Stakeholders’ feedback on the proposed recommendations for updating the patented medicine prices review board (pmprb) budget impact analysis guidelines
Bibliographic record
Abstract
INTRODUCTION: The present study aimed to obtain Canadian stakeholders' feedback on a list of proposed recommendations for updating the Patented Medicine Prices Review Board (PMPRB)'s 2007 budget impact analysis (BIA) guidelines. METHODS: A mixed-methods study was designed to obtain feedback from two stakeholder perspectives-(public and private) payers and manufacturers-on the proposed BIA recommendations. We obtained policymakers' opinion through one-on-one interviews and collected feedback from manufacturers and their consultants using a survey. The interview guide and the survey were developed based on the list of recommendations related to BIA key elements, which were either not discussed or addressed differently in the PMPRB 2007 BIA guidelines. The list was derived from 16 Canadian or other national and transnational BIA guidelines. A thematic analysis was applied for analysis of the qualitative (interview) data. RESULTS: Thirty-five policymakers and manufacturers participated in the study. Stakeholders supported the inclusion of 56% of the proposed recommendations into the guidelines pertaining to the use of expert opinions, data extrapolated from the payers' database, scenario analysis, and dynamic population. Inclusion of indirect costs, and cost transfers from other jurisdictions, were not approved. There was no consensus regarding the inclusion of patients' adherence/compliance and cost offsets. CONCLUSIONS: The present study has provided sufficient insights to enable the creation of a penultimate version for updating the PMPRB BIA guidelines. This penultimate version will be subject to a broader consultation among stakeholders prior to a final revision and approval. Further Canadian stakeholder feedback is required for reaching consensus on inconclusive recommendations.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.075 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".