Prescribing Trends for Bipolar Disorder Drugs in Alberta, Canada Between 2008 and 2021: Tendances en matière de prescription de médicaments pour le trouble bipolaire en Alberta, au Canada, entre 2008 et 2021
Bibliographic record
Abstract
AimsThe approval of new drugs for bipolar disorder (BD) may have caused a shift in prescribing trends among patients with BD. The objective of the study was to describe prescribing trends amongst individuals with BD in Alberta, Canada.MethodsThis study used provincial administrative health data from Alberta, Canada. Individuals with at least one ICD-9 or ICD-10 code for BD were identified from three databases - Provider claims, Hospital Discharge Abstract Database and the Ambulatory Care Classification System. Within this cohort, we identified prevalent, new and combination use of commonly prescribed BD drugs through prescription information from the Pharmaceutical Information Network database.ResultsBetween April 1, 1994, and March 31, 2021, 136,628 individuals had at least 1 code of BD with 9,466,407 prescriptions dispensed between January 1, 2008 to March 31, 2021. New users of all drugs declined over time, especially from 2019 to 2021. Among all BD drugs, antidepressants were the most commonly prescribed in both prevalent and new users throughout the study period. Among recommended treatments for BD, quetiapine was one of the most prescribed drugs amongst prevalent users. An overall decline was noted in prescribing of lithium, divalproex and carbamazepine among prevalent and new users. Most individuals were prescribed a single drug for BD treatment. The most common combination therapy for prevalent users was an antidepressant with a second-generation antipsychotic (SGA).ConclusionsOverall, we uncovered a concerning trend in the prescribing patterns for BD treatment, with antidepressants and SGAs being prescribed frequently and a decline in prescribing of lithium and other mood stabilizers. This study emphasizes the need for initiatives promoting evidence-based guidelines and better alignment with best practices for managing BD in outpatient settings.Plain Language Summary TitlePrescribing Trends for Bipolar Disorder Drugs in Alberta, Canada Between 2008 to 2021.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".