The Effect of Physician Disclosure of Financial Incentives on Trust
Bibliographic record
Abstract
BACKGROUND: Many physicians receive financial incentives to limit their ordering of expensive tests and procedures. While Medicare mandates disclosure of incentives, it is not clear how to inform patients without undermining trust. METHODS: Our objective was to determine public opinion about physician disclosure of financial incentives and how this might be best communicated to patients. The 2002 General Social Survey included 2765 interviews from a probability sample of English-speaking US households. The interview included questions about financial incentives and an audiotaped scenario of a physician discussing the impact of financial incentives on ordering a magnetic resonance image. Respondents heard 1 of 6 randomly selected disclosure strategies. The measurements included ratings of trust, satisfaction, agreement with the physician's decision, and likelihood of remaining with the physician/health plan or seeking a second opinion. RESULTS: Nearly half (48.8%) of respondents had previously heard of financial incentives to limit test ordering. Of the respondents, 94.8% wanted to be told about incentives, at the time of enrollment in a health plan (80.5%), by a health plan representative (44.8%), their physician (17.1%), or both (38.1%). Of the 6 different disclosure strategies, "addressing emotions" and "negotiation" were associated with the best outcomes, while "common enemy" and "denying influences" were most negatively perceived. Black and Hispanic subjects were less likely to express satisfaction or trust and more likely to disenroll or seek a second opinion. CONCLUSIONS: The public wants information about physician financial incentives. Specific communication styles enhance how this information is conveyed to patients, increasing trust and supporting the physician-patient relationship.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".