Pénuries de médicaments : 10 ans de recul au Canada
Bibliographic record
Abstract
Resume Objectif : Presenter un etat des lieux des penuries de medicaments dans les etablissements de sante du Quebec de 2006 a 2015. Description de la problematique : Il existe de nombreuses causes aux penuries de medicaments, et ce probleme fait intervenir differentes personnes. Afin de pallier aux penuries de medicaments, de nombreuses actions ont ete entreprises au cours des dernieres annees. Resolution de la problematique : A partir des donnees du site vendredipm.ca et de McKesson CanadaMD pour le groupe d’achat SigmaSante, nous avons comptabilise par periode de 12 mois (aout a juillet de l’annee suivante) les penuries de medicaments de 2006 a 2015. Notre analyse a trouve un nombre moyen de 630 medicaments en rupture de stock par annee. Le nombre moyen de fabricants concernes est de 57 par annee et la proportion moyenne de penuries provenant de fabricants de medicaments generiques est de 79 %. La proportion moyenne de penuries provenant de medicaments injectables est de 36 % (intervalle : 33 a 42 %) tandis que la duree moyenne des ruptures de stock, en hausse progressive, est de 135 jours. Conclusion : En moyenne, la penurie touchait 630 medicaments par an entre 2006 et 2015. La situation ne s’est pas amelioree au cours de la derniere decennie, et ce probleme est preoccupant, tant pour les cliniciens que pour les patients. La publication periodique d’un etat des penuries de medicaments est une source d’information pertinente qui devrait mobiliser les pharmaciens et autres parties prenantes. Abstract Objective: To provide an overview of drug shortages in Quebec’s health-care facilities from 2006 to 2015. Problem description: There are many causes of drug shortages and many players involved. Numerous measures have been taken in the past few years to address the problem. Problem resolution: Using data from the (no longer functional) website vendredipm.ca and from McKesson Canada for the purchasing group SigmaSante, we determined the profile of drug shortages from 2006 to 2015 per 12-month period. Based on the McKesson Canada/vendredipm.ca data from 2006 to 2015, the mean number of out-of-stock drugs was 630 per year. The average number of manufacturers involved was 57 per year, and the average proportion of shortages involving generic drug manufacturers was 79%. The average proportion of shortages involving injectables was 36% and the average stock-out duration, which had gradually increased, was 135 days. Conclusion: There was an average of 630 drugs in short supply per year from 2006 to 2015. The situation has not improved over the past decade. This problem is a cause for concern, both for clinicians and patients. A periodically published list of drug shortages is a useful source of information that should prompt pharmacists and other stakeholders to take action.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".