Barriers and facilitators to establishing a national public health observatory.
Bibliographic record
Abstract
OBJECTIVE: To determine what stakeholders perceive as barriers and facilitators to creating a national public health observatory (PHO) in Trinidad and Tobago. METHODS: A descriptive study was conducted based on 15 key informant interviews carried out from April to September 2013. The key informants worked within the health care sector in Trinidad and Tobago. Using a semi-structured interview guide, information was collected on knowledge, attitudes, and beliefs about creating a PHO; barriers and facilitators to creating and sustaining a PHO; legal considerations; and human resource and information technology requirements. Common themes of the responses were identified. RESULTS: The majority of participants supported the development of a national PHO, recognized its value in informing their work, and indicated that a national PHO could 1) provide information to support evidence-informed decision-making for health policy and strategic planning; 2) facilitate data management by establishing data policies, procedures, and standards; 3) increase the use of data by synthesizing and disseminating information; and 4) provide data for benchmarking. However, a number of barriers were identified, including 1) the perception that data collection is not valued; 2) untimely availability of data; 3) limited data synthesis, dissemination, and utilization to inform decision-making; and 4) challenges related to the allocation of human resources and existing information technology. CONCLUSIONS: Key informants support the development of a national PHO in Trinidad and Tobago. The findings align well within the components of the conceptual framework for establishing national health observatories. A stepwise approach to establishing a national PHO in Trinidad and Tobago, beginning with structural components and followed by functional components, is recommended. A national PHO in Trinidad and Tobago could serve as a model for other countries in the Caribbean.
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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 | 0.028 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".