Untangling the inter-relatedness within integrated care programmes for community-dwelling frail older people: a rapid realist review
Bibliographic record
Abstract
OBJECTIVE: To identify the relationships between the context in which integrated care programmes (ICPs) for community-dwelling frail older people are applied, the mechanisms by which the programmes do (not) work and the outcomes resulting from this interaction by establishing a programme theory. DESIGN: Rapid realist review. INCLUSION CRITERIA: Reviews and meta-analyses (January 2013-January 2019) and non-peer-reviewed literature (January 2013-December 2019) reporting on integrated care for community-dwelling frail older people (≥60 years). ANALYSIS: Selection and appraisal of documents was based on relevance and rigour according to the Realist And Meta-narrative Evidence Syntheses: Evolving Standards criteria. Data on context, mechanisms, programme activities and outcomes were extracted. Factors were categorised into the five strategies of the WHO framework of integrated people-centred health services (IPCHS). RESULTS: 27 papers were included. The following programme theory was developed: it is essential to establish multidisciplinary teams of competent healthcare providers (HCPs) providing person-centred care, closely working together and communicating effectively with other stakeholders. Older people and informal caregivers should be involved in the care process. Financial support, efficient use of information technology and organisational alignment are also essential. ICPs demonstrate positive effects on the functionality of older people, satisfaction of older people, informal caregivers and HCPs, and a delayed placement in a nursing home. Heterogeneous effects were found for hospital-related outcomes, quality of life, healthcare costs and use of healthcare services. The two most prevalent WHO-IPCHS strategies as part of ICPs are 'creating an enabling environment', followed by 'strengthening governance and accountability'. CONCLUSION: Currently, most ICPs do not address all WHO-IPCHS strategies. In order to optimise ICPs for frail older people the interaction between context items, mechanisms, programme activities and the outcomes should be taken into account from different perspectives (system, organisation, service delivery, HCP and patient).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.069 | 0.243 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".