Rationing of hip and knee replacement: effect on the severity of patient-reported symptoms and the demand for surgery in Otago.
Bibliographic record
Abstract
AIM: A key Government health target has been to increase access to elective surgery. Despite this, there is a growing concern about unmet demand and increasing numbers of patients are being declined elective surgery. This study aims to determine whether there has been an increase in the severity of osteoarthritis of the hip and knee in patients undergoing publicly-funded elective total joint replacement (TJR) and any increase in demand for TJR in Otago. METHOD: Demographic details and preoperative patient reported outcome scores (Oxford hip or knee score (OHS,OKS) and a reduced Western Ontario and McMaster Osteoarthritis Index (WOMAC) score (RWS) were collected prospectively in an historical cohort of patients undergoing total hip and knee replacement (THR, TKR) between 2006-2010. These were compared with all patients undergoing THR and TKR in the 12-month period commencing 1 November 2013, and all patients waitlisted during this period but returned to GP due to capacity issues. An estimate of current demand was made by adding all waitlisted public patients from the 12-month period to surgical numbers from private and those funded by ACC. RESULTS: In the 2006-2010 group of 613 patients, the mean OHS was 13.6 (SD 6.7) and OKS 15.4 (SD 6.5) and RWS 30.5 (SD 8.0). Three hundred and sixty-seven patients who underwent surgery in 2013/4 had significantly poorer scores (OHS 9.9 (SD 4.9), OKS 10.6 (SD 3.8), RWS 34.8 (SD 6.7)). The scores of 194 patients returned to GP in 2013/4 were the same as the historical surgical group (OHS13.0 (SD 6.2, OKS 15.2 (SD 5.9), RWS 30.8 (SD 8.4)). Six hundred and eight patients were wait-listed for public surgery and 356 joints were performed in private or under ACC in the 12-month period. The current intervention rate in Otago is 371/100,000 per year, while the demand has risen from 417/100000 in 2010-12 to 494/100,000 per year. In 2014, the shortfall was 241 joints per year. CONCLUSION: Patients undergoing primary elective total hip and knee replacement in Otago in 2014 are more severely disabled than between 2006-2010. Patients currently being returned to GP would have qualified for publicly funded surgery during that period. The demand for elective TJR in Otago has increased by 19% since 2012.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".