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1. A randomized simulation trial evaluating ABiMed, a clinical decision support system for medication reviews and polypharmacy management

Author

Mouazer, Abdelmalek, Dubois, Sophie, Léguillon, Romain, Boudegzdame, Nada, Levrard, Thibaud, Bars, Yoann Le, Simon, Christian, Séroussi, Brigitte, Grosjean, Julien, Lelong, Romain, Letord, Catherine, Darmoni, Stéfan, Sedki, Karima, Meneton, Pierre, Tsopra, Rosy, Falcoff, Hector, and Lamy, Jean-Baptiste

Subjects
Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, J.3
Abstract

Background: Medication review is a structured interview of the patient, performed by the pharmacist and aimed at optimizing drug treatments. In practice, medication review is a long and cognitively-demanding task that requires specific knowledge. Clinical practice guidelines have been proposed, but their application is tedious. Methods: We designed ABiMed, a clinical decision support system for medication reviews, based on the implementation of the STOPP/START v2 guidelines and on the visual presentation of aggregated drug knowledge using tables, graphs and flower glyphs. We evaluated ABiMed with 39 community pharmacists during a randomized simulation trial, each pharmacist performing a medication review for two fictitious patients without ABiMed, and two others with ABiMed. We recorded the problems identified by the pharmacists, the interventions proposed, the response time, the perceived usability and the comments. Pharmacists' medication reviews were compared to an expert-designed gold standard. Results: With ABiMed, pharmacists found 1.6 times more relevant drug-related problems during the medication review (p=1.1e-12) and proposed better interventions (p=9.8e-9), without needing more time (p=0.56). The System Usability Scale score is 82.7, which is ranked "excellent". In their comments, pharmacists appreciated the visual aspect of ABiMed and its ability to compare the current treatment with the proposed one. A multifactor analysis showed no difference in the support offered by ABiMed according to the pharmacist's age or sex, in terms of percentage of problems identified or quality of the proposed interventions. Conclusions: The use of an intelligent and visual clinical decision support system can help pharmacists when they perform medication reviews. Our main perspective is the validation of the system in clinical conditions., Comment: 8 pages, 6 figures

Published
2024

2. Impact on clinical guideline adherence of Orient-COVID, a CDSS based on dynamic medical decision trees for COVID19 management: a randomized simulation trial

Author

Jammal, Mouin, Saab, Antoine, Khalil, Cynthia Abi, Mourad, Charbel, Tsopra, Rosy, Saikali, Melody, and Lamy, Jean-Baptiste

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, 92C50 (Primary), 68U35 (Secondary)
Abstract

Background: The adherence of clinicians to clinical practice guidelines is known to be low, including for the management of COVID-19, due to their difficult use at the point of care and their complexity. Clinical decision support systems have been proposed to implement guidelines and improve adherence. One approach is to permit the navigation inside the recommendations, presented as a decision tree, but the size of the tree often limits this approach and may cause erroneous navigation, especially when it does not fit in a single screen. Methods: We proposed an innovative visual interface to allow clinicians easily navigating inside decision trees for the management of COVID-19 patients. It associates a multi-path tree model with the use of the fisheye visual technique, allowing the visualization of large decision trees in a single screen. To evaluate the impact of this tool on guideline adherence, we conducted a randomized controlled trial in a near-real simulation setting, comparing the decisions taken by medical students using Orient-COVID with those taken with paper guidelines or without guidance, when performing on six realistic clinical cases. Results: The results show that paper guidelines had no impact (p=0.97), while Orient-COVID significantly improved the guideline adherence compared to both other groups (p<0.0003). A significant impact of Orient-COVID was identified on several key points during the management of COVID-19: ordering troponin lab tests, prescribing anticoagulant and oxygen therapy. A multifactor analysis showed no difference between male and female participants. Conclusions: The use of an interactive decision tree for the management of COVID-19 significantly improved the clinician adherence to guidelines. Future works will focus on the integration of the system to electronic health records and on the adaptation of the system to other clinical conditions., Comment: 8 pages, 5 figures

Published
2024

3. A Web Interface for Antibiotic Prescription Recommendations in Primary Care: User-Centered Design Approach

Author

Madar, Ronni, Ugon, Adrien, Ivanković, Damir, and Tsopra, Rosy

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundAntibiotic misuse is a serious public health problem worldwide. National health authorities release clinical practice guidelines (CPGs) to guide general practitioners (GPs) in their choice of antibiotics. However, despite the large-scale dissemination of CPGs, GPs continue to prescribe antibiotics that are not recommended as first-line treatments. This nonadherence to recommendations may be due to GPs misunderstanding the CPGs. A web interface displaying antibiotic prescription recommendations and their justifications could help to improve the comprehensibility and readability of CPGs, thereby increasing the adoption of recommendations regarding antibiotic treatment. ObjectiveThis study aims to design and evaluate a web interface for antibiotic prescription displaying both the recommended antibiotics and their justifications in the form of antibiotic properties. MethodsA web interface was designed according to the same principles as e-commerce interfaces and was assessed by 117 GPs. These GPs were asked to answer 17 questions relating to the usefulness, user-friendliness, and comprehensibility and readability of the interface, and their satisfaction with it. Responses were recorded on a 4-point Likert scale (ranging from “absolutely disagree” to “absolutely agree”). At the end of the evaluation, the GPs were allowed to provide optional, additional free comments. ResultsThe antibiotic prescription web interface consists of three main sections: a clinical summary section, a filter section, and a recommended antibiotics section. The majority of GPs appreciated the clinical summary (90/117, 76.9%) and filter (98/117, 83.8%) sections, whereas 48.7% (57/117) of them reported difficulty reading some of the icons in the recommended antibiotics section. Overall, 82.9% (97/117) of GPs found the display of drug properties useful, and 65.8% (77/117) reported that the web interface improved their understanding of CPG recommendations. ConclusionsThe web interface displaying antibiotic recommendations and their properties can help doctors understand the rationale underlying CPG recommendations regarding antibiotic treatment, but further improvements are required before its implementation into a clinical decision support system.

Published
2021
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4. Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic

Author

Neuraz, Antoine, Lerner, Ivan, Digan, William, Paris, Nicolas, Tsopra, Rosy, Rogier, Alice, Baudoin, David, Cohen, Kevin Bretonnel, Burgun, Anita, Garcelon, Nicolas, and Rance, Bastien

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundA novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, which require a preexisting data or knowledge model; however, novel diseases do not have preexisting knowledge models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to a novel knowledge model. However, although this idea has often been suggested, no opportunity has arisen to actually test it in real time. The current coronavirus disease (COVID-19) pandemic presents such an opportunity. ObjectiveThe aim of this study was to evaluate the added value of information from clinical text in response to emergent diseases using natural language processing (NLP). MethodsWe explored the effects of long-term treatment by calcium channel blockers on the outcomes of COVID-19 infection in patients with high blood pressure during in-patient hospital stays using two sources of information: data available strictly from structured electronic health records (EHRs) and data available through structured EHRs and text mining. ResultsIn this multicenter study involving 39 hospitals, text mining increased the statistical power sufficiently to change a negative result for an adjusted hazard ratio to a positive one. Compared to the baseline structured data, the number of patients available for inclusion in the study increased by 2.95 times, the amount of available information on medications increased by 7.2 times, and the amount of additional phenotypic information increased by 11.9 times. ConclusionsIn our study, use of calcium channel blockers was associated with decreased in-hospital mortality in patients with COVID-19 infection. This finding was obtained by quickly adapting an NLP pipeline to the domain of the novel disease; the adapted pipeline still performed sufficiently to extract useful information. When that information was used to supplement existing structured data, the sample size could be increased sufficiently to see treatment effects that were not previously statistically detectable.

Published
2020
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5. ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management

Author

Mouazer, Abdelmalek, Léguillon, Romain, Boudegzdame, Nada, Levrard, Thibaud, Bars, Yoann Le, Simon, Christian, Séroussi, Brigitte, Grosjean, Julien, Lelong, Romain, Letord, Catherine, Darmoni, Stéfan, Schuers, Matthieu, Sedki, Karima, Dubois, Sophie, Falcoff, Hector, Tsopra, Rosy, and Lamy, Jean-Baptiste

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, I.2.1 J.3
Abstract

Background: Polypharmacy, i.e. taking five drugs or more, is both a public health and an economic issue. Medication reviews are structured interviews of the patient by the community pharmacist, aiming at optimizing the drug treatment and deprescribing useless, redundant or dangerous drugs. However, they remain difficult to perform and time-consuming. Several clinical decision support systems were developed for helping clinicians to manage polypharmacy. However, most were limited to the implementation of clinical practice guidelines. In this work, our objective is to design an innovative clinical decision support system for medication reviews and polypharmacy management, named ABiMed. Methods: ABiMed associates several approaches: guidelines implementation, but the automatic extraction of patient data from the GP's electronic health record and its transfer to the pharmacist, and the visual presentation of contextualized drug knowledge using visual analytics. We performed an ergonomic assessment and qualitative evaluations involving pharmacists and GPs during focus groups and workshops. Results: We describe the proposed architecture, which allows a collaborative multi-user usage. We present the various screens of ABiMed for entering or verifying patient data, for accessing drug knowledge (posology, adverse effects, interactions), for viewing STOPP/START rules and for suggesting modification to the treatment. Qualitative evaluations showed that health professionals were highly interested by our approach, associating the automatic guidelines execution with the visual presentation of drug knowledge. Conclusions: The association of guidelines implementation with visual presentation of knowledge is a promising approach for managing polypharmacy. Future works will focus on the improvement and the evaluation of ABiMed., Comment: 10 pages, 7 figures

Published
2023

18. ABiMed: Towards an Innovative Clinical Decision Support System for Medication Reviews and Polypharmacy Management

Author

Mouazer, Abdelmalek, primary, Leguillon, Romain, additional, Leroy, Bertille, additional, Sedki, Karima, additional, Simon, Christian, additional, Falcoff, Hector, additional, Schuers, Matthieu, additional, Dubois, Sophie, additional, Bousquet, Cédric, additional, Soualmia, Lina, additional, Letord, Catherine, additional, Darmoni, Stéfan, additional, Bouaud, Jacques, additional, Séroussi, Brigitte, additional, Tsopra, Rosy, additional, and Lamy, Jean-Baptiste, additional

Published
2022
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21. A semi-automatic semantic method for mapping SNOMED CT concepts to VCM Icons

Author

Lamy, Jean-Baptiste, Tsopra, Rosy, Venot, Alain, and Duclos, Catherine

Subjects
Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

VCM (Visualization of Concept in Medicine) is an iconic language for representing key medical concepts by icons. However, the use of this language with reference terminologies, such as SNOMED CT, will require the mapping of its icons to the terms of these terminologies. Here, we present and evaluate a semi-automatic semantic method for the mapping of SNOMED CT concepts to VCM icons. Both SNOMED CT and VCM are compositional in nature; SNOMED CT is expressed in description logic and VCM semantics are formalized in an OWL ontology. The proposed method involves the manual mapping of a limited number of underlying concepts from the VCM ontology, followed by automatic generation of the rest of the mapping. We applied this method to the clinical findings of the SNOMED CT CORE subset, and 100 randomly-selected mappings were evaluated by three experts. The results obtained were promising, with 82 of the SNOMED CT concepts correctly linked to VCM icons according to the experts. Most of the errors were easy to fix.

Published
2013

22. General practitioners’ deprescribing decisions in older adults with polypharmacy: a case vignette study in 31 countries

Author

Jungo, Katharina Tabea, Mantelli, Sophie, Rozsnyai, Zsofia, Missiou, Aristea, Kitanovska, Biljana Gerasimovska, Weltermann, Birgitta, Mallen, Christian, Collins, Claire, Bonfim, Daiana, Kurpas, Donata, Petrazzuoli, Ferdinando, Dumitra, Gindrovel, Thulesius, Hans, Lingner, Heidrun, Johansen, Kasper Lorenz, Wallis, Katharine, Hoffmann, Kathryn, Peremans, Lieve, Pilv, Liina, Šter, Marija Petek, Bleckwenn, Markus, Sattler, Martin, van der Ploeg, Milly, Torzsa, Péter, Kánská, Petra Bomberová, Vinker, Shlomo, Assenova, Radost, Bravo, Raquel Gomez, Viegas, Rita P. A., Tsopra, Rosy, Pestic, Sanda Kreitmayer, Gintere, Sandra, Koskela, Tuomas H., Lazic, Vanja, Tkachenko, Victoria, Reeve, Emily, Luymes, Clare, Poortvliet, Rosalinde K. E., Rodondi, Nicolas, Gussekloo, Jacobijn, and Streit, Sven

Published
2021
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24. A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

Author

Tsopra, Rosy, Fernandez, Xose, Luchinat, Claudio, Alberghina, Lilia, Lehrach, Hans, Vanoni, Marco, Dreher, Felix, Sezerman, O.Ugur, Cuggia, Marc, de Tayrac, Marie, Miklasevics, Edvins, Itu, Lucian Mihai, Geanta, Marius, Ogilvie, Lesley, Godey, Florence, Boldisor, Cristian Nicolae, Campillo-Gimenez, Boris, Cioroboiu, Cosmina, Ciusdel, Costin Florian, Coman, Simona, Hijano Cubelos, Oliver, Itu, Alina, Lange, Bodo, Le Gallo, Matthieu, Lespagnol, Alexandra, Mauri, Giancarlo, Soykam, H.Okan, Rance, Bastien, Turano, Paola, Tenori, Leonardo, Vignoli, Alessia, Wierling, Christoph, Benhabiles, Nora, and Burgun, Anita

Published
2021
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27. An Integrated Pipeline for Phenotypic Characterization, Clustering and Visualization of Patient Cohorts in a Rare Disease-Oriented Clinical Data Warehouse.

Author

Xiaoyi CHEN, Junyuan WANG, FAVIEZ, Carole, Xiaomeng WANG, VINCENT, Marc, TSOPRA, Rosy, BURGUN, Anita, and GARCELON, Nicolas

Abstract

Rare diseases pose significant challenges due to their heterogeneity and lack of knowledge. This study develops a comprehensive pipeline interoperable with a document-oriented clinical data warehouse, integrating cohort characterization, patient clustering and interpretation. Leveraging NLP, semantic similarity, machine learning and visualization, the pipeline enables the identification of prevalent phenotype patterns and patient stratification. To enhance interpretability, discriminant phenotypes characterizing each cluster are provided. Users can visually test hypotheses by marking patients exhibiting specific keywords in the EHR like genes, drugs and procedures. Implemented through a web interface, the pipeline enables clinicians to navigate through different modules, discover intricate patterns and generate interpretable insights that may advance rare diseases understanding, guide decision-making, and ultimately improve patient outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Patient Characteristics and General Practitioners’ Advice to Stop Statins in Oldest-Old Patients: a Survey Study Across 30 Countries

Author

van der Ploeg, Milly A., Streit, Sven, Achterberg, Wilco P., Beers, Erna, Bohnen, Arthur M., Burman, Robert A., Collins, Claire, Franco, Fabio G., Gerasimovska-Kitanovska, Biljana, Gintere, Sandra, Gomez Bravo, Raquel, Hoffmann, Kathryn, Iftode, Claudia, Peštić, Sanda Kreitmayer, Koskela, Tuomas H., Kurpas, Donata, Maisonneuve, Hubert, Mallen, Christan D., Merlo, Christoph, Mueller, Yolanda, Muth, Christiane, Petrazzuoli, Ferdinando, Rodondi, Nicolas, Rosemann, Thomas, Sattler, Martin, Schermer, Tjard, Šter, Marija Petek, Švadlenková, Zuzana, Tatsioni, Athina, Thulesius, Hans, Tkachenko, Victoria, Torzsa, Péter, Tsopra, Rosy, Tuz, Canan, Vaes, Bert, Viegas, Rita P. A., Vinker, Shlomo, Wallis, Katharine A., Zeller, Andreas, Gussekloo, Jacobijn, and Poortvliet, Rosalinde K. E.

Published
2019
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33. eOSCE stations live versus remote evaluation and scores variability

Author

Bouzid, Donia, Mullaert, Jimmy, Ghazali, Aiham, Ferré, Valentine Marie, Mentré, France, Lemogne, Cédric, Ruszniewski, Philippe, Faye, Albert, Dinh, Alexy Tran, Mirault, Tristan, Smadja, Nathan Peiffer, Muller, Léonore, Pierrotin, Laure Falque, Thy, Michael, Assadi, Maksud, Yung, Sonia, de Tymowski, Christian, Le Hingrat, Quentin, Eyer, Xavier, Wicky, Paul Henri, Oualha, Mehdi, Houdouin, Véronique, Jabre, Patricia, Vodovar, Dominique, Burgio, Marco Dioguardi, Zucman, Noémie, Tsopra, Rosy, Tazi, Asmaa, Ressaire, Quentin, Nguyen, Yann, Girard, Muriel, Frachon, Adèle, Depret, François, Pellat, Anna, de Masson, Adèle, Azais, Henri, de Castro, Nathalie, Jeantrelle, Caroline, Javaud, Nicolas, Malmartel, Alexandre, de Margerie, Constance Jacquin, Chousterman, Benjamin, Fournel, Ludovic, Holleville, Mathilde, Blanche, Stéphane, 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, Institut de psychiatrie et neurosciences de Paris (IPNP - U1266 Inserm), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Hôpital Beaujon [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), AP-HP Hôpital universitaire Robert-Debré [Paris], CIC Hôpital Bichat, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-UFR de Médecine, Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Health data- and model- driven Knowledge Acquisition (HeKA), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), and Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138))

Subjects
[SHS.EDU]Humanities and Social Sciences/Education, General Medicine, Education
Abstract

Background Objective structured clinical examinations (OSCEs) are known to be a fair evaluation method. These recent years, the use of online OSCEs (eOSCEs) has spread. This study aimed to compare remote versus live evaluation and assess the factors associated with score variability during eOSCEs. Methods We conducted large-scale eOSCEs at the medical school of the Université de Paris Cité in June 2021 and recorded all the students’ performances, allowing a second evaluation. To assess the agreement in our context of multiple raters and students, we fitted a linear mixed model with student and rater as random effects and the score as an explained variable. Results One hundred seventy observations were analyzed for the first station after quality control. We retained 192 and 110 observations for the statistical analysis of the two other stations. The median score and interquartile range were 60 out of 100 (IQR 50–70), 60 out of 100 (IQR 54–70), and 53 out of 100 (IQR 45–62) for the three stations. The score variance proportions explained by the rater (ICC rater) were 23.0, 16.8, and 32.8%, respectively. Of the 31 raters, 18 (58%) were male. Scores did not differ significantly according to the gender of the rater (p = 0.96, 0.10, and 0.26, respectively). The two evaluations showed no systematic difference in scores (p = 0.92, 0.053, and 0.38, respectively). Conclusion Our study suggests that remote evaluation is as reliable as live evaluation for eOSCEs.

Published
2022

34. Design of an ontology-based triage system for painful patients

Author

Saadi, Alexandre, Rogier, Alice, Burgun, Anita, Tsopra, Rosy, Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Health data- and model- driven Knowledge Acquisition (HeKA), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École pratique des hautes études (EPHE), and SAADI, Alexandre

Subjects
MESH: Humans, Clinical Decision Support System, [SDV.MHEP.PHY] Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Ontology, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], Chronic pain, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, MESH: Referral and Consultation, MESH: Systematized Nomenclature of Medicine, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], MESH: Chronic Pain, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, MESH: Triage
Abstract

International audience; Objective: Waiting time for a consultation for chronic pain is a widespread health problem. This paper present the design of an ontology use to assess patients referred to a consultation for chronic pain. Methods: We designed OntoDol, an ontology of pain domain for patient triage based on priority degrees. Terms were extracted from clinical practice guidelines and mapped to SNOMED-CT concepts through the Python module Owlready2. Selected SNOMED-CT concepts, relationships, and the TIME ontology, were implemented in the ontology using Protégé. Decision rules were implemented with SWRL. We evaluated OntoDol on 5 virtual cases. Results: OntoDol contains 762 classes, 92 object properties and 18 SWRL rules to assign patients to 4 categories of priority. OntoDol was able to assert every case and classify them in the right category of priority. Conclusion: Further works will extend OntoDol to other diseases and assess OntoDol with real world data from the hospital.

Published
2022

35. An Integrated Care Platform System (C3-Cloud) for Care Planning, Decision Support, and Empowerment of Patients With Multimorbidity: Protocol for a Technology Trial

Author

von Tottleben, Malte, Grinyer, Katie, Arfa, Ali, Traore, Lamine, Verdoy, Dolores, Lim Choi Keung, Sarah N., Larranaga, Igor, Jaulent, Marie-Christine, De Manuel Keenoy, Esteban, Lilja, Mikael, Beach, Marie, Marguerie, Christopher, Yuksel, Mustafa, Erturkmen, Gokce Banu Laleci, Klein, Gunnar O., Lindman, Pontus, Mar, Javier, Kalra, Dipak, Arvanitis, Theodoros N., Leprovost, Damien, Assele-Kama, Ariane, Dusenne, Mikael, Tsopra, Rosy, Sadou, Eric, Lamas, Eugénia, Toubiana, Laurent, Stroetmann, Veli, Vogt, Jess, Hammerschmidt, Reinhard, Schmidtmann, Daniel, Sherman, Marie, Eriksson, Anna, Gärd, Karin, Zhao, Lei, Despotou, George, Sarıgül, Bünyamin, Teoman, Alper, de Blas, Antonio, González, Nicolás, Fullaondo, Ane, Goode, Phil, Ekestubbe, Goran, Allwell-Brown, Eneimi, Fendukly, Mattias, Palacio, Manuel, Chen, Rong, Vander Stichele, Robert, Thienpont, Geert, von Tottleben, Malte, Grinyer, Katie, Arfa, Ali, Traore, Lamine, Verdoy, Dolores, Lim Choi Keung, Sarah N., Larranaga, Igor, Jaulent, Marie-Christine, De Manuel Keenoy, Esteban, Lilja, Mikael, Beach, Marie, Marguerie, Christopher, Yuksel, Mustafa, Erturkmen, Gokce Banu Laleci, Klein, Gunnar O., Lindman, Pontus, Mar, Javier, Kalra, Dipak, Arvanitis, Theodoros N., Leprovost, Damien, Assele-Kama, Ariane, Dusenne, Mikael, Tsopra, Rosy, Sadou, Eric, Lamas, Eugénia, Toubiana, Laurent, Stroetmann, Veli, Vogt, Jess, Hammerschmidt, Reinhard, Schmidtmann, Daniel, Sherman, Marie, Eriksson, Anna, Gärd, Karin, Zhao, Lei, Despotou, George, Sarıgül, Bünyamin, Teoman, Alper, de Blas, Antonio, González, Nicolás, Fullaondo, Ane, Goode, Phil, Ekestubbe, Goran, Allwell-Brown, Eneimi, Fendukly, Mattias, Palacio, Manuel, Chen, Rong, Vander Stichele, Robert, and Thienpont, Geert

Abstract

Background: There is an increasing need to organize the care around the patient and not the disease, while considering the complex realities of multiple physical and psychosocial conditions, and polypharmacy. Integrated patient-centered care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced information and communication technology solutions for semiautomated clinical decision support. Objective: The Collaborative Care and Cure Cloud project (C3-Cloud) has developed 2 collaborative computer platforms for patients and members of the multidisciplinary team (MDT) and deployed these in 3 different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients with 2 or more chronic conditions (diabetes mellitus type 2, heart failure, kidney failure, depression), their informal caregivers, health care professionals, and, to some extent, health care systems. Methods: This paper describes the protocol for conducting an evaluation of user experience, acceptability, and usefulness of the platforms. For this, 2 “testing and evaluation” phases have been defined, involving multiple qualitative methods (focus groups and surveys) and advanced impact modeling (predictive modeling and cost-benefit analysis). Patients and health care professionals were identified and recruited from 3 partnering regions in Spain, Sweden, and the United Kingdom via electronic health record screening. Results: The technology trial in this 4-year funded project (2016-2020) concluded in April 2020. The pilot technology trial for evaluation phases 3 and 4 was launched in November 2019 and carried out until April 2020. Data collection for these phases is completed with promising results on platform acceptance and socioeconomic impact. We believe that the phased, iterative appro

Published
2022
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37. General practitioners’ perceptions of using virtual primary care during the COVID-19 pandemic: An international cross-sectional survey study

Author

Li, Edmond, primary, Tsopra, Rosy, additional, Jimenez, Geronimo, additional, Serafini, Alice, additional, Gusso, Gustavo, additional, Lingner, Heidrun, additional, Fernandez, Maria Jose, additional, Irving, Greg, additional, Petek, Davorina, additional, Hoffman, Robert, additional, Lazic, Vanja, additional, Memarian, Ensieh, additional, Koskela, Tuomas, additional, Collins, Claire, additional, Espitia, Sandra Milena, additional, Clavería, Ana, additional, Nessler, Katarzyna, additional, O’Neill, Braden Gregory, additional, Hoedebecke, Kyle, additional, Ungan, Mehmet, additional, Laranjo, Liliana, additional, Ghafur, Saira, additional, Fontana, Gianluca, additional, Majeed, Azeem, additional, Car, Josip, additional, Darzi, Ara, additional, and Neves, Ana Luisa, additional

Published
2022
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42. Benefits and Challenges of Using Virtual Primary Care During the COVID-19 Pandemic: An International Cross-sectional Survey Study (Preprint)

Author

Li, Edmond, primary, Tsopra, Rosy, additional, Jimenez, Geronimo, additional, Serafini, Alice, additional, Gusso, Gustavo, additional, Lingner, Heidrun, additional, Fernandez, Maria Jose, additional, Irving, Greg, additional, Petek, Davorina, additional, Hoffman, Robert, additional, Lazic, Vanja, additional, Memarian, Ensieh, additional, Koskela, Tuomas H, additional, Collins, Claire, additional, Espitia, Sandra Milena, additional, Clavería, Ana, additional, Nessler, Katarzyna, additional, O’Neill, Braden Gregory, additional, Hoedebecke, Kyle, additional, Ungan, Mehmet, additional, Laranjo, Liliana, additional, Ghafur, Saira, additional, Fontana, Gianluca, additional, Majeed, Azeem, additional, Car, Josip, additional, Darzi, Ara, additional, and Neves, Ana Luísa, additional

Published
2021
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43. Evaluating the Impact of COVID-19 on the Adoption of Virtual Care in General Practice in 20 Countries (inSIGHT): Protocol and Rationale Study

Author

Neves, Ana Luísa, primary, Li, Edmond, additional, Serafini, Alice, additional, Jimenez, Geronimo, additional, Lingner, Heidrun, additional, Koskela, Tuomas H, additional, Hoffman, Robert D, additional, Collins, Claire, additional, Petek, Davorina, additional, Claveria, Ana, additional, Tsopra, Rosy, additional, Irving, Greg, additional, Gusso, Gustavo, additional, O’Neill, Braden Gregory, additional, Hoedebecke, Kyle, additional, Espitia, Sandra Milena, additional, Ungan, Mehmet, additional, Nessler, Katarzyna, additional, Lazic, Vanja, additional, Laranjo, Liliana, additional, Memarian, Ensieh, additional, Fernandez, Maria Jose, additional, Ghafur, Saira, additional, Fontana, Gianluca, additional, Majeed, Azeem, additional, Car, Josip, additional, and Darzi, Ara, additional

Published
2021
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44. Benefits and Challenges of Using Virtual Primary Care During the COVID-19 Pandemic: From Key Lessons to a Framework for Implementation

Author

Li, Edmond, primary, Tsopra, Rosy, additional, Gimenez, Geronimo Larrain, additional, Serafini, Alice, additional, Gusso, Gustavo, additional, Lingner, Heidrun, additional, Fernandez, Maria Jose, additional, Irving, Greg, additional, Petek, Davorina, additional, Hoffman, Robert, additional, Lazic, Vanja, additional, Ensieh, Memarian, additional, Koskela, Tuomas, additional, Collins, Claire, additional, Espitia, Sandra Milena, additional, Clavería, Ana, additional, Nessler, Katarzyna, additional, O’Neill, Braden Gregory, additional, Hoedebecke, Kyle, additional, Ungan, Mehmet, additional, Laranjo, Liliana, additional, Ghafur, Saira, additional, Fontana, Gianluca, additional, Majeed, Azeem, additional, Car, Josip, additional, Darzi, Ara, additional, and Neves, Ana Luisa, additional

Published
2021
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45. a case vignette study in 31 countries

Author

Jungo, Katharina Tabea, Mantelli, Sophie, Rozsnyai, Zsofia, Missiou, Aristea, Kitanovska, Biljana Gerasimovska, Weltermann, Birgitta, Mallen, Christian, Collins, Claire, Bonfim, Daiana, Kurpas, Donata, Petrazzuoli, Ferdinando, Dumitra, Gindrovel, Thulesius, Hans, Lingner, Heidrun, Johansen, Kasper Lorenz, Wallis, Katharine, Hoffmann, Kathryn, Peremans, Lieve, Pilv, Liina, Šter, Marija Petek, Bleckwenn, Markus, Sattler, Martin, van der Ploeg, Milly, Torzsa, Péter, Kánská, Petra Bomberová, Vinker, Shlomo, Assenova, Radost, Bravo, Raquel Gomez, Viegas, Rita P.A., Tsopra, Rosy, Pestic, Sanda Kreitmayer, Gintere, Sandra, Koskela, Tuomas H., Lazic, Vanja, Tkachenko, Victoria, Reeve, Emily, Luymes, Clare, Poortvliet, Rosalinde K.E., Rodondi, Nicolas, Gussekloo, Jacobijn, Streit, Sven, and NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)

Subjects
Deprescribing, SDG 3 - Good Health and Well-being, Old age, Polypharmacy, Multimorbidity, Geriatrics and Gerontology, Primary health care
Abstract

Funding: The work of Katharina Tabea Jungo was supported by the Swiss National Science Foundation (SNSF) (NFP 407440_167465, PI Prof. Streit) and the work of Zsofia Rozsnyai by the Swiss Society of General Internal Medicine (SGAIM) Foundation (PI Prof. Streit). The SGAIM Foundation reviewed the study protocol but did not give us feedback or help usplan, conduct, interpret results, or write this manuscript. The SNSF had the same role but did not review the study protocol. CM is funded by the National Institute for Health Research (NIHR) Applied Research Collaborations (West Midlands), the NIHR School for Primary Caren Research and an NIHR Research Professorship in General Practice (RP 2014–04-026). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. ER is supported by an NHMRC-ARC Dementia Research Development Fellowship. Background: General practitioners (GPs) should regularly review patients’ medications and, if necessary, deprescribe, as inappropriate polypharmacy may harm patients’ health. However, deprescribing can be challenging for physicians. This study investigates GPs’ deprescribing decisions in 31 countries. Methods: In this case vignette study, GPs were invited to participate in an online survey containing three clinical cases of oldest-old multimorbid patients with potentially inappropriate polypharmacy. Patients differed in terms of dependency in activities of daily living (ADL) and were presented with and without history of cardiovascular disease (CVD). For each case, we asked GPs if they would deprescribe in their usual practice. We calculated proportions of GPs who reported they would deprescribe and performed a multilevel logistic regression to examine the association between history of CVD and level of dependency on GPs’ deprescribing decisions. Results: Of 3,175 invited GPs, 54% responded (N = 1,706). The mean age was 50 years and 60% of respondents were female. Despite differences across GP characteristics, such as age (with older GPs being more likely to take deprescribing decisions), and across countries, overall more than 80% of GPs reported they would deprescribe the dosage of at least one medication in oldest-old patients (> 80 years) with polypharmacy irrespective of history of CVD. The odds of deprescribing was higher in patients with a higher level of dependency in ADL (OR =1.5, 95%CI 1.25 to 1.80) and absence of CVD (OR =3.04, 95%CI 2.58 to 3.57). Interpretation: The majority of GPs in this study were willing to deprescribe one or more medications in oldest-old multimorbid patients with polypharmacy. Willingness was higher in patients with increased dependency in ADL and lower in patients with CVD. publishersversion published

Published
2021

46. Additional file 1 of Reorganisation of GP surgeries during the COVID-19 outbreak: analysis of guidelines from 15 countries

Author

Tsopra, Rosy, Frappe, Paul, Streit, Sven, Neves, Ana Luisa, Persijn J. Honkoop, Espinosa-Gonzalez, Ana Belen, Geroğlu, Berk, Jahr, Tobias, Lingner, Heidrun, Nessler, Katarzyna, Pesolillo, Gabriella, Sivertsen, Øyvind Stople, Thulesius, Hans, Zoitanu, Raluca, Burgun, Anita, and Shérazade Kinouani

Abstract

Additional file 1. Materials sent to each GP-reviewer - Initial set of key recommendations collected from the World Health Organisation (WHO) [14], the Centers for Disease Control and prevention (CDC) [15] and based on health professional resources from health care facilities (GP: general practitioner).

Published
2021
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47. Additional file 2 of Reorganisation of GP surgeries during the COVID-19 outbreak: analysis of guidelines from 15 countries

Author

Tsopra, Rosy, Frappe, Paul, Streit, Sven, Neves, Ana Luisa, Persijn J. Honkoop, Espinosa-Gonzalez, Ana Belen, Geroğlu, Berk, Jahr, Tobias, Lingner, Heidrun, Nessler, Katarzyna, Pesolillo, Gabriella, Sivertsen, Øyvind Stople, Thulesius, Hans, Zoitanu, Raluca, Burgun, Anita, and Shérazade Kinouani

Subjects
Data_FILES
Abstract

Additional file 2. Guidelines used for this study.

Published
2021
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49. Evaluating the impact of COVID-19 on the adoption of virtual care in general practice in 20 countries (inSIGHT): rationale and study protocol (Preprint)

Author

Neves, Ana Luísa, primary, Li, Edmond, additional, Serafini, Alice, additional, Gimenez, Geronimo Larrain, additional, Lingner, Heidrun, additional, Koskela, Tuomas, additional, Hoffman, Robert D, additional, Collins, Claire, additional, Petek, Davorina, additional, Claveria, Ana, additional, Tsopra, Rosy, additional, Irving, Greg, additional, Gusso, Gustavo, additional, O’Neill, Braden Gregory, additional, Hoedebecke, Kyle, additional, Espitia, Sandra Milena, additional, Ungan, Mehmet, additional, Nessler, Katarzyna, additional, Lazic, Vanja, additional, Laranjo, Liliana, additional, Ensieh, Memarian, additional, Fernandez, Maria Jose, additional, Ghafur, Saira, additional, Fontana, Gianluca, additional, Majeed, Azeem, additional, Car, Josip, additional, and Darzi, Ara, additional

Published
2021
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50. Limits and Variability in Drug Databases: Lessons Learnt from Drug Comparisons

Author

Lamy, Jean-Baptiste, Berthelot, Hélène, Favre, Madeleine, Tsopra, Rosy, 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, Société de Formation Thérapeutique du Généraliste (SFTG), Université de Paris - UFR Sciences Fondamentales et Biomédicales [Sciences], Université de Paris (UP), Université Sorbonne Nouvelle - Paris 3 - Institut des Hautes Études de l'Amérique latine (USN IHEAL), Université Sorbonne Nouvelle - Paris 3, Centre Hospitalier Universitaire [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université Paris Cité - UFR Sciences Fondamentales et Biomédicales [Sciences], Université Paris Cité (UPC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), UFR Sciences Fondamentales et Biomédicales [Sciences] - Université Paris Cité, Université Paris Cité (UPCité), and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Drug databases, nervous system, Databases, Factual, Pharmaceutical Preparations, musculoskeletal, neural, and ocular physiology, Computer Graphics, InformationSystems_DATABASEMANAGEMENT, Learning, [SDV.IB]Life Sciences [q-bio]/Bioengineering, macromolecular substances, Nonverbal Communication
Abstract

International audience; Several drug databases exist, but sometimes differ in their content. Here, we propose a taxonomy of the variability we observed, and we present a tool for investigating the variability through the visual comparison of the properties of a given drug as represented in several sources or databases.

Published
2020

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