Increased Use of Antidepressants in Canada: 1981–2000
Bibliographic record
Abstract
OBJECTIVE: To provide a descriptive analysis of Canadian utilization (prescriptions, cost, cost per prescription) of antidepressants (ATC-code: N06A). METHODS: IMS Canada provided prescription volumes and costs from 1981 to 2000. We analyzed time trends for antidepressants in general and 4 subclasses (tricyclic antidepressants [TCAs], selective serotonin-reuptake inhibitors [SSRIs], dual action antidepressants [DAAs], and monoamine oxidase inhibitors [MAOIs]). Costs were discounted using the consumer price index, adjusting for population growth using data from Statistics Canada. RESULTS: Between 1981 and 2000, total prescriptions increased from 3.2 to 14.5 million. Market share of TCAs (23.7%) and MAOIs (2.1%) remained constant, despite the introduction of the first SSRI, fluoxetine, in 1989. SSRI prescriptions increased to 6.7 million (market share 46.3%). DAA use increased gradually after 1994 to 3.5 million prescriptions (23.9% market share) in 2000. The number of prescriptions expanded (possibly due to SSRIs) by 238%, with an increased cost of 2.7 billion dollars. Total expenditures for antidepressants increased exponentially, from 31.4 million dollars in 1981 to 543.4 million dollars in 2000 (y = 4E - 130e(0.1556x) [R(2) = 0.99]). Cost per prescription increased linearly from 9.85 dollars in 1981 to 37.44 dollars in 2000 (y = 1.72x + 7.92 [R(2) = 0.96]). CONCLUSIONS: Utilization and costs of pharmacotherapy for depression have increased above the inflation rate and are expected to exceed 1.2 billion dollars (50 dollars per prescription) in 2005. Increased costs may be due to increased availability of new products with increased safety, efficacy, and acquisition cost; increased number of users; and increasing costs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".