United States physician communication on cost of cancer care under the affordable health care act
Bibliographic record
Abstract
Background: The aim of this study is to survey United States oncologists as healthcare system changes are implemented to reassess physician perceptions about the cost of cancer care and physicians’ perceived needs.Methods: From June through August of 2013, an electronic survey was sent to practicing oncologists across 50 states.Results: The electronic survey response rate was 15% (136 oncologists out of 899 total physicians) with respondents from 35 of the 50 states. Sixty percent of respondents thought that both out-of-pocket costs and healthcare system costs of cancer treatments were likely or extremely likely to have a larger effect on their decisions regarding which cancer treatments to recommend to patients in the future under the Affordable Care Act (ACA). A large majority of respondents felt that physician education was needed on the use of cost-effectiveness data and on communicating cost of therapies with patients, 91% and 85%, respectively.Conclusion: Respondents reported that their clinical treatment decisions are influenced by concerns over out-of-pocket patient costs, and that they want more cost and comparative effectiveness research as well as more education on how to communicate with patients about cost of therapy.
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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 | 0.006 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".