Prescription Drug Coverage of Guideline-Directed Medical Therapy for People Living with Heart Failure with Reduced Ejection Fraction in Canada
Bibliographic record
Abstract
Background: Guideline-directed medical therapy (GDMT) for heart failure (HF) is cost-effective and is associated with significant reductions in morbidity and mortality. Yet, GDMT remains under-prescribed. The Canadian Cardiovascular Society's HF Working Group assessed formulary access to GDMT across Canada to identify differences in reimbursement and review how coverage aligns with evidence-based guidelines. Methods: An environmental scan was conducted for the period from June 2022 to July 2024 on the formulary coverage of angiotensin receptor-neprilysin inhibitors, beta-blockers, sodium-glucose cotransporter-2 inhibitors, mineralocorticoid receptor antagonists, and sinus node inhibitors in 10 Canadian provinces, 2 territories, and 6 federal programs. Results: In all provincial and territorial plans, patient eligibility and prior medication use criteria are required for sacubitril-valsartan reimbursement. Sacubitril-valsartan has coverage restrictions based on natriuretic peptides and prescriber qualifications, except in Ontario and Quebec. Carvedilol coverage is not a benefit in Ontario or British Columbia. Bisoprolol and spironolactone have universal coverage. Eplerenone is not listed in British Columbia. Dapagliflozin coverage is a benefit in all plans except Quebec. Ivabradine coverage has patient eligibility and prior medication use criteria in all provinces and territories and prescriber restrictions in certain regions. Two federal plans have universal coverage of GDMT. Conclusions: Differences in criteria for drug reimbursement create provincial and territorial variation in access to GDMT in Canada. Coverage criteria include prior medication use and prescriber qualifications, which are not supported by evidence-based guidelines. Systemwide changes in the funding of drug reimbursement programs are needed to improve access to GDMT for the more than 750,000 people living with HF in Canada.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".