PP43 Impact Of The COVID-19 Pandemic In The Brazilian National Committee for Health Technology Incorporation (Conitec) Recommendation Process
Bibliographic record
Abstract
Introduction Health Technology Assessment (HTA) Process assists decision-making in health policies. The COVID-19 pandemic caused a high demand on protocol or guideline updates and incorporation of new drugs or therapies, overwhelming local agencies. A recent study reported that major HTA bodies in England, Scotland, Germany, and Canada reduced their number of drug recommendations in 2020, due to reprioritization of resources and COVID-related challenges. The present study aimed to evaluate the impact of the COVID-19 pandemic at the Brazilian National Committee for Health Technology Incorporation (Conitec) recommendation process. Methods This descriptive study evaluated all official recommendation reports available on the Government website in 2020 and 2021, extracting the data of disease category, technology type, the aim of the report, Public Involvement, and final result for the recommendation. The results were presented in tabular and graphical form using the machine learning, through the software R studio and excel. Results A total of 168 documents were evaluated, including guidelines and recommendation reports, with no reduction in the number of evaluations considering 2019. In 2020, there was a more significant evaluation of guidelines, and in 2021, a report on the non-incorporation of technologies. There were four specific documents about COVID 19, including vaccines and hospital care guidelines. The most incorporated and non-incorporated technologies were medication, targeting rare and highly prevalent diseases in balance. The Brazilian government was the main proposer. These results are part of the study “A Survey about the core methods of the recommendation reports for Brazilian Ministry of Health carried out by Brazilian Health Technology Assessment Centers”, which will characterize and analyze the core methods of the recommendation reports conducted by the Brazilian HTA Centers. Conclusions The pandemic had a low impact on demands in the routine of the Conitec. Establish indicators and technological norms applicable to health services, contribute to the identification of possible new practices, methods or criteria.
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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 | 0.101 | 0.249 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".