Survey Results Show That Adults Are Willing To Pay Higher Insurance Premiums For Generous Coverage Of Specialty Drugs
Bibliographic record
Abstract
Generous coverage of specialty drugs for cancer and other diseases may be valuable not only for sick patients currently using these drugs, but also for healthy people who recognize the potential need for them in the future. This study estimated how healthy people value insurance coverage of specialty drugs, defined as high-cost drugs that treat cancer and other serious health conditions like multiple sclerosis, by quantifying willingness to pay via a survey. US adults were estimated to be willing to pay an extra $12.94 on average in insurance premiums per month for generous specialty-drug coverage--in effect, $2.58 for every dollar in out-of-pocket costs that they would expect to pay with a less generous insurance plan. Given the value that people assign to generous coverage of specialty drugs, having high cost sharing on these drugs seemingly runs contrary to what people value in their health insurance.
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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 | 0.025 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".