Access to WHO Essential Medicines for Childhood Cancer Care in Trinidad and Tobago: A Health System Analysis of Barriers and Enablers
Bibliographic record
Abstract
PURPOSE: Improving access to essential medicines is necessary to reduce global mortality resulting from childhood cancer. However, there is a lack of context-specific data in many low- to middle-income countries on the determinants of access to essential childhood cancer medicines. We conducted a mixed-methods case study of the barriers to and enablers of access to WHO essential medicines for childhood cancer care in Trinidad and Tobago, in response to domestic calls for policy attention and reform. METHODS: We interviewed stakeholders (N = 9) across the pharmaceutical supply system using a novel analytic framework and qualitative interview guide. Interviews were recorded, transcribed, and analyzed with constant comparative methods to capture emergent themes. Quantitatively, we examined alignment of the national essential medicines list with the 2017 WHO Essential Medicines List for Children (EMLc). National buyer prices for EMLc cancer medicines were compared with median international prices, with calculation of median price ratios to assess procurement efficiency. RESULTS: Principal barriers identified included a lack of data-driven procurement, low supplier incentive to engage in tenders, reactive rather than proactive processes in response to stockouts, and siloed information systems. Recurring themes of regionalization, standardization, and proactivity emerged as priorities for policy reform. Quantitative analysis of the national essential medicines list and median price ratios for procured medicines aligned with findings reported qualitatively. CONCLUSION: Our study contributes to global efforts to improve childhood cancer care by identifying policy-relevant evidence on access to essential childhood cancer medicines and providing a model for future studies in other jurisdictions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".