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I-CARE4OLD Horizon 2020 project
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Project title:
I-CARE4OLD Horizon 2020 project
“Individualized CARE for Older Persons with Complex Chronic Conditions at home and in nursing homes”
period: June 2021 – May 2025
Research areas:
Highly individualized care, clinical pharmacy, geriatric pharmacoepidemiology, next generation decision-support tools, big e-health data, AI analyses, real-world outcomes of pharmacological and non-pharmacological interventions
Description:
EU-funded I-CARE4OLD H2020 project is chaired by Vrie University and VU Medical Centre in Amsterdam, The Netherlands. In the European Consortium there are involved 11 collaborating institutions: Università Cattolica del Sacro Cuore, Italy (co-lead), Charles University, Faculty of Pharmacy in Hradec Králové, Czech Republic (co-work on WP5, WP6 and WP7), Karolinska Institute, Sweden, Finnish Institute for Health and Wellfare and Nordic Healthcare Group, Finland, Jagiellonian University, Poland, Catholic University Leuven, Belgium, Profility, Israel, Hebrew Senior Life, USA, University of Waterloo, Canada, the interRAI corp. and the European Geriatric Medicine Society.
This project applies AI modelling to test real-world outcomes of various interventions (pharmacological and non-pharmacological) and their impact on health and health trajectories in complex seniors with multimorbidity and polypharmacy (impact on functional status measures, hospital and emergency department admissions, frailty, morbidity and mortality). Due to too many co-variates and high interindividual variability, the real-world outcomes of prescribed interventions could not have been tested by traditional randomized controlled, clinical controlled or other traditional epidemiological studies.
By using data of over 50 millions of comprehensive geriatric assessments of complex vulnerable older adults with various chronic disease conditions and various multidrug schemes, and by considering an interplay of many other variables or other multiple risk factors influencing the outcomes, the aim of this project is to develop, test and validate the first AI models describing inter-individual variability of responses of older adults to standardly used pharmacological and non-pharmacological strategies. This project focuses on highly complex and vulnerable older adults in primary care (home care and nursing home care), previously excluded from randomized controlled and other clinical controlled trials.
International, multidisciplinary teams of experts in health, social care and artificial intelligence combine expertise to solve above-described goals. The aim of this project is to develop by AI methods the next-generation decision support SW tool helping to predict individual response of complex older adults to various interventions.
Budget:
Total: 6,492,416 EUR
FoP CUNI: 386,047 EUR
Outcomes:
The outcomes of the project are validated decision support AI algorithms using a variety of techniques of machine learning to predict older individuals´ outcomes/responses (e.g. death, acute hospital admissions, quality of life, changes in functional status measures etc.). SW platform integrating these models and helping (by more appropriate individual predictions) to better select more effective and safer interventions for healthcare professionals is developed, as well as guidances on how to interpret findings of this SW platform.
The overall impact of the project is to better individualize treatment strategies and more appropriately select for multimorbid and vulnerable complex older adults various interventions. Several scientific papers (involving FoP CUNI team) were already published from the I-CARE4OLD H2020 group, e.g. methodological paper, classification of tested non-pharmacological interventions , paper on the development of Cognitive Risk Score for predicting cognitive functions´ decline in older adults, and paper testing sensitivity of AI tools to identify potentially inappropriate prescribing .
Links to the project:
https://www.icare4old.eu/
https://cordis.europa.eu/project/id/965341
https://www.icare4old.eu/resources/scientific-papers
