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Record W1976796263 · doi:10.4212/cjhp.v65i3.1138

Drug Shortages: What Can Hospital Pharmacists Do?

2012· article· en· W1976796263 on OpenAlexaffvenueabout
Régis Vaillancourt

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsEconomic shortagePharmacyBusinessGovernment (linguistics)Hospital pharmacyMedicineQuality (philosophy)Medical emergencyNursing

Abstract

fetched live from OpenAlex

Hospital pharmacists have become accustomed to drug shortages over the past few years. For example, in 2010, 94% of Canadian pharmacists surveyed claimed that they had had difficulty locating a medication during the previous week. A 2010 survey of members of the American Society of HealthSystem Pharmacists indicated that both pharmacists and pharmacy technicians were spending an average of 8–9 h/week dealing with issues related to drug shortages. Furthermore, drug shortages are not limited to North America, but rather are a worldwide problem. The causes of drug shortages are multifactorial and include supply disruptions, changes to regulatory requirements, shortages of raw materials, recalls, government pricing strategies, and monopolization of manufacturing. With the current shortages of Sandoz products (first announced in February 2012), hospital pharmacy managers spend most of their days monitoring the drug supply and working with clinicians to deal with the shortages. The question considered here is, What can hospital pharmacists do to prevent further exacerbation of the human-caused crisis we are currently facing? In this era of globalization, drug manufacturers, like hospitals, are always seeking to save money. One way to reduce costs is the concentration of manufacturing. However, if production within a particular company slows down, the whole world may be affected. In a recent study published by the US Food and Drug Administration, 55 (43%) of 127 shortages were attributed to manufacturing quality problems. Does this sound familiar? What role did hospital pharmacists play in the development of the current situation? Hospitals are mandated to provide high-quality care while saving money. As pharmacy managers, many of us deal with a group purchasing organization, such as SigmaSante in Quebec and Medbuy or HealthPRO in the rest of Canada. These 3 buying groups represent about 90% of the Canadian hospital pharmacy market. So what is the connection between group purchasing and the current drug shortages? It arises from the concept of “winner take all”. Currently, group purchasing organizations put out requests for proposals (RPFs) for a 3to 5-year term, which allows the single supplier chosen to reduce its production costs and submit a lower bid on the next RFP. As an example, assume there are 3 manufacturers of a specific injectable product, drug X. Bids submitted in response to an RFP are assessed, and the contract is given to the lowest bidder, supplier Y. When the next RFP is put forward, supplier Y already has a secure production line for drug X, which allows it to bid at a lower price than the other 2 suppliers. Over time, supplier Y may get contracts with all 3 major group purchasing organizations. At that point, it may no longer be cost-effective for other suppliers to keep producing drug X, because their production costs will be too high, and they will probably stop producing drug X. In this way, trying to save money on hospital drug budgets leads to decreased competition and a situation in which supplier Y is the only manufacturer of drug X. If this supplier’s plant goes “down” for some reason, we are in trouble. In fact, this is what is happening right now! What can we learn from the current drug shortages? The simple answer is that we need to maintain healthy competition in the Canadian drug market to secure the chain of supply of essential drugs. This is not a new concept. For example, the federal, provincial, and territorial vaccine contracting group understood the risk years ago. This contracting group is responsible for nationwide procurement of vaccines. To maintain Canadian manufacturing capacity for the influenza vaccine, the group has been awarding a split contract for many years, giving the majority of the business to the lowest bidder and the remainder to the secondand possibly third-lowest bidders. The split may be 50%–25%–25% if there are 3 suppliers or 70%–30% if there are only 2. This approach ensures that more than one manufacturer is able to maintain a production chain. In contrast, New Zealand had a single-source provider for influenza vaccine

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)0.011
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.017
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0100.020
Open science0.0030.007
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0100.004

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 head0.043
GPT teacher head0.284
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations6
Published2012
Admission routes3
Has abstractyes

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