Patient willingness to contribute to the cost of novel implants in total joint arthroplasty: the Canadian experience
Bibliographic record
Abstract
Background: In Canada, health care is covered by provincial health insurance programs; patients do not directly participate in paying for their acute care expenses. The aim of this study is to assess the willingness of Canadian patients to contribute to the costs of novel total joint arthroplasty implants. Methods: We administered a questionnaire to patients attending an outpatient arthroplasty clinic in Ontario. In the questionnaire, the longevity and risk of complications of a “standard” implant were described. We asked if participants would be willing to contribute to the cost of 3 novel implants that had differing longevities and risks of complications compared with the standard implant. Results: One hundred and fifteen patients completed our questionnaire. Up to 62% of patients were willing to contribute a copayment to get an implant with greater longevity. Willingness to pay decreased to 40% for an implant with greater longevity but an increased risk of complications. Forty percent of participants were willing to pay for an implant with the same longevity as the standard implant but a decreased risk of complications. Participants with a higher income were more willing than other participants to contribute to the cost of a novel implant with greater longevity or lower complication rates. Conclusion: This study demonstrated that up to 62% of our sample of patients in Ontario were willing to share the costs of a novel total joint replacement implant. Willingness to pay was associated with the proposed benefits of the implant and certain patient characteristics. Our study shows that a high proportion of Canadian patients may be willing to copay to have access to new technologies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".