Protocol of the pilot study to test and evaluate the iCARE tool: a machine learning-based e-platform tool to make health prognoses and support decision-making for the care of older persons with complex chronic conditions.

Journal: BMJ open
PMID: 40254305

Abstract

INTRODUCTION: The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challenges, the I-CARE4OLD project, funded by the EU-Horizon 2020 programme, developed an advanced clinical decision support tool-the iCARE tool-leveraging large longitudinal data from millions of home care and nursing home recipients across eight countries. The tool uses machine learning techniques applied to data from interRAI assessments, enriched with registry data, to predict health trajectories and evaluate pharmacological and non-pharmacological interventions. This study aims to pilot the iCARE tool and assess its feasibility, usability and impact on clinical decision-making among healthcare professionals.

Authors

  • Anna-Maria Hiltunen
    Nordic Healthcare Group, Helsinki, Finland.
  • Ira Haavisto
    Nordic Healthcare Group, Helsinki, Finland.
  • Mikko Nuutinen
    Nordic Healthcare Group, Helsinki, Finland.
  • Mari Lahelma
    Nordic Healthcare Group, Helsinki, Finland.
  • Anna Salminen
    Nordic Healthcare Group, Helsinki, Finland.
  • Johanna De Almeida Mello
    LUCAS, Center for Care Research and Consultancy, KU Leuven, Leuven, Belgium.
  • Rosa Liperoti
    Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
  • Elizabeth P Howard
    Connell School of Nursing, Boston College, Chestnut Hill, Boston, MA, USA.
  • Daniela Fialová
    Department of Social and Clinical Pharmacy, Faculty of Pharmacy, Charles University, Hradec Králové, Czech Republic.
  • Katarzyna Szczerbińska
    Laboratory for Research on Aging Society, Chair of Epidemiology and Preventive Medicine, Medical Faculty, Jagiellonian University Medical College, Kraków, Poland.
  • Mor Alon
    Profility Inc, Checker Software Solutions, Haifa, Israel.
  • Ilona Barańska
    Laboratory for Research on Aging Society, Chair of Epidemiology and Preventive Medicine, Medical Faculty, Jagiellonian University Medical College, Kraków, Poland.
  • Collin Exmann
    Department of General Practice, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Anja Declercq
    LUCAS, Center for Care Research and Consultancy, KU Leuven, Leuven, Belgium.
  • Wiebe Boorsma
    Department of General Practice, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Graziano Onder
    Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Instituto Superiore di Sanità, Rome, Italy.
  • Hein P J van Hout
    Amsterdam UMC, Vrije Universiteit Amsterdam, department of General Practice & Elderly Care Medicine, Amsterdam Public Health research institute, De Boelelaan 1117, Amsterdam, Netherlands.
  • Riikka-Leena Leskelä
    Department of Public Health, University of Helsinki, Helsinki, Finland; Nordic Healthcare Group, Helsinki, Finland.

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