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Record W2117404492 · doi:10.4212/cjhp.v65i2.1123

Drug Shortages in Health Care Institutions: Perspectives in Early 2012

2012· article· en· W2117404492 on OpenAlexaffvenueabout
Géraldine Ottino, Denis Lebel, Jean‐François Bussières

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
FundersAstraZeneca
KeywordsEconomic shortageHealth careBusinessMedicinePolitical scienceLawGovernment (linguistics)

Abstract

fetched live from OpenAlex

in 2010 and 2011, Eggertson highlighted the problem of drug shortages in Canada and described initiatives of the Canadian Pharmacists Association, hospital pharmacists, and drug manufacturers to address the problem. 1,2any stakeholders have underscored the importance of the drug shortage problem and its risks, but few quantitative data have been published. 3,4A few regulatory agencies (e.g., the US Food and Drug Administration 5 and the Agence française de sécurité sanitaire des produits de santé in France 6 ) and a few professional organizations and associations (e.g., the US Institute for Safe Medication Practices, 7 the American Society of Health-System Pharmacists, 8 and the Canadian Pharmacists Association 9 ) have published online guidelines and lists of product shortages to make it easier to manage these events.In Canada, the Pharmacy Practice Research Unit of the Centre hospitalier universitaire Sainte-Justine launched an openaccess website in February 2011 that provides a progress report on all drug shortages in health care institutions (see www.fridaypm.ca[English] and www.vendredipm.ca[French]).Many of these shortages also affect outpatients using oral formulations.Initially, the website was being updated every 2 weeks by our research team using a list of drug shortages provided by the wholesaler McKesson Canada, under contract to SigmaSanté (the group purchasing agent for hospital group purchases in the Montréal and Laval areas and the Eastern Townships of Quebec) and through self-reporting by hospitals.Starting in January 2012, the website was being updated directly by the manufacturers on a voluntary pilot basis; doing so became mandatory on April 1, 2012, according to contractual terms and conditions with SigmaSanté.This real-time updating should make it possible to immediately display progress reports for all of the stakeholders.Our research unit has been interested in drug shortages for more than a year.In a recently published retrospective study, 10 we compiled a list of all the drug shortages experienced by health care institutions in the Montréal and Laval areas and the Eastern Townships from January 2006 to August 2010.Since then, we have gathered data on shortages from August 30, 2010, to August 23, 2011.Our latest data indicate that there were a total of 429 drug shortages in this 12-month period in 2010-2011; the corresponding numbers of drug shortages were 493 in calendar year 2006, 400 in 2007, 442 in 2008, 680 in 2009, and 385 in the first 8 months of 2010.The average duration (± standard deviation) of the drug shortages has remained similar, with 108 ± 130 days (range 5-1623 days) over the period 2006-2010 and 103 ± 85 days (range 8-363) for the 12-month period in 2010-2011.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0050.003
Scholarly communication0.0110.009
Open science0.0010.004
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.071
GPT teacher head0.329
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2012
Admission routes3
Has abstractyes

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