Effect of unmanned aerial vehicle (drone) delivery on blood product delivery time and wastage in Rwanda: a retrospective, cross-sectional study and time series analysis
Bibliographic record
Abstract
BACKGROUND: The accessibility of blood and blood products remains challenging in many countries because of the complex supply chain of short lifetime products, timely access, and demand fluctuation at the hospital level. In an effort to improve availability and delivery times, Rwanda launched the use of drones to deliver blood products to remote health facilities. We evaluated the effect of this intervention on blood product delivery times and wastage. METHODS: We studied data from 20 health facilities between Jan 1, 2015, and Dec 31, 2019, in Rwanda. First, we did a cross-sectional comparison of data on emergency delivery times from the drone operator collected between March 17, 2017, and Dec 31, 2019, with two sources of estimated driving times (Regional Centre for Blood Transfusion estimates and Google Maps). Second, we used interrupted time series analysis and monthly administrative data to assess changes in blood product expirations after the commencement of drone deliveries. FINDINGS: Between March 17, 2017, and Dec 31, 2019, 12 733 blood product orders were delivered by drones. 5517 (43%) of 12 733 were emergency orders. The mean drone delivery time was 49·6 min (95% CI 49·1 to 50·2), which was 79 min faster than existing road delivery methods based on estimated driving times (p<0·0001) and 98 min faster based on Google Maps estimates (p<0·0001). The decrease in mean delivery time ranged from 3 min to 211 min depending on the distance to the facility and road quality. We also found a decrease of 7·1 blood unit expirations per month after the start of drone delivery (95% CI -11·8 to -2·4), which translated to a 67% reduction at 12 months. INTERPRETATION: We found that drone delivery led to faster delivery times and less blood component wastage in health facilities. Future studies should investigate if these improvements are cost-effective, and whether drone delivery might be effective for other pharmaceutical and health supplies that cannot be easily stored at remote facilities. FUNDING: Canadian Institutes for Health Research.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".