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Record W4317209651 · doi:10.1007/s40258-022-00787-0

The Impact of Suboxone’s Market Exclusivity on Cost of Opioid Use Disorder Treatment

2023· article· en· W4317209651 on OpenAlexafffundabout
Meghan McGee, Kellia Chiu, Rahim Moineddin, Abhimanyu Sud

Bibliographic record

VenueApplied Health Economics and Health Policy · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsInstitute for Work & HealthHumber River Regional HospitalUniversity of TorontoLunenfeld-Tanenbaum Research Institute
FundersHealth Canada
KeywordsBuprenorphine(+)-NaloxoneMedicineMethadoneOpioid use disorderFormularyPublic healthListing (finance)OpioidEmergency medicineAnesthesiaBusinessFamily medicineFinanceInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Buprenorphine-naloxone is an essential part of the response to opioid poisoning rates in North America. Manipulating market exclusivity is a strategy manufacturers use to increase profitability, as evidenced by Suboxone in the USA. OBJECTIVE: To investigate excess costs of buprenorphine-naloxone due to unmerited market exclusivity (no legal patent or data protection) in Canada. METHODS: Using controlled interrupted time-series, this study examined changes in the cost of buprenorphine-naloxone before and after the first generics were listed on public formularies. Methadone cost was the control. Public data from the Canadian Institute of Health Information in British Columbia, Manitoba, and Saskatchewan were used. All buprenorphine-naloxone and methadone claims (2010-2019) accepted for payment by the provincial drug plan/programme were collected. Primary outcome was mean cost per mg of buprenorphine-naloxone after the first listing of generics. RESULTS: Mean cost per mg of buprenorphine-naloxone before the first listing of generics was $1.21 CAD in British Columbia, $1.27 CAD in Manitoba, and $0.85 CAD in Saskatchewan. Following the introduction of generics, the cost per mg decreased by $0.22 CAD (95% CI - 0.33 to - 0.10; p = 0.0014) in British Columbia, $0.36 CAD (95% CI - 0.58 to - 0.13; p = 0.004) in Manitoba, and $0.27 CAD (95% CI - 0.50 to - 0.05; p = 0.03) in Saskatchewan. Mean cost per mg decreased by $0.26 CAD (95% CI - 0.38 to - 0.13; p = 0.0004) after a third generic was introduced in British Columbia. Excess costs to public formularies during the 4- to 5-year period prior to the listing of generics were $1,992,558 CAD in British Columbia, $80,876 CAD in Manitoba, and $4130 CAD in Saskatchewan. If buprenorphine-naloxone cost $0.61 CAD (mean cost after the third generic entered) instead of $1.21 CAD per mg during the pre-generics period, public payers in British Columbia could have saved $5,016,220 CAD between 2011 and 2015. CONCLUSIONS: Unmerited 6 years of market exclusivity for brand-name buprenorphine-naloxone in Canada resulted in substantial excess costs. There is an urgent need to implement policies that can help reduce costs for high-priority drugs in Canada.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.143
GPT teacher head0.408
Teacher spread0.265 · 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 designTheoretical or conceptual
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

Citations2
Published2023
Admission routes3
Has abstractyes

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