Patients’ Views on Surgeons’ Financial Conflicts of Interest
Bibliographic record
Abstract
BACKGROUND: The U.S. Department of Justice's investigations into financial relationships between surgical device manufacturers and orthopaedic surgeons have raised the question as to whether surgeons can continue to collaborate with industry and maintain public trust. We explored postoperative patients' views on financial relationships between surgeons and surgical device manufacturers, their views on disclosure as a method to manage these relationships, and their opinions on oversight. METHODS: From November 2010 to March 2011, we surveyed 251 postoperative patients in the U.S. (an 88% response rate) and 252 postoperative patients in Canada (a 92% response rate) in follow-up hip and knee arthroplasty clinics with use of self-administered questionnaires. Patients were eligible to complete the questionnaire if their surgery (primary or revision hip or knee arthroplasty) had occurred at least three months earlier. RESULTS: Few patients are worried about possible financial relationships between their surgeon and industry (6% of surveyed patients in the U.S. and 6% of surveyed patients in Canada). Most patients thought that it is appropriate for surgeons to receive payments from manufacturers for activities that can benefit patients, such as royalties for inventions (U.S., 69%; Canada, 66%) and consultancy (U.S., 48%; Canada, 53%). Most patients felt that it is not appropriate for their surgeon to receive gifts from industry (U.S., 63%; Canada, 59%). A majority felt that their surgeon would hold patients' interests paramount, regardless of any financial relationship with a manufacturer (U.S., 76%; Canada, 74%). A majority of patients wanted their surgeon's professional organization to ensure that financial relationships are appropriate (U.S., 83%; Canada, 83%); a minority endorsed government oversight of these relationships (U.S., 26%; Canada, 35%). CONCLUSIONS: Most patients are not worried about possible financial relationships between their surgeon and industry. They clearly distinguish financial relationships that benefit current or future patients from those that benefit the surgeon or device manufacturer. They favor disclosure with professional oversight as a method of managing financial relationships between surgeons and manufacturers.
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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 | 0.019 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".