Billing Deprescribing Interventions: Portrait of an Initiative in Québec, Canada
Bibliographic record
Abstract
BACKGROUND: Deprescribing is a patient-centred process in which a healthcare professional reduces or stops medications to improve health outcomes. Since late 2022, community pharmacists in Québec, Canada, have been able to bill for deprescribing interventions, enabling more robust deprescribing research in large cohort studies. OBJECTIVE: This study aimed to assess the prevalence of deprescribing claims in Québec community pharmacies from January 1, 2023, to November 30, 2024, and to identify the most commonly deprescribed medication classes. METHODS: We analysed the total number of deprescribing claims submitted by pharmacists during this period and categorized deprescribed medications using the American Hospital Formulary Service classification. FINDINGS: Over 90 000 claims were submitted for deprescribing interventions, with most involving central nervous system medications. Although the number of claims increased over time, the overall volume remained modest. CONCLUSION: While limitations remain, such as the gradual adoption of billing interventions, Québec's reimbursement model for deprescribing interventions provides an important framework for research, offering a mechanism to study deprescribing in real-world settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".