Pre‐Hospital Pulse‐Oximetry and Supplemental Oxygen Utilization in Malawi: An Exploratory Cost‐Effectiveness Analysis
Bibliographic record
Abstract
BACKGROUND: Pneumonia is the leading cause of death globally in children aged 0-5 years. Early access to pulse-oximetry and supplemental oxygen in low-resource, pre-hospital settings may result in improved pediatric pneumonia outcomes. However, few data exist regarding their application in such settings. METHODS: We performed an exploratory cost-effectiveness analysis using a decision analytic model to examine use of pulse-oximetry and supplemental oxygen in pre-hospital environments of Malawi. RESULTS: Our model yielded an Incremental Cost-Effectiveness Ratio (ICER) for pre-hospital pulse-oximetry use of $35 (USD) per disability-adjusted life-year (DALY) averted compared to no pulse-oximetry use. One-way sensitivity analysis showed highest sensitivity to the parameter of downstream hospitalization cost. Given that inpatient management is the standard of care for hypoxemic pneumonia, when only pre-hospital costs were considered the result was an ICER of $9.9/DALY averted. Both values were considered cost-effective according to a conservative willingness-to-pay (WTP) threshold set for 1x the average GDP per capita in Malawi ($588, 2018). When oxygen was analyzed in combination with pulse-oximetry, we found a baseline WTP threshold for pre-hospital oxygen of $71 per patient. For every 1% reduction in total pediatric pneumonia mortality consequent to pre-hospital oxygen use, we determined the recommended WTP allowance for oxygen would increase by approximately $4.53. CONCLUSION: We conclude that pulse-oximetry is likely cost-effective in low-resource, pre-hospital environments. We acknowledge the need for further research on the effectiveness of pre-hospital oxygen in reducing pediatric pneumonia mortality and suggest ranges of cost and efficacy for which oxygen is likely to be found cost-effective in tandem with pulse-oximetry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".