Differences in Drug Shortages in the US and Canada
Bibliographic record
Abstract
Importance: Drug shortages are a persistent public health issue that increased during the COVID-19 pandemic. Both the US and Canada follow similar regulatory standards and require reporting of drug-related supply chain issues that may result in shortages. However, it is unknown what proportion are associated with meaningful shortages (defined by a significant decrease in drug supply) and whether differences exist between Canada and the US. Objective: To compare how frequently reports of drug-related supply chain issues in the US vs Canada were associated with drug shortages. Design, Setting, and Participants: Longitudinal cross-sectional study conducted from January 2023 to March 2024 using drug-related reports of supply chain issues from 2017 to 2021 that were less than 180 days apart in Canada and the US. Shortages were assessed using data from the IQVIA Multinational Integrated Data Analysis database, comprising 89% of US and 100% of Canadian drug purchases. Exposure: Country (Canada vs US), timing of report issuance (before vs after the COVID-19 pandemic), and characteristics of the supply chain prior to the reports of drug-related supply chain issues (including World Health Organization essential medicine status, Health Canada tier 3 medicine [moderate risk classification], whether there was sole-source manufacturing of the drug, the formulation, the price per unit, ≥20 years since drug approval, and the number of therapeutic alternatives). Main Outcomes and Measures: A drug shortage (a decrease of ≥33% in monthly purchased standardized drug units) within 12 months, relative to the average units purchased during the 6 months prior to the report of supply chain issues to a US or Canadian reporting system. Results: Among the 104 drug-related reports of supply chain issues in both countries, 49.0% (95% CI, 39.3%-59.7%) were associated with drug shortages in the US vs 34.0% (95% CI, 25.0%-45.0%) in Canada (adjusted hazard ratio [HR], 0.53 [95% CI, 0.36-0.79]). The lower risk of drug shortages in Canada vs the US was consistent before the COVID-19 pandemic (adjusted HR, 0.47 [95% CI, 0.30-0.75]) and after the pandemic (adjusted HR, 0.31 [95% CI, 0.15-0.66]). After combining reports of supply chain issues in both countries, the shortage risk was double for sole-sourced drugs (adjusted HR, 2.58 [95% CI, 1.57-4.24]) and nearly half for Canadian tier 3 medicines (moderate risk) (adjusted HR, 0.56 [95% CI, 0.32-0.98]). Conclusions and Relevance: Drug-related reports of supply chain issues were 40% less likely to result in meaningful drug shortages in Canada compared with the US. These findings highlight the need for international cooperation between countries to curb the effects of drug shortages and improve resiliency of the supply chain for drugs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".