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Record W2907431713 · doi:10.1017/s0266462318002131

PP51 Updating Canadian Pharmaceutical Budget Impact Analysis Guidelines

2018· article· en· W2907431713 on OpenAlexaboutno aff
Naghmeh Foroutan, Mitchell Levine, Jean‐Éric Tarride, Feng Xie

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsGuidelineMEDLINESystematic reviewMedicineGrey literatureAgency (philosophy)Family medicinePolitical science

Abstract

fetched live from OpenAlex

Introduction: The Canadian BIA guideline was published by the Patented Medicine Prices Review Board (PMPRB) in 2007. Our initial systematic literature review of national and international BIA guidelines showed that a number of new recommendations relating to BIA model structure, input data and reporting format have been adopted in other jurisdictions such as UK, Australia, Poland, Ireland, Belgium, France and the International Society for Pharmacoeconomics and Outcomes Research (ISPOR). The main objective of the present study was to conduct a comparative review of national, international and Canadian Federal, provincial and territorial BIA guidelines and provide a list of new recommendations related to the BIA key elements which have not been discussed or included in the Canadian PMPRB BIA guidelines. Methods: BIAs guidelines were searched in databases such as MEDLINE, EMBASE, Cochrane, and the gray literature including regulatory agency websites. An Excel-based data abstraction form was designed in order to highlight differences between recommendations related to the BIA key elements provided by PMPRB, provincial, and other national and international BIA guidelines. Results: Twelve guidelines were reviewed in detail. Sixty percent of the recommendations were new or were different from recommendations in the Canadian PMPRB BIA guidelines. They related to BIA key elements such as perspective, target population, costing, presenting results, data sources and handling the uncertainty. Conclusions: The present literature review is the initial step towards updating the Canadian BIA guidelines. This study presents a comparative review of key elements in BIA among different guidelines and provides a list of relevant practical recommendations for the improvement of the Canadian BIA guidelines. The new methodologic advancements and recommendations that were identified are being presented to Canadian stakeholders for their opinion and feedback prior to the development of a proposed new set of Canadian guidelines.

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)0.073
metaresearch head score (Gemma)0.297
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.687

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.297
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0320.035
Science and technology studies0.0040.002
Scholarly communication0.0120.004
Open science0.0090.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0230.005

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 head0.256
GPT teacher head0.578
Teacher spread0.322 · 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.

Study designNot applicable
DomainMethods
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

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