Determinants of patient and surgeon perspectives on maximum acceptable waiting times for hip and knee arthroplasty
Bibliographic record
Abstract
OBJECTIVES: Lengthy waiting times for hip and knee arthroplasty have raised concerns about equitable and timely access to care. The Western Canada Waiting List project has developed priority criteria scores linked to maximum acceptable waiting times (MAWT) for different levels of priority. Our study purpose was to assess the determinants of patient- and surgeon-rated MAWT, and to test whether the anticipated waiting time has an independent influence after adjusting for age, sex and patient urgency. A second aim was to compare MAWT, waiting time and anticipated waiting time for different levels of urgency assessed using the priority criteria score. METHODS: Orthopaedic surgeons assessed 233 consecutive patients waiting for arthroplasty in terms of their urgency (assessed using the priority criteria score and a visual analogue scale), MAWT and anticipated waiting time. Patient data included urgency (assessed by a visual analogue scale), MAWT and the Western Ontario McMaster Osteoarthritis index. We used hierarchical linear regression to test the models. RESULTS: After adjusting for age and sex, urgency (assessed by priority criteria score and visual analogue scale) and anticipated waiting time accounted for 40% of the variance in surgeon MAWT. The patient model accounted for 30% of the variance in patient MAWT. Older patients preferred signficantly shorter MAWTs (P <0.05). Anticipated waiting time added significantly to both the surgeon and patient MAWT models (R(2) change 0.11 and 0.07, respectively). Actual waiting time was weakly correlated with urgency assessed using the priority criteria score (r = -0.25, P <0.0001). CONCLUSIONS: Patients' and surgeons' views are critical to a fair process of establishing MAWT for elective procedures. Anticipated waiting time may influence the perspectives on MAWT and must be considered in their interpretation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".