Rehabilitation services following total joint replacement: a qualitative analysis of key processes and structures to decrease length of stay and increase surgical volumes in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was: (1) to identify key total joint replacement (TJR) care processes and structures from acute care and rehabilitation hospitals; (2) to determine the perceived implications of practice patterns and processes on wait times, discharge planning, transitions in care, utilization of rehabilitation services, and outcomes; and (3) to understand how acute care hospitals funded for additional cases were addressing current and future rehabilitation needs. METHODS: A qualitative descriptive approach using key informant interviews was used to provide further insights and depth of understanding to current practice patterns, structures and processes of care for TJR patients. RESULTS: Twenty-three key informants from a total of 15 hospitals across Ontario participated in this project. Themes that emerged related to processes of care (e.g. patient education, preoperative services, clinical pathways), and structures that supported these processes of care (e.g. organizational supports, increased funding and resources). The results point to a number of key practices that can facilitate smooth, integrated care for TJR patients, particularly in relation to best practices to decrease length of stay and increase surgical volumes. Increased funding related to strategic priorities placed on TJRs by the provincial government was viewed as an important impetus to implement a number of these key practices. CONCLUSION: From a rehabilitation perspective, there is need for consistent funding to secure more rehabilitation services for both preoperative and post-operative management of care that allows for shorter lengths of stay and to ensure optimal outcomes.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".