Viet-Thi Tran1, Philippe Ravaud2. 1. METHODS Team, Université de Paris, CRESS, INSERM, INRA, F-75004 Paris, France; Center for Clinical Epidemiology, Hôtel-Dieu Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), 1 Place du Parvis Notre Dame, 75004 Paris, France. Electronic address: thi.tran-viet@aphp.fr. 2. METHODS Team, Université de Paris, CRESS, INSERM, INRA, F-75004 Paris, France; Center for Clinical Epidemiology, Hôtel-Dieu Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), 1 Place du Parvis Notre Dame, 75004 Paris, France; Department of Epidemiology, Columbia University Mailman School of Public Health, 22 W 168th St, New York, NY, USA.
Abstract
BACKGROUND: The current clinical research system relies on a "one-off" project-by-project model involving a costly and time-wasting permanent construction and deconstruction of the research infrastructure. We propose a new model of research relying on collaborative principles: the COllaborative Open Platform (COOP') e-cohort. DEVELOPMENT: The COOP' e-cohort aims at building a large community of patients willing to participate in research by contributing to the generation of a large database of patient-reported data, passively enriched, at the individual level, by linkage with routinely collected care and/or medico-administrative data. Approved teams can use the platform and benefit from already enrolled participants or collected data or add new online questionnaires to perform observational or interventional studies to answer a broad range of research questions. APPLICATION: The Community of Patients for Research (ComPaRe) is a proof-of-concept COOP' e-cohort in the field of chronic conditions that was launched in 2017. As of April 2020, 36,000 patients have joined the project and contributed to more than 4 million data points. Patient-reported data will be enriched by linkage with the French national health system databases and with hospital data for patients receiving care in the Paris region. Since 2017, 150 researchers have used the platform for research projects. Three clinical trials nested in ComPaRe have been funded. CONCLUSION: By moving from myriad independent studies to a large collaborative infrastructure of research, COOP' e-cohorts will accelerate the research process by avoiding the redundancy of many steps common to all research projects and by limiting waste of research.
BACKGROUND: The current clinical research system relies on a "one-off" project-by-project model involving a costly and time-wasting permanent construction and deconstruction of the research infrastructure. We propose a new model of research relying on collaborative principles: the COllaborative Open Platform (COOP') e-cohort. DEVELOPMENT: The COOP' e-cohort aims at building a large community of patients willing to participate in research by contributing to the generation of a large database of patient-reported data, passively enriched, at the individual level, by linkage with routinely collected care and/or medico-administrative data. Approved teams can use the platform and benefit from already enrolled participants or collected data or add new online questionnaires to perform observational or interventional studies to answer a broad range of research questions. APPLICATION: The Community of Patients for Research (ComPaRe) is a proof-of-concept COOP' e-cohort in the field of chronic conditions that was launched in 2017. As of April 2020, 36,000 patients have joined the project and contributed to more than 4 million data points. Patient-reported data will be enriched by linkage with the French national health system databases and with hospital data for patients receiving care in the Paris region. Since 2017, 150 researchers have used the platform for research projects. Three clinical trials nested in ComPaRe have been funded. CONCLUSION: By moving from myriad independent studies to a large collaborative infrastructure of research, COOP' e-cohorts will accelerate the research process by avoiding the redundancy of many steps common to all research projects and by limiting waste of research.
Authors: Van Thu Nguyen; Philippe Ravaud; Viet Thi Tran; Bridget Young; Isabelle Boutron Journal: J Med Internet Res Date: 2022-02-01 Impact factor: 5.428