Determinants of willingness to pay for hip and knee joint replacement surgery for osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: To determine whether patients with osteoarthritis (OA) would be willing to pay for joint replacement and whether patient characteristics or health outcomes, including pain, physical function and health-related quality of life, were related to willingness to pay (WTP). METHODS: Patients who had undergone primary total hip replacement (THR) or total knee replacement (TKR) for OA completed a disease-specific questionnaire (Western Ontario and McMaster: WOMAC index), a generic measure of health status (Medical Outcome Study Short Form-36: SF-36) and an Evaluation Questionnaire to measure WTP and satisfaction with the replacement. RESULTS: Responses were obtained from 109 (77%) THR patients and 129 (72%) TKR patients. Mean age of respondents was 67 yr for THR (47% female) and 73 yr for TKR (60% female). Overall, 85% of patients responded to the WTP question. Of the THR patients, 71% were willing to pay something, 11% were not willing to pay anything and 18% did not answer the question. For TKR patients these figures were 70, 16 and 14% respectively. However, of those who responded to the WTP question, only 25% of the THR patients and 18% of the TKR patients indicated they would be willing to pay the actual current average cost of the operation in Australia (>/= A$15 000). A lower postoperative pain score (as measured by the WOMAC index) was a significant predictor of WTP for both THR and TKR patients. Income also significantly predicted WTP in THR patients but not in TKR patients. The other significant predictors for TKR patients were older age, having private health insurance and willingness to recommend joint replacement to others. CONCLUSIONS: Willingness to pay was a measure that was understandable and acceptable to patients, most of whom were willing to pay something. There was a high correlation between WTP, good health outcomes and patient satisfaction, pain relief being the dominant determinant.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".