Access to essential medicines within the ethnic health system in eastern Myanmar
Bibliographic record
Abstract
The eastern border region of Myanmar is a mainly rural area, with a large population of vulnerable groups due to internal displacement and ongoing ethnic conflict and discrimination. Myanmar has the 2nd lowest overall health system performance out of 191 countries internationally, and reports indicate that ethnic communities are largely excluded from formal healthcare. Health and human rights concerns have been raised over limited access to essential medicines (AEM)1,2. Implications of not having AEM, such as antibiotics and vitamins, include high rates of morbidity, suffering, and morality at individual levels and low average life expectancy and poor overall health at the population level3. This cross-sectional study aims to describe the current level of access to seven different essential children’s medicines in 98 clinics in eastern Myanmar, using stock data from the Health Facility Assessment Tools 2017 Survey. The association between level of clinic remoteness (distance to the clinic from a large city) and AEM is being explored. Data analysis is currently being conducted and results will be available in March 2019. There is limited research pertaining to this geographic region and population despite evidence of a damaged health system and a high volume of potentially vulnerable people. Therefore, the findings of this study could inform further investigations to improve equitable access to essential medicines among all people in eastern Myanmar. References 1. Loxley, R. Opportunities for Health System Strengthening during Government Transition in Myanmar: a Major Research Paper. (Queen's University, 2016). 2. Tandon, A., Murray, C. J., Lauer, J. A. & Evans, D. B. Measuring health system performance for 191 countries. GPE Discuss. Pap. Ser. No. 30 (2000). doi:10.1007/s10198-002-0138-1 3. Ahmadiani, S. & Nikfar, S. Challenges of access to medicine and the responsibility of pharmaceutical companies: A legal perspective. DARU, J. Pharm. Sci. (2016). doi:10.1186/s40199-016-0151-z
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".