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Completed H2020 European Commission

Individualized CARE for Older Persons with Complex Chronic Conditions at home and in nursing homes

€6.49M EUR

Funder European Commission
Recipient Organization Stichting Amsterdam Umc
Country Netherlands
Start Date Jun 01, 2021
End Date May 31, 2025
Duration 1,460 days
Number of Grantees 15
Roles Participant; Coordinator; Principal Investigator
Data Source European Commission
Grant ID 965341
Grant Description

BACKGROUNDOptimal care for older patients with complex chronic conditions (CCC) is challenging.

Not only do older patients with CCC present with multiple conditions and functional impairments, these often interact with each other, as well as with their treatments. Patients with CCC are concentrated in home care and nursing home settings.

Professionals working in these settings often lack appropriate decision support that mirrors the medical and functional complexity of these persons.

AIMTo improve prognoses and estimation of treatment impact for older care recipients with CCC in home care and nursing homes settings, and develop, validate, and test next generation individualised decision support.IMPACT Better informed decision making for clinical management of older care recipients with CCC in home care and nursing homes, through (1) high quality internationally validated predictive algorithms on disease trajectories and treatment outcomes; (2) a multi-nationally tested e-platform for health professionals to receive predictive scenarios on course and treatment outcomes of newly assessed care recipients at point of care; and (3) dissemination among health professionals working in nursing homes and home care.APPROACHWe collated longitudinal data from 52 million older recipients of home care and nursing home care from eight countries including (1) highly reliable, valid and harmonised comprehensive assessments of functional capacities, diseases, and treatments, linked with (2) administrative repositories on mortality and care use.

We develop and validate decision support algorithms using a variety of techniques including machine learning to better predict (i) outcomes (eg death, acute admissions, quality of life) and the modifying impact of (ii) pharmacological and (iii) non-pharmacological treatments.

We co-create decision support output with health professionals and patients and pilot it's applicability at point of care with an e-platform.

All Grantees

University of Waterloo; Stichting Vu; Hebrew Rehabilitation Center; Istituto Superiore Di Sanita; Nhg Finland Oy; Profility (Israel) Ltd; Terveyden Ja Hyvinvoinnin Laitos; European Union Geriatric Medicine Society Aisbl; Stichting Amsterdam Umc; Karolinska Institutet; Univerzita Karlova; Katholieke Universiteit Leuven; Universita Cattolica Del Sacro Cuore; Uniwersytet Jagiellonski; University of Illinois At Urbana-Champaign

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