Health technology assessment for resource allocation decisions: Are key principles relevant for Latin America?
Bibliographic record
Abstract
OBJECTIVES: A set of fifteen key principles (KP) has been recently proposed to guide decisions on the structure of HTA programs, the methods of HTA, the processes for conducting HTA and the use of HTA findings in decision-making. The objective of this research is to explore whether these KPs are relevant and useful in Latin America (LA), and to what extent they are being applied. METHODS: A Web-based survey was sent to 11,792 HTA researchers and users in LA to explore the perceived relevance of each KP, its current level of application and the gap between these two. RESULTS: We received 1,142 responses from nineteen LA countries (9.7 percent response rate). The subgroup of KP related to Methods and to the Use of HTA received the higher mean scores in the relevance scale (9.00 and 8.94). Level of current application scored low in all KP (3.2 to 4.9). Higher gaps were observed in principles related to the use of HTA in decision making and to the processes for conducting HTA. Countries with more developed HTA showed higher scores in the degree of current application (5.3 versus 3.4, p < .01) and lower gaps (3.84 versus 5.21, p < .01). Researchers, compared with research users, scored the relevance of the KPs higher. CONCLUSIONS: KPs seem to be very relevant to most HTA researchers and users in LA. However, the current level of application was considered uniformly poor. Higher gaps were observed in KPs related to the link between HTA and decision making, highlighting one of the major challenges for the countries in the region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".