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Record W4406147792 · doi:10.1017/s0266462324004173

PD195 Variation In Decision-Making And Market Access Routes For Vaccines: Insights From Seven Countries

2024· article· en· W4406147792 on OpenAlexaboutno aff
Emily Gregg, K. Watts, Charlotte Graham, Stuart Mealing

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementBusinessMarket accessEuropean unionReimbursementAuthorizationPublic economicsMarketingEconomic growthEconomicsInternational tradeGeographyComputer science

Abstract

fetched live from OpenAlex

Introduction Quick and equitable market access to vaccines is a global priority. However, market access routes for vaccines are complex and differ from those for pharmaceuticals. Furthermore, there is variation in decision-making between countries due to local requirements. This work aimed to increase awareness of the key elements of these pathways and the stakeholders involved in European Union (EU) and non-EU countries. Methods Pragmatic desk-based research was undertaken in November 2023 to explore key elements of the market access pathways for vaccines and how these differ between countries. Specifically, the countries of interest were Canada, England, France, Germany, Italy, Spain, and the USA. Where available, information was extracted about the key stages and stakeholders involved in the decision-making pathway as well as details about any post-licensing monitoring, the value assessment framework used, vaccine pricing, and the procurement process. In addition, examples of barriers to vaccine access were extracted. The key findings and between-country differences were summarized narratively. Results National Immunization Technical Advisory Groups (NITAGs) were key stakeholders in all countries explored and had varying roles. The evidence requirements differed among countries, such as Germany’s requirement for economic and epidemiological modeling. The Vaccine Monitoring Platform coordinates studies for post-authorization monitoring of vaccines across EU countries. However, England is not part of this network and uses a national agency instead. Vaccine procurement and pricing also differed (e.g., France uses individual reimbursement, England uses national tendering, and Canada uses regional tendering). There was variation in vaccine pricing within the USA, depending on the healthcare provider. Barriers to vaccine access were well reported. Conclusions These results can influence the market access strategy of vaccine developers to ensure rapid and equitable vaccine access across countries. Several between-country differences in vaccine market access routes were identified; for example, the role of NITAGs, evidence requirements, and post-licensing monitoring processes. Barriers to vaccine access have been reported in the literature, with some organizations providing recommendations to overcome these.

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)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.406
Teacher spread0.393 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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