Project description
New e-tool to help healthcare professionals treat elderly with complex chronic conditions
Older patients with complex chronic conditions are mainly in home care and nursing home settings. Many times, healthcare professionals in these settings lack appropriate decision support. In this context, the EU-funded I-CARE4OLD project will develop and test next-generation decision support using high-quality internationally standardised routine care data based on a comprehensive assessment e-platform tool, InterRAI. Specifically, the project’s multidisciplinary international consortium has collated longitudinal data from 52 million older recipients of home care and nursing home care from 8 countries including reliable, valid and harmonised comprehensive assessments of functional capacities, diseases and treatments. The focus was on predicting outcomes and the impact of treatments.
Objective
BACKGROUND
Optimal 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.
AIM
To 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.
APPROACH
We 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.
Fields of science
Not validated
Not validated
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
1081 HV Amsterdam
Netherlands