Costs of testing sick children in primary care with pulse oximetry: Evidence from four countries, both with and without electronic clinical decision support
Bibliographic record
Abstract
Introducing pulse oximeters (PO) at primary care facilities can help health workers identify severely ill children who need referral to hospital thereby allowing for improved child clinical outcomes. Adding clinical decision support algorithms (CDSA) can improve adherence to Integrated Management of Childhood Illness guidelines. The current study analyses the costs of introducing PO either with or without an electronic CDSA using an RCT in India and Tanzania and in a pre-post design with an electronic CDSA in Kenya and Senegal. The impact of the intervention is discussed for the RCT (trial registration NCT04910750) and for the pre-post study (trial registration NCT05065320), following SPIRIT guidelines. Economic data were collected in all four countries using questionnaires administered at primary health facilities and referral hospitals and supplemented by information from administrative sources, following CHEERS guidelines. Trained research assistants at the facilities collected data on children enrolled and health outcomes. Net costs per 100 children managed using PO ranged from $16.62 (Kenya, health center) to $70.51 (Tanzania, dispensary), in both cases using CDSA. Senegal was an outlier at $385.45, using PO and CDSA in the smaller postes de santé. Major causes explaining variation included training modality, numbers of sick children attending the facility, and the effect of PO and CDSA on use of antibiotics, diagnostics, and hospitalizations. Standard care (without PO) was associated with fewer severe complications (primarily untimely hospitalizations), at lower cost, in the two countries where effectiveness data are available, India and Tanzania. Scaling up PO use at primary care level nationally could have an important budgetary impact. Findings suggest ways that costs could potentially be reduced. However, hospitalization costs borne by households may affect both household and provider behavior and limit the potential clinical benefits of 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 | 0.001 |
| 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".