Anticipatory Care Planning Intervention for Older Adults at Risk of Functional Decline: Study protocol for a Primary Care Cluster Feasibility Randomised Trial
Bibliographic record
Abstract
Abstract Background The treatment and management of long-term health conditions is the greatest challenge facing health systems around the world today. Innovative approaches to patient care in the community such as Anticipatory Care Planning (ACP), which seek to help with the provision of high-quality comprehensive care to older adults at risk of functional decline, require evaluation. This study will evaluate one approach that will include primary care as the setting for Anticipatory Care Planning.Methods This study will help to determine the feasibility for a definitive randomised trial to evaluate the implementation and outcomes of an ACP intervention. The intervention will be delivered by specially trained registered nurses in a primary care setting with older adults identified as at risk of functional decline. The intervention will comprise of: a) information collection via patient assessment; b) facilitated informed dialogue between the patient, family carer, general practitioner and other healthcare practitioners; and, c) documentation of the agreed support plan and follow-up review dates. Through a structured consultation with patients and their family carers, the nurses will complete a mutually agreed personalized support plan.Discussion This study will determine the feasibility for a full trial protocol to evaluate the implementation and outcomes of an (ACP) intervention in primary care to assist older adults aged 70 years of age or older and assessed as at risk of functional decline. The study will be implemented in two jurisdictions on the island of Ireland which employ different health systems but which face similar health challenges. This study will allow us to examine important issues, such as the impact of two different healthcare systems on the health of older people and the influence of different legislative interpretations on undertaking cross jurisdictional research in Ireland.
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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 | 0.040 | 0.035 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.069 | 0.013 |
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".