Examining “success” in post-hip fracture care transitions: A strengths-based approach
Bibliographic record
Abstract
Transitions between health care settings are a high-risk period for care quality and patient safety (Coleman, 2003; Picker Institute, 1999), particularly for older patients - such as those with hip fracture - who have complex needs and may undergo multiple care transitions. We sought to understand the key elements of "success" in care transition. Using a strengths-based perspective (Rapp, 1998; Saleebey, 2006), we focused on interprofessional health care providers' perspectives of what constitutes a "good" care transition for elderly hip fracture patients. As part of a larger ethnographic field study, semi-structured interviews were conducted with 17 health providers across a number of disciplines employed across the continuum of post-hip fracture management in British Columbia, Canada. We found two hallmarks of "success" in care transitions: a focus on process - information gathering and communication, and a focus on outcomes - autonomy and care pathways. Strategies for promoting and improving success, such as using practitioner-driven ground-up solutions to address challenges in care transitions, are highlighted.
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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 | 0.038 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".