this indication. Objectives. To evaluate the safety and efficacy of experimental candidate agents delivered in outpatient settings to reduce the risk of hospitalization or death in at-risk patients with early-stage proven Covid-19 and no indication for hospital admission. Methods. Multicentric, open-label, multi-arm, multi-stage (MAMS) randomized controlled trial with a pilot tolerability and safety phase, and a clinical efficacy phase. Efficacy will be determined by the proportion of participants who have an indication for hospital admission, administration of acute oxygen therapy (because of Covid-19) or who decease between D0 and D14 in the experimental treatment group compared to the control group. Expected results. This trial will assess the tolerance and efficacy of diverse treatments administered at an early stage of Covid-19, in patients with risk factors of developing a severe disease. It will also provide information that can contribute to increase primary care actors' ability to conduct clinical trials at the national level., Contexte. La pandémie de Covid-19 a eu d’importantes répercussions sanitaires et sociales. Les acteurs de soins primaires, en particulier les spécialistes de médecine générale, prennent en charge la majorité des patients atteints de Covid-19. Un traitement précoce initié en première ligne, notamment chez les patients à risque d’aggravation, pourrait réduire les taux d’hospitalisation et de décès. Aucun traitement n’est actuellement validé dans cette indication.Objectif. Évaluer l’efficacité et la tolérance de traitements expérimentaux administrés à un stade précoce, en ambulatoire, dans le but de diminuer le risque de développer une forme sévère de la maladie chez des patients atteints de Covid-19 ayant des facteurs de risque d’aggravation et qui n’ont pas de critères d’hospitalisation.Méthodes. Essai thérapeutique contrôlé randomisé multicentrique, en ouvert, multi-bras, multi-étapes (MAMS) comprenant une phase pilote d’évaluation de la tolérance et une phase d’évaluation de l’efficacité. L’efficacité sera évaluée par la proportion de participants ayant eu une indication d’hospitalisation, une indication d’oxygénothérapie aiguë (en raison de la Covid-19), ou décédés entre J0 et J14 dans le groupe traitement expérimental par rapport au groupe témoin. Résultats attendus. Cet essai permettra d’évaluer la tolérance et l’efficacité de l’administration précoce de divers traitements dans le cadre de la Covid-19 chez des patients à risque de développer des formes graves. Il fournira également des informations susceptibles d’améliorer la recherche clinique interventionnelle impliquant la personne humaine en soins primaires et sa structuration.

Published
2021

46. Le Centre d’Innovation du partenariat avec les patients et le public : un moteur du développement de la culture du partenariat de soin avec le patient, avec les patients et le public en Europe

Author

Flora, Luigi, Benattar, Jean-Michel, Darmon, David, Centre d'Innovation du Partenariat avec les Patients et le Public, Faculté de médecine, Université Côte d'Azur (CI3P), Faculté de médecine, Université Côte d'Azur, Risques, Epidémiologie, Territoire, INformations, Education et Santé (RETINES), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA), Centre National de Ressources et Résilience (CN2R), Centre de recherche interuniversitaire, Expérience, Ressources Culturelles, Education (EXPERICE), Université Paris 8 Vincennes-Saint-Denis (UP8)-Université de Pau et des Pays de l'Adour (UPPA)-LABEX ICCA, Université Paris 13 (UP13)-Université Sorbonne Nouvelle - Paris 3-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord-Université Paris 13 (UP13)-Université Sorbonne Nouvelle - Paris 3-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord-Université Sorbonne Paris Nord, Centre d'Etudes des Solidarités Sociales (Ass.1901) (CESOL), Association, Centre de recherches juridiques de Paris 8 (CRJP8), Université Paris 8 Vincennes-Saint-Denis (UP8), Direction Collaboration et Partenariat Patient, Faculté de médecine, Université de Montréal (DCPP), and Département d'enseignement et de recherche en médecine générale(DERMG), faculté de médecine, Université Côte d'azur (DERMG)

Subjects
ComputingMilieux_MISCELLANEOUS, [SHS]Humanities and Social Sciences
Abstract

International audience

Published
2020

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