ArticleBMJ open2023
Optimising the care for older persons with complex chronic conditions in home care and nursing homes: design and protocol of I-CARE4OLD, an observational study using real-world data.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Uptake of Clinical Decision Support Systems Among Health Care Professionals in Six European Countries and the United States: Cross-Sectional Survey Within the I-CARE4OLD Project.Journal of medical Internet research · 2026Article
- Personalized Digital Care Program Allocation for Older Adults: Reinforcement Learning-Based Simulation Study.JMIR aging · 2026Article
- The Impact of Healthcare Professionals' Characteristics on the Evaluation of Clinical Decision Support Systems: Insights from a Cross-Country Usability and Technology Acceptance Study of the iCARE Tool.Journal of medical systems · 2026Article
- Clinical and environmental factors, functional status, and multimorbidity-stratifying progression and prognosis of multimorbidity, frailty, and disability: the Age-It Research Program.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- ESCP best practice: development of the national methodology for the provision of clinical-pharmaceutical care and its implementation in the healthcare system of the Czech Republic.International journal of clinical pharmacy · 2025Article
- Effect of discontinuing antipsychotic medications on the risk of hospitalization in long-term care: a machine learning-based analysis.BMC medicine · 2025Article
- Navigating artificial intelligence in home healthcare: challenges and opportunities in nursing wound care.BMC nursing · 2025Article
- Article
Corrections and comments
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Authors and funding
21 authors at 12 institutions in 10 countries.
Funding
Abstract
introductionIn ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home care and nursing homes, where most older persons with CCCs receive care, professionals often lack appropriate decision support suitable and sufficient to address the medical and functional complexity of persons with CCCs. This EU-funded project aims to develop decision support systems using high-quality, internationally standardised, routine care data to support better prognostication of health trajectories and treatment impact among older persons with CCCs. METHODS AND ANALYSIS: Real-world data from older persons aged ≥60 years in home care and nursing homes, based on routinely performed comprehensive geriatric assessments using interRAI systems collected in the past 20 years, will be linked with administrative repositories on mortality and care use. These include potentially up to 51 million care recipients from eight countries: Italy, the Netherlands, Finland, Belgium, Canada, USA, Hong Kong and New Zealand. Prognostic algorithms will be developed and validated to better predict various health outcomes. In addition, the modifying impact of pharmacological and non-pharmacological interventions will be examined. A variety of analytical methods will be used, including techniques from the field of artificial intelligence such as machine learning. Based on the results, decision support tools will be developed and pilot tested among health professionals working in home care and nursing homes. ETHICS AND DISSEMINATION: The study was approved by authorised medical ethical committees in each of the participating countries, and will comply with both local and EU legislation. Study findings will be shared with relevant stakeholders, including publications in peer-reviewed journals and presentations at national and international meetings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.