Focused Jurisdictional Scan of Glomerulonephritis Medication Access in Canada: A Program Report
Bibliographic record
Abstract
Purpose of Program: Glomerulonephritis (GN) is a group of rare kidney diseases that is increasingly being managed with higher cost immunosuppressive (IS) agents in Canada. Ontario Health's Ontario Renal Network (ORN) oversees the management and delivery of GN services in the province. Stakeholder surveys previously conducted by ORN identified that both clinicians and patients do not perceive access to GN medications as comprehensive or timely. The program conducted a focused jurisdictional scan among 7 provinces to inform ORN initiatives to improve access to GN medications. Specifically, the program examined clinician experience with GN access, public drug coverage criteria, and timelines for public coverage for select IS agents (ie, tacrolimus, cyclosporine, mycophenolate mofetil [MMF], mycophenolate sodium, rituximab, and eculizumab) used to manage GN in adults who live in Canada. Methods: For the selected IS agents, a focused jurisdictional scan on medication access was conducted by ORN in 2018 and updated in July 2022. Information was obtained by searching the gray literature and/or credible online sources for public funding policies and eligibility criteria. Findings were supplemented by personal communications with provincial drug programs and consulting GN clinical experts from 7 provinces (ie, Alberta, British Columbia, Saskatchewan, Manitoba, Ontario, Nova Scotia, and Quebec). Key Findings: Clinicians from different provinces prescribe IS agents similarly for GN indications, despite distinctions in public drug funding policies. While patients can obtain public funding for many IS agents, for GN, most provinces rely on case-by-case review processes. In addition, provinces can vary in their funding criteria and which IS agents are listed on the public formulary. For IS agents that require prior authorization or case-by-case review, timelines vary by province with decisions taking a few days to weeks. British Columbia, with a GN-specific drug formulary, had the most integrated and efficient system for patients and prescribers. Limitations: This scan primarily relied on publicly available information for drug coverage criteria and clinician experience with access in their province. Since this scan was conducted, public drug coverage criteria and/or application processes may have changed. Implications: While patients in most provinces have similar needs and nephrologists similar prescribing patterns, gaps still exist for publicly funded GN medications. Interprovincial differences in the drugs funded, funding criteria, and application process may affect timely and equitable access to GN medications across Canada. Given the rarity of GN, a pan-Canadian funding approach may be warranted to improve the current state.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.013 | 0.024 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".