Identifying practices of information transfer between the hospital and primary care for older adults: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Transition of care from hospital to primary care has been recognised globally as a high-risk scenario for older patients' safety by the WHO. Indeed, sub-optimal care transitions are associated with increased mortality, morbidity and adverse events.Improving communication through timely and accurate clinical information transfer has been identified as a key component of optimal care transitions. However, timely and accurate clinical information transfer from hospital to primary care varies across countries and institutions. Information transfer practices are heterogeneous, in some places depending on individual initiative and sometimes not occurring at all.To improve current practices, we will conduct a scoping review to identify the current and suggested practices of information transfer between hospital-based physicians or pharmacists and the primary care team of older patients. METHODS AND ANALYSIS: and the JBI Manual for Evidence Synthesis, and the findings reported according to the PRISMA extension for Scoping Reviews. We will use a search strategy developed with a specialised librarian to search four databases (MEDLINE, Embase, CINAHL and AgeLine) and reference lists of selected studies. All studies adhering to our iteratively created eligibility criteria outlined by the population, concept and context elements will be included. The data extraction table will also be constructed iteratively with the research team, and results will be presented tabularly and qualitatively. ETHICS AND DISSEMINATION: Ethics approval was obtained. We plan to disseminate the results as scientific communication (peer-reviewed journal and presentations) and during a deliberative dialogue workshop with key stakeholders in order to generate recommendations to improve current practices in our own clinical setting, potentially to be adapted and scaled up with our collaborators provincially, nationally and internationally.This protocol has been registered on the Open Science Framework: https://osf.io/eg958.
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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 | 0.162 | 0.119 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 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".