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Record W2600754488 · doi:10.1093/schbul/sbx024.108

SU112. The Dark Side of Haloperidol Decanoate Shortage in Canada

2017· article· en· W2600754488 on OpenAlexaffabout
Marie‐France Demers, Isabelle Bilodeau, Laurie Laberge, Daniel A. Lavigne, Guylaine Tremblay, Guillaume Chalifour, Éric Lepage, Marc‐André Roy

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité Laval
Fundersnot available
KeywordsMedicineEconomic shortagePopulationPharmacyHealth careAntipsychoticSchizophrenia (object-oriented programming)PsychiatryFamily medicineEnvironmental healthPolitical scienceGovernment (linguistics)

Abstract

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Background: Drug shortages have become an issue of growing interest for health care providers and patients. The number of drug shortages has been rapidly escalating in the last decade all over the world and affecting all types of drugs. In July 2015, American Society of Hospital Pharmacy (ASHP) reports 265 active-drug shortages. Among impacts of such shortages are safety risks, including compromised efficacy, increased side effects burden, more frequent medication errors, and that lead to higher hospital expenses, spanning higher costs for substitute drug, increased costs for health care professionals to deal with switches and rehospitalization. Subsequent shortage of the alternative drug may add to the complexity of the situation over time. In treatment of schizophrenia (Sz), it is only in the recent years that drug shortages became an issue in Canada (Piportil, 2014; Haldol, 2015; Modecate, 2016). In such population, long-acting injectable antipsychotic (LAIAs) are traditionally used in nonadherent, so called “difficult to follow” patients even though, there is a lot of recent literature favoring earlier use of LAIAs in the course of treatment. Haloperidol decanoate (HD) is a first-generation LAIA indicated in the treatment of schizophrenia. In Canada, in 2015, a 6-month shortage of HD led to the obligation of switching patients from this antipsychotic to another drug. Methods: We report a retrospective chart-review mirror study of the 6 months before and after switching HD in 61 patients followed in a third-line psychiatric hospital facility in Quebec city. Results: Patients were mainly suffering from Sz (80%; BP 20%). A significant proportion of patients were also suffering from comorbid personality disorders 46% and/or 57% substance use disorders. Mean age was 50 years old. For 30% of the patients, extrapyramidal syndrome (such as tardive dyskinesia) was described with use of HD before switching. For 60% of patients, HD had been used for more than 10 years. Fifty-eight percentage of the cohort had not been hospitalized during the previous 2 years. A third of the patients were switched to fluphenazine décanoate (FD), while another third were switched to oral haloperidol, the others to various other antipsychotics (only 1 patient to clozapine). Over all, in the 6 month before switching, number of hospitalization days required for this cohort was 800 days compared to 1185 days in the 6 months after, with an individual “mean hospitalization duration of 31 days before compared to 40 days afterwards, corresponding to cost increase of $180 000, only including hospitalizations”. Conclusion: HD shortage had significant impacts, particularly on hospitalizations, in this cohort according to our retrospective chart review. Moreover, in summer 2016, FD itself became back-ordered meaning a new switch for many of those vulnerable patients. These results call for a more vigorous and coordinated reaction from our health care authorities to avoid such situations.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.244
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations3
Published2017
Admission routes2
Has abstractyes

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