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

Author

Listed:
  • Jonás Carmona-Pírez

    (EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Delicias-Sur Primary Care Health Centre, Aragon Health Service (SALUD), 50009 Zaragoza, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain)

  • Beatriz Poblador-Plou

    (EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain
    These authors contributed equally to this work.)

  • Antonio Poncel-Falcó

    (EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain
    Aragon Health Service (SALUD), 50017 Zaragoza, Spain)

  • Jessica Rochat

    (Division of Medical Information Sciences, Geneva University Hospitals, 1205 Geneva, Switzerland
    Department of Radiology and Medical Informatics, University of Geneva, 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
    Department of Radiology and Medical Informatics, University of Geneva, 1205 Geneva, Switzerland)

  • Christian Lovis

    (Division of Medical Information Sciences, Geneva University Hospitals, 1205 Geneva, Switzerland
    Department of Radiology and Medical Informatics, University of Geneva, 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
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain
    Aragon Health Service (SALUD), 50017 Zaragoza, Spain)

  • Antonio Gimeno-Miguel

    (EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain
    These authors contributed equally to this work.)

  • Alexandra Prados-Torres

    (EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, 50009 Zaragoza, Spain
    Health Services Research on Chronic Patients Network (REDISSEC), ISCIII, 28029 Madrid, Spain
    Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS), ISCIII, 28029 Madrid, Spain
    These authors contributed equally to this work.)

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.

Suggested Citation

  • 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 , 2022. "Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and Their Association with Mortality through a Frequent Pattern Growth Association Algorithm," IJERPH, MDPI, vol. 19(4), pages 1-10, February.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2040-:d:747525
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    References listed on IDEAS

    as
    1. Ignatios Ioakeim-Skoufa & Beatriz Poblador-Plou & Jonás Carmona-Pírez & Jesús Díez-Manglano & Rokas Navickas & Luis Andrés Gimeno-Feliu & Francisca González-Rubio & Elena Jureviciene & Laimis Dambraus, 2020. "Multimorbidity Patterns in the General Population: Results from the EpiChron Cohort Study," IJERPH, MDPI, vol. 17(12), pages 1-15, June.
    2. Palmer, Katie & Marengoni, Alessandra & Forjaz, Maria João & Jureviciene, Elena & Laatikainen, Tiina & Mammarella, Federica & Muth, Christiane & Navickas, Rokas & Prados-Torres, Alexandra & Rijken, Mi, 2018. "Multimorbidity care model: Recommendations from the consensus meeting of the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS)," Health Policy, Elsevier, vol. 122(1), pages 4-11.
    Full references (including those not matched with items on IDEAS)

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