Comparison of Drug Benefits Provided by Veterans Affairs Canada and the Canadian Forces Health Services Group
Bibliographic record
Abstract
BACKGROUND: Drug benefits are provided at public expense to all actively serving Canadian Armed Forces (CAF) personnel, with ongoing drug coverage offered by Veterans Affairs Canada (VAC) for selected conditions following termination of employment. Differences in drug coverage between these programs could introduce risks for treatment disruption. OBJECTIVES: Work was undertaken to establish a process that would allow systematic comparison of the entire VAC and CAF formularies, and to identify and explain discordant listings in 14 therapeutic categories that pose risk of adverse outcomes with sudden treatment interruption. METHODS: Lists of medications were created for each program, including regular benefit and restricted use drugs, using files obtained from the claims processor in January 2015. Products were coded using the Anatomic-Therapeutic-Chemical (ATC) system. Degree of alignment within therapeutic categories was assessed based on the percentage of fifth-level ATCs that were covered in common. Discordantly listed drugs in 14 categories of concern were reviewed to identify similarities in product characteristics. RESULTS: A total of 1124 medications were identified in 80 therapeutic categories. Coverage of medications was identical in 11 categories, and overall, almost three-quarters of identified drugs (73.4%, n = 825) were covered in common by both plans. Many discordant listings reflected known differences in the programs' operating procedures. A number of discrepancies were also identified in newer therapeutic categories. CONCLUSIONS: There is significant overlap in the medications covered by the CAF and VAC drug benefit programs. Application of the ATC coding system allowed for discrepancies to be readily identified across the entire formulary, and in specific therapeutic categories of concern.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".