Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and Their Association with Mortality through a Frequent Pattern Growth Association Algorithm

Jonás Carmona-Pírez, Beatriz Poblador-Plou, Antonio Poncel-Falcó, Jessica Rochat, Celia Alvarez-Romero, Alicia Martínez-García, Carmen Angioletti, Marta Almada, Mert Gencturk, A. Anil Sinaci, Jara Eloisa Ternero-Vega, Christophe Gaudet-Blavignac, Christian Lovis, Rosa Liperoti, Elisio Costa, Carlos Luis Parra-Calderón, Aida Moreno-Juste, Antonio Gimeno-Miguel and Alexandra Prados-Torres
Additional contact information
Jonás Carmona-Pírez: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
Beatriz Poblador-Plou: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
Antonio Poncel-Falcó: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
Jessica Rochat: Division of Medical Information Sciences, Geneva University Hospitals, 1205 Geneva, Switzerland
Celia Alvarez-Romero: Group of Research and Innovation in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville (IBiS), Virgen del Rocío University Hospital/CSIC/University of Seville, 41013 Seville, Spain
Alicia Martínez-García: Group of Research and Innovation in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville (IBiS), Virgen del Rocío University Hospital/CSIC/University of Seville, 41013 Seville, Spain
Carmen Angioletti: Department of Geriatric and Orthopedic Sciences, Catholic University of Sacred Heart, 00168 Rome, Italy
Marta Almada: Ucibio Requimte, Faculty of Pharmacy, University of Porto, Porto4Ageing, 4050-313 Porto, Portugal
Mert Gencturk: SRDC Software Research & Development and Consultancy Corporation, Ankara 06800, Turkey
A. Anil Sinaci: SRDC Software Research & Development and Consultancy Corporation, Ankara 06800, Turkey
Jara Eloisa Ternero-Vega: Internal Medicine Department, Virgen del Rocío University Hospital, 41013 Seville, Spain
Christophe Gaudet-Blavignac: Division of Medical Information Sciences, Geneva University Hospitals, 1205 Geneva, Switzerland
Christian Lovis: Division of Medical Information Sciences, Geneva University Hospitals, 1205 Geneva, Switzerland
Rosa Liperoti: Department of Geriatric and Orthopedic Sciences, Catholic University of Sacred Heart, 00168 Rome, Italy
Elisio Costa: Ucibio Requimte, Faculty of Pharmacy, University of Porto, Porto4Ageing, 4050-313 Porto, Portugal
Carlos Luis Parra-Calderón: Group of Research and Innovation in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville (IBiS), Virgen del Rocío University Hospital/CSIC/University of Seville, 41013 Seville, Spain
Aida Moreno-Juste: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
Antonio Gimeno-Miguel: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
Alexandra Prados-Torres: EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain

IJERPH, 2022, vol. 19, issue 4, 1-10

Abstract: The current availability of electronic health records represents an excellent research opportunity on multimorbidity, one of the most relevant public health problems nowadays. However, it also poses a methodological challenge due to the current lack of tools to access, harmonize and reuse research datasets. In FAIR4Health, a European Horizon 2020 project, a workflow to implement the FAIR (findability, accessibility, interoperability and reusability) principles on health datasets was developed, as well as two tools aimed at facilitating the transformation of raw datasets into FAIR ones and the preservation of data privacy. As part of this project, we conducted a multicentric retrospective observational study to apply the aforementioned FAIR implementation workflow and tools to five European health datasets for research on multimorbidity. We applied a federated frequent pattern growth association algorithm to identify the most frequent combinations of chronic diseases and their association with mortality risk. We identified several multimorbidity patterns clinically plausible and consistent with the bibliography, some of which were strongly associated with mortality. Our results show the usefulness of the solution developed in FAIR4Health to overcome the difficulties in data management and highlight the importance of implementing a FAIR data policy to accelerate responsible health research.

Keywords: FAIR principles; multimorbidity; mortality; research data management; pathfinder case study; privacy-preserving distributed data mining (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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