Reimbursement for Supportive Cancer Medications Through Private Insurance in Saskatchewan
Bibliographic record
Abstract
Background: As demand for cancer treatment grows, and newer, more expensive drugs become available, public payers in Canada are finding it increasingly difficult to fund the full range of available cancer drugs.Objective: To determine the extent of private drug coverage for supportive cancer treatments in Saskatchewan, preparatory to exploring the potential for cost-sharing. Methods: Patients who presented for chemotherapy and who provided informed consent for participation were surveyed regarding their access to private insurance. Insurers were contacted to verify patients’ level of coverage for supportive cancer medications. Groups with specified types of insurance were compared statistically in terms of age, income bracket, time required to assess insurance status, and amount of deductible. Logistic regression was used to determine the effect of patients’ age and income on the probability of having insurance.Results: Of 169 patients approached to participate, 156 provided consent and completed the survey. Their mean age was 58.5 years. About two-fifths of all patients (64 or 41%) were in the lowest income bracket (up to $30 000). Sixty-three (40%) of the patients had private insurance for drugs, and 36 (57%) of these plans included reimbursement for supportive cancer medications. A deductible was in effect in 31 (49%) of the plans, a copayment in 28 (44%), and a maximum payment in 8 (13%). Income over $50 000 was a significant predictor of access to drug insurance (p = 0.003), but age was not significantly related to insurance status. Conclusions: A substantial proportion of cancer patients in this study had access to private insurance for supportive cancer drugs for which reimbursement is currently provided by the Saskatchewan Cancer Agency. Cost-sharing and optimal utilization of the multipayer environment might offer a greater opportunity for public payers to cover future innovative and supportive therapies for cancer, but further study is required to determine whether a cost-sharing program would be cost-effective and in the best interest of patients.RÉSUMÉ Contexte : Avec la demande croissante pour les traitements anticancéreux, et l’arrivée de nouveaux médicaments plus coûteux, les payeurs publics canadiens ont de plus en plus de difficultés à rembourser toute la gamme de médicaments anticancéreux maintenant offerts.Objectif : Déterminer dans quelle proportion les médicaments adjuvants des anticancéreux sont remboursés par les régimes privés d’assurance médicaments en Saskatchewan, avant d’évaluer la possibilité du partage des coûts.Méthodes : Les patients qui se sont présentés à une séance de chimiothérapie et qui ont donné leur consentement éclairé à participer au sondage ont répondu à un questionnaire sur leur couverture d’assurance médicaments privée. Un suivi auprès des assureurs de chaque patient a permis de vérifier la couverture offerte pour les médicaments adjuvants des anticancéreux. Les groupes de patients ayant chacun un type défini d’assurance ont été comparés pour ce qui est des critères suivants : âge, tranche de revenu, délai d’évaluation de la couverture d’assurance et montant de la franchise. Un modèle de régression logistique a servi à déterminer l’effet de l’âge et du revenu des patients sur la probabilité d’avoir une assurance.Résultats : Des 169 patients sollicités pour participer au sondage, 156 ont donné leur consentement et répondu au sondage. L’âge moyen était de 58,5 ans. Environ deux cinquièmes des patients (64 ou 41 %) se situaient dans la tranche de revenu le plus faible (jusqu’à 30 000 $). Soixante-trois (40 %) des patients détenaient une assurance médicaments privée, et 36 (57 %) de ces assurances remboursaient les médicaments adjuvants des anticancéreux. Les franchises étaient en vigueur pour 31 (49 %) des assurances, les coassurances pour 28 (44 %) et les remboursements maximums pour 8 (13 %). Un revenu supérieur à 50 000 $ était un facteur prédictif significatif d’accès à une assurance médicaments (p = 0,003), mais pas l’âge.Conclusions : Une proportion considérable de patients atteints de cancer dans cette étude avaient accès à un régime privé d’assurance couvrant les médicaments adjuvants des anticancéreux qui étaient actuellement remboursés par la Saskatchewan Cancer Agency. Le partage des coûts et l’utilisation optimale du contexte de payeurs multiples permettraient aux payeurs de rembourser publics de futurs traitements novateurs et adjuvants du cancer, mais d’autres études sont nécessaires pour déterminer si un programme de partage des coûts serait rentable et dans le meilleur intérêt des patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".