OP40 Effect Of Advanced Nursing Practice On Hospital Use For The Elderly
Bibliographic record
Abstract
Introduction: Within the local context in Montréal, the elderly population makes up more than 50% of patient hours in emergency department. To meet ministerial targets for length of stay, our health technology assessment unit was requested to conduct an umbrella review to evaluate interventions aimed at reducing health care services use for this population. Within that context, our unit was asked to further evaluate the efficacy of advance practice nurse (APN)-led interventions. The objective of this rapid response was to summarize the scientific literature for APN-led interventions on hospital services use. Methods: An umbrella review using the PRISMA statement was conducted to review the scientific literature. Systematic searches were conducted in five databases, along with a grey literature search. Two reviewers performed the study selection, quality assessment using the ROBIS, and data extraction. The primary studies within the selected systematic reviews were extracted by two reviewers and a meta-analysis was conducted to analyze the efficacy of APN-involved in discharge planning and transitional care. Results: From the twenty-seven systematic reviews identified in the literature search, four reported data on APN-led interventions. In all, sixteen primary studies were included in the four systematic reviews. While most studies focused on transitional care, there was heterogeneity in the components of the interventions implemented. At six months post-discharge, a reduction of forty-one percent in relative risk of readmission was observed with APN-led discharge planning and transitional care with patient education, follow-up and services coordination. Studies with fewer components reported less significant results than studies with comprehensive discharge planning and transitional care. The few APN-led primary care studies identified in the systematic reviews reported inconsistent results. Conclusions: APN-led comprehensive discharge planning and transitional care can reduce hospital readmission rate. Several components were identified and should be considered in the discharge planning and transitional care.
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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 | 0.018 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".