PP101 Development Process Of The Economic Guidelines In Tunisia
Bibliographic record
Abstract
Introduction Health technology assessment (HTA) has become a critical support to health policy decision-making. The HTA evaluation process requires transparency, formalized processes, clear timelines, and standardization according to international best practice. Tunisia is establishing an HTA-based decision-making system through the National Authority for Accreditation and Assessment in Healthcare (INEAS) to ensure impartiality and fairness in decision-making, which is important for an emerging democracy. INEAS opted for a participatory approach in developing the national health economic guidelines to better engage healthcare sector stakeholders in the HTA process. We aimed to present the main phases of the process used to develop the Tunisian health economic guidelines, the methodological choices for pharmacoeconomic evaluations, and the methodological choices for budget impact analyses. Methods The different phases of developing the guidelines were listed and reported. Results The guidelines were developed under a technical cooperation program of the World Health Organization and involved collaboration between the Institut national d’excellence en santé et en services sociaux (INESSS in Quebec, Canada) and INEAS. The first version of the guidelines was drafted following a review of international HTA guidelines and best practice reference books, taking into account the Tunisian healthcare system context. This first draft was discussed in a workshop with the main health system stakeholders and then peer reviewed by international experts. Based on the feedback from experts, a second version was prepared and published on the INEAS website for public consultation. The Union of Innovative Pharmaceutical Research Companies (SEPHIRE), the National Health Insurance Fund (CNAM), and healthcare professionals provided the majority of feedback. The comments provided by SEPHIRE were discussed during a second workshop. The guidelines were revised and updated based on the comments provided and the final version was published in November 2021. Conclusions INEAS adopted a participatory approach for developing its economic guidelines, which enhanced engagement of the major health system stakeholders in the HTA implementation process in Tunisia.
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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 | 0.069 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".