Effectiveness of introducing pulse oximetry and clinical decision support algorithms for the management of sick children in primary care in India and Tanzania on hospitalisation and mortality: the TIMCI pragmatic cluster randomised controlled trial
Bibliographic record
Abstract
Background Pulse oximetry can support better detection of hypoxaemia, an important mortality predictor, and digital clinical decision support algorithms (CDSAs) can strengthen adherence to Integrated Management of Childhood Illness (IMCI) guidelines. This study sought to address evidence gaps on the impact of providing these tools to primary care healthcare providers on under-five hospitalisations and mortality. Methods A pragmatic, parallel group, superiority, cluster randomised controlled trial (RCT) conducted in 172 primary care facilities in India and Tanzania (106 and 66 facilities, respectively). Facilities were randomly allocated (1:1) in India to pulse oximetry (PO) or control and (1:1:1) in Tanzania to PO + CDSA, PO, or control, stratified by facility type and location (India: district; Tanzania: urban/rural). Sick children aged 0–59 months attending study facilities were eligible. Pulse oximeters and CDSAs were given to healthcare providers, along with training and guidance, supportive supervision, monitoring, community engagement, and operational support. Providers were advised to use pulse oximetry for all sick children in India, and in Tanzania for all 1–59 days, and for those 2–59 months with cough, difficulty breathing, or a moderate to severe illness. Urgent referral was recommended for SpO 2 <90%. Trained research assistants collected data from caregivers and facility records on Day 0, with a follow-up phone call or visit on Day 7 and 28. Two primary outcomes, based on caregiver report, were assessed centrally: 1) rates of ‘severe complication' (death, delayed hospitalisation (≥24 h from the Day 0 consultation) or hospitalisation without Day 0 referral) by Day 7; and 2) rates of hospitalisation within 24 h of the Day 0 consultation, with referral. Intention-to-treat analyses were performed on combined and individual country data, stratified by age (1–59 days, 2–59 months). Primary outcomes were assessed using generalised estimating equations for logistic regression, with facilities as clusters. Results were estimated in terms of odds ratios and risk differences (RDs), adjusted where computable. The trial is registered with clinicaltrials.gov (NCT04910750). Findings A total of 157,677 sick children (1–59 days: 3188 control, 4012 PO, 2386 PO + CDSA; 2–59 months: 54,318 control, 56,968 PO, 36,805 PO + CDSA) were enrolled from 28 March, 2022 to 31 March, 2023 in Tanzania and from 20 June, 2022 to 21 April, 2023 in India. Severe complications were rare in the control arm, with 16 (0·5%) events in 1–59 days, 77 (0·1%) in 2–59 months. No significant difference was observed in 1–59 days in the PO arm, with 27 events (0·7%, RD 0·2% [−0·2%; 0·5%]), but a slight increase was noted in 2–59 months, with 143 events (0·3%, adjusted RD 0·1% [0·0%; 0·2%]). No statistically significant differences were observed in the CDSA + PO arm, with 21 events (0·9%, RD 0·5% [−0·1%, 1·0%]) in 1–59 days, 128 (0·3%, adjusted RD 0·1% [−0·0%, 0·3%]) in 2–59 months. Day 0 hospitalisations with referral were very rare in the control arm, with 0 events (0·0%) in 1–59 days, 12 (0·0%) in 2–59 months. Arm comparisons were either not computable or not statistically significant, within the PO arm: 9 events (0·2%) in 1–59 days, 22 (0·0%, RD 0·0% [−0·0%, 0·1%]) in 2–59 months; in the CDSA + PO arm: 6 events (0·3%) in 1–59 days, 32 (0·1%, RD 0·0% [−0·0%, 0·1%]) in 2–59 months. Interpretation When implemented in routine health systems at primary care level in India and Tanzania, contrary to expectations, pulse oximetry and CDSAs were not found to increase rates of hospitalisation within 24 h of primary care referral, nor to decrease deaths, or delayed or un-referred hospitalisations. Wider health system challenges, including referral barriers, inequitable oxygen access and hospital care quality must be addressed if the potential of these tools in delivering child outcome benefits is to be realised. Funding Unitaid grant n°2019-35-TIMCI: Tools for Integrated Management of Childhood Illness.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".