Compliance of public health facilities with essential medicines and health supplies redistribution guidelines in Mbale district, Eastern Uganda: a mixed-methods study
Bibliographic record
Abstract
INTRODUCTION: Redistribution of essential medicines and health supplies (EMHS) is a mechanism to address supply chain uncertainty by moving excess stock of health commodities from health facilities that are overstocked to health facilities with shortages, where it is most needed. It prevents the wastage of scarce resources and improves efficiency within a health supply chain system. Many public health facilities in Uganda experience stock-outs, overstocking, and expiry of essential medicines. This study assessed the compliance of public health facilities with the Uganda Ministry of Health redistribution strategy for EMHS in Mbale district, Eastern Uganda. METHODS: A mixed-methods study was conducted among 55 respondents at public health facility level and five key informants at the district level. Audio-recorded data were transcribed and coded to develop themes. Thematic analysis was performed using ATLAS.ti Version 8.5. Quantitative data were analysed using IBM SPSS Version 24.0. RESULTS: About a third (33%) of the surveyed health facilities complied with EMHS redistribution guidelines. Respondents agreed that EMHS redistribution had helped reduce health commodity expiries and stock-outs in health facilities. Respondents who did not know about the timely release of funds for redistribution were 68% less likely to comply, and those who said the guidelines were never shared were 88% less likely to comply with the guidelines. CONCLUSIONS: Compliance with the EMHS redistribution guidelines was low and associated with failure to share the guidelines with staff and inadequate awareness about release funds for EMHS redistribution. The district local government should allocate more funds to the EMHS redistribution.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".