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Record W2931204110 · doi:10.3389/fphar.2019.00196

Factors Influencing Delays in Patient Access to New Medicines in Canada: A Retrospective Study of Reimbursement Processes in Public Drug Plans

2019· article· en· W2931204110 on OpenAlexafffundabout
Sam Salek, Sarah Lussier Hoskyn, Jeffrey Johns, Nicola Allen, Chander Sehgal

Bibliographic record

VenueFrontiers in Pharmacology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsInnovative Medicines Canada
FundersInnovative Medicines Canada
KeywordsReimbursementListing (finance)MedicinePublic healthNoticeFamily medicineTimelineHealth technologyOrphan drugBusinessHealth careFinanceNursingEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Individuals who rely on public health payers to access new medicines can access fewer innovative medicines and must wait longer in Canada compared to major markets around the world. New medicines/indications approved by Health Canada and reviewed for eligibility for reimbursement by the Common Drug Review or the pan-Canadian Oncology Drug Review (CDR/pCODR) from the beginning of 2012 through to the end of December 2016 were analyzed, with data taken from the relevant bodies' websites and collected by IQVIA. This analysis investigated individual review segments - Notice of Compliance (NOC) to Health Technology Assessment (HTA) submission, HTA review time, pan-Canadian Pharmaceutical Alliance (pCPA) negotiation time, and public reimbursement decision time, and analyzed the trends of each over time and contributions to overall time to listing decisions. Average overall timelines for public reimbursement after NOC were long and most of this time is taken up by HTA and pCPA processes, at 236 and 273 days, respectively. This study confirms that Canadian public reimbursement delays from 2013-2014 to 2015-2016 lengthened from NOC to listing (Quebec + 53%, first provincial listing + 38%, and country-wide listing + 22%), reaching 499, 505, and 571 days, respectively. Over the same period, time from NOC to completion of HTA has increased by 33%, and time from post-HTA to first provincial listing by 44%. The pCPA process appears to be the main contributor to this increasing time trend, and although some provinces could be listing more quickly post-pCPA, they appear to be listing fewer products. Reasons for large delays in time to listing include the many-layered sequential process of reviews conducted before public drug plans decide whether to provide access to new innovative medicines. Although there has been some headway made in certain parts of the review processes (e.g., pre-NOC HTA), total time to listing continues to increase, seemingly due to the pCPA process and other additional review processes by drug plans. More clarity in the pCPA and provincial decision-making processes and better coordination between HTA, pCPA, and provincial decision-making processes is needed to increase predictability in the processes and reduce timelines for Canadian patients and manufacturers.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
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 head0.173
GPT teacher head0.394
Teacher spread0.222 · 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.

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

Citations28
Published2019
Admission routes3
Has abstractyes

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