A dog's breakfast: prescription drug coverage varies widely across Canada

Med Care. 2001 Apr;39(4):315-26. doi: 10.1097/00005650-200104000-00003.


Background: Each province in Canada independently assesses drugs for their reimbursement eligibility. Publicly funded access to specific drugs is therefore dependent on province of residence.

Objective: Evaluate the variability of access and its determinants for publicly available prescription drugs across Canada, and discuss the feasibility of implementing a national plan.

Methods: For a sample of 58 drugs receiving Health Protection Branch approval in Canada between 01/01/1996 and 12/31/1997, all provinces were surveyed about their formulary inclusion/exclusion decision. Kappa values were estimated to measure concordance between provincial coverage decisions. Logistic analysis using Generalized Estimating Equations was used to assess the impact of key features of provincial plans on the decision.

Results: Among the 58 drugs, 5 (9%) were included in all 10 and 14 (24%) by at least 8 provincial formularies. None were excluded by all the provinces. Concordance rates among provinces were low (overall kappa-like statistic = 0.20 and range of pairwise kappa = -0.11 to 0.64). Logistic regression showed that therapeutic category, price ratio to comparator, the integration of public with private coverage, and the existence of ability-to-pay criteria were significant determinants of the inclusion decision.

Conclusions: Findings show that public access to the same prescription medications differs widely across provinces. If Canada were to adopt a "National" plan without disrupting current individual prescriptions, all currently funded drugs in each province would have to be "grandfathered" and included in the new National formulary. Such an all-inclusive list would also make such a plan unaffordable.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Canada
  • Formularies as Topic
  • Health Services Accessibility
  • Humans
  • Insurance Coverage / statistics & numerical data*
  • Insurance, Pharmaceutical Services / statistics & numerical data*
  • Logistic Models