Evidence map›Paper›PMID 42743224›Full record

Trial reportPloS one2026

Assessing the accuracy and efficiency of an electronic platform for managing childhood illnesses in rural China: A cluster randomized controlled trial.

Puhong Zhang, Yang Zhao, Jie Shang, Duolikun Nadila, Tao Li, Yu Liu, Gulizat Abdurixit, Jane Elizabeth Hirst

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Puhong ZhangThe George Institute for Global Health, China Office, Beijing, China.ORCID https://orcid.org/0000-0003-4610-9848
Yang ZhaoThe George Institute for Global Health, China Office, Beijing, China.
Jie ShangThe George Institute for Global Health, China Office, Beijing, China.
Duolikun NadilaThe George Institute for Global Health, China Office, Beijing, China.
Tao LiChild Health Big Data Research Center, Capital Institute of Paediatrics, Beijing, China.
Yu LiuSchool of Computer Science and Engineering, Beihang University, Beijing, China.
Gulizat AbdurixitXinjiang Programme, Save the Children, Xinjiang, China.
Jane Elizabeth HirstNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe Integrated Management of Childhood Illness (IMCI) faces challenges in capacity building and quality control. This trial aims to assess an electronic IMCI (eIMCI) platform in improving the effectiveness and efficiency in disease classification and management by community health workers (CHWs).

designCluster randomized controlled trial.

settingRural western China.

participants24 CHWs and 72 ill children aged 2 months to 5 years (3 children per CHW). CHWs were randomly assigned to intervention or control groups.

interventionsThe intervention CHWs received online training and performed disease management using the eIMCI platform featuring integrated training modules and decision-support tools. The control group received traditional face-to-face training and used paper-based IMCI protocols.

main outcome measuresProportion of children correctly diagnosed or classified by CHWs, as determined by a pediatric specialist. Relative risk (RR) between groups was estimated using Poisson Generalized Linear Mixed Models incorporating a random intercept for CHW to account for clustering of children within individual CHWs and adjusting for key covariates at both the CHW and child levels.

resultsThe intervention group (13 CHWs, 39 children) had a higher rate of correct classification (64.1%) compared to the control group (11 CHWs, 33 children) (39.4%, P = .056). Multivariable regression analysis confirmed this (RR = 2.1, 95% CI: 1.5-3.1; P < .001). No significant difference was found in correct treatment rates (38.5% vs. 27.3%, P = .316). Online training reduced time and costs by approximately 80%, though with a slight decrease in post-training evaluation scores.

conclusionsThe eIMCI platform shows potential in enhancing IMCI implementation and significantly reducing the training burden in resource-limited settings. Trial registration: Chinese Clinical Trial Registry: ChiCTR2100042533, https://www.chictr.org.cn/showproj.html?proj=119995.

Indexed as

Community Health WorkersChild, PreschoolChinaCluster AnalysisDisease ManagementFemaleHumansInfantMaleRural Population

Identifiers

PMID42743224
PMCPMC13577394

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.