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Record W2027781054 · doi:10.1177/1715163513490654

Wasted medications, wasted resource

2013· article· en· W2027781054 on OpenAlexaffvenueabout
Jeffry Tchen, Régis Vaillancourt, Annie Pouliot

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2013
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Waterloo
Fundersnot available
KeywordsUnderinsuredGovernment (linguistics)Medical prescriptionPharmacyBusinessHealth careCopaymentMedicineHealth insuranceEnvironmental healthEconomic growthFamily medicineNursingEconomics

Abstract

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In Canada, almost anything can be recycled; however, medication is not currently recycled in community practice. For many years, US hospitals in some states have taken unused medication and redispensed it without an issue.1 In 2010, Canadians spent $31.1 billion on drugs.2 It is estimated that 3% to 7% of medications intended for patients goes unused in the United States and that similar wastage could cost Canada approximately $8 billion annually.3,4 In the current economic climate, the government is searching for ways to improve and pay for public health care. Recycling medication is a solution that sacrifices neither quality nor finances. A Health Canada study from 2000 revealed that more than 10% of Canadians had no insurance, while another 10% were considered underinsured (those spending 2.5% of their gross family income for drugs are considered underinsured and those paying 4.5% are considered uninsured).5 Medications are not covered for outpatients, resulting in a situation where those who cannot afford medications have adherence issues. The lack of a publicly funded program to pay for medications for marginalized Canadians puts them at increased risk of health problems, stress and hospitalization. In 38 US states, there have been medication recycling programs in place dating as far back as 1997.3 In Tulsa, Oklahoma, alone, 6000 prescriptions were collected in 2005, which resulted in a savings of $1.4 million.6 In this program, drugs were collected from nursing homes and then distributed to patients in need via a central pharmacy.1 The nursing home residents sign a consent form to release their medication to the recycling program. Those who wish to participate in the program must sign a consent form acknowledging they understand the purpose of the program and that the pharmacy, pharmacist and manufacturers are not held responsible for medications that have been donated in good faith. To ensure patient safety, all states that have legislation concerning drug recycling contain provisions: that all collected donations must have an expiration date and not be expired, that a licensed pharmacist is part of the verification and distribution process, that each patient who receives a drug must have a valid prescription and that controlled substances cannot be collected. In some states, only drugs that are packaged in unit doses and have not left the circle of care can be collected, so that the safety of the medicines can be ensured. In the 3 years that the Iowa Prescription Drug Corporation has been distributing recycled drugs, there has been no evidence that patient safety has been compromised.1 Currently, laws in most provinces prevent an initiative like this from taking place because it is professional misconduct to redispense and resell medication. These laws have been put in place to protect the public, but are we really protecting the segments of the population unable to afford medication? Canadians who lack insurance, for instance when they are unemployed or their finances are not sufficient, can be put under unnecessary stress by needing to find ways to pay for potentially lifesaving medication. Although a recycling program would not resolve access to medication as fully as universal prescription coverage, it would fill a void for those Canadians who would otherwise have to make difficult financial decisions. A Canadian recycling program, run by a not-for-profit organization to prevent double-billing, would not put added pressure on government and would save patients money and improve their health without putting them at increased risk. We need to implement a program like this in Canada to ensure that everybody who needs medication can access it. ■

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)0.003
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.186
Threshold uncertainty score0.371

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0070.012
Scholarly communication0.0110.007
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0260.005

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 head0.118
GPT teacher head0.391
Teacher spread0.273 · 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

Citations11
Published2013
Admission routes3
Has abstractyes

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