Patient out-of-pocket and insurer payment decisions for bevacizumab for metastatic colorectal cancer: A Canadian analysis
Bibliographic record
Abstract
6576 Background: Like many health care services in Canada, intravenous (IV) cancer therapies are typically funded publicly through hospitals and provincial cancer agencies. Delays may be encountered between regulatory approval and public funding of new drugs. IV drugs are not routinely covered through private insurance (PRI) plans, requiring patients to appeal for special consideration, including employer exceptions or pay cash. Uncertainty of drug funding may create challenges for physicians and patients when discussing treatment options. The Roche Patient Assistance Program (RPAP) provides reimbursement navigation, copay/financial assistance and access to infusion clinics. This observational study examines patient access to bevacizumab (B) in the absence of public funding. Methods: An analysis of the RPAP database for the period of July 2006 to August 2008 was conducted assessing patients enrolled, insurance status, approval rates, and access to B. Receipt of treatment with B was evaluated according to insurance coverage. Results: A total of 877 patients accessed the RPAP for treatment with B. 647 (74%) had PRI and 230 (26%) were uninsured. Of PRI patients, 310 (48%) were approved coverage and 337 (52%) were denied. 204 patients (65%) with approved PRI coverage received B therapy. Of patients with PRI but denied coverage for B, 135 (40%) elected to pay for B. Of patients with no PRI, 120 (52%) paid for B. Of all patients with no coverage for B (no PRI or denied PRI), 255 patients (45%) elected to pay for B. Conclusions: In a public healthcare environment, when B was not publicly funded, approximately half of patients without any PRI coverage who accessed the RPAP were willing to pay for B. Although private insurers state IV drugs are not plan benefits, almost half of patients were able to obtain B coverage. A conventional analysis of willingness-to-pay should be conducted to better understand reasons behind patient and private insurer decisions observed in this study. Further research should also be conducted to determine whether results can be generalized to other unfunded anticancer agents within the Canadian health care system. [Table: see text]
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".