Evidence map›Paper›PMID 33758014›Full record

ReviewBMJ global health2021

Employing learning health system principles to advance research on severe neonatal and paediatric illness in Kenya.

Mike English, Grace Irimu, Samuel Akech, Jalemba Aluvaala, Morris Ogero, Lynda Isaaka, Lucas Malla, Timothy Tuti, David Gathara, Jacquie Oliwa and 1 more

Open access · goldAbstract readReview
In one paragraph

Review in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
11.8field-weighted citation impact, top 2% of its field
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

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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

11 authors at 2 institutions in 3 countries.

Mike EnglishHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya MEnglish@kemri-wellcome.org.ORCID 0000-0002-7427-0826
Grace IrimuHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Samuel AkechHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Jalemba AluvaalaHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.ORCID 0000-0002-0851-3711
Morris OgeroHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Lynda IsaakaHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Lucas MallaHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Timothy TutiHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.ORCID 0000-0002-7915-3004
David GatharaHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Jacquie OliwaHealth Services Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.
Ambrose AgweyuEpidemiology and Demography, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.ORCID 0000-0001-8760-1279
Kenya Medical Research Institute · KEUniversity of Nairobi · KE

Funding

Medical Research Council MR/R006083/1Wellcome Trust 092654Wellcome Trust 097170Wellcome Trust 207522Wellcome Trust 207522/Z/17/Z
6 · The paper itself

Abstract

We have worked to develop a Clinical Information Network (CIN) in Kenya as an early form of learning health systems (LHS) focused on paediatric and neonatal care that now spans 22 hospitals. CIN's aim was to examine important outcomes of hospitalisation at scale, identify and ultimately solve practical problems of service delivery, drive improvements in quality and test interventions. By including multiple routine settings in research, we aimed to promote generalisability of findings and demonstrate potential efficiencies derived from LHS. We illustrate the nature and range of research CIN has supported over the past 7 years as a form of LHS. Clinically, this has largely focused on common, serious paediatric illnesses such as pneumonia, malaria and diarrhoea with dehydration with recent extensions to neonatal illnesses. CIN also enables examination of the quality of care, for example that provided to children with severe malnutrition and the challenges encountered in routine settings in adopting simple technologies (pulse oximetry) and more advanced diagnostics (eg, Xpert MTB/RIF). Although regular feedback to hospitals has been associated with some improvements in quality data continue to highlight system challenges that undermine provision of basic, quality care (eg, poor access to blood glucose testing and routine microbiology). These challenges include those associated with increased mortality risk (eg, delays in blood transfusion). Using the same data the CIN platform has enabled conduct of randomised trials and supports malaria vaccine and most recently COVID-19 surveillance. Employing LHS principles has meant engaging front-line workers, clinical managers and national stakeholders throughout. Our experience suggests LHS can be developed in low and middle-income countries that efficiently enable contextually appropriate research and contribute to strengthening of health services and research systems.

Indexed as

Health Services ResearchQuality ImprovementChildChild Health ServicesChild, PreschoolCOVID-19Delivery of Health CareDeveloping CountriesDiarrheaHealth Services AccessibilityHumansInfantInfant, NewbornKenyaMalariaPandemicschild healthhealth services researchhealth systems evaluationpaediatrics

Identifiers

PMID33758014
PMCPMC7993294
OpenAlexW3137152387

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.