Evidence map›Paper›PMID 26063746›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2016

Innovating to enhance clinical data management using non-commercial and open source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya.

Timothy Tuti, Michael Bitok, Chris Paton, Boniface Makone, Lucas Malla, Naomi Muinga, David Gathara, Mike English

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
18.3field-weighted citation impact, top 1% 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

56 citing papers in PubMed, 93 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

8 authors at 3 institutions in 2 countries.

Timothy TutiKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya TTuti@kemri-wellcome.org.
Michael BitokKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya.
Chris PatonNuffield Department of Medicine, University of Oxford John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK.
Boniface MakoneKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya.
Lucas MallaKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya.
Naomi MuingaKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya.
David GatharaKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya.
Mike EnglishKEMRI-Wellcome Trust Research Programme, P. O. Box 43640 - 00100, Nairobi, Kenya Nuffield Department of Medicine, University of Oxford John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK.
Kenya Medical Research Institute · KEJohn Radcliffe Hospital · GBUniversity of Oxford · GB

Funding

Wellcome Trust 092654Wellcome Trust 097170
6 · The paper itself

Abstract

objectiveTo share approaches and innovations adopted to deliver a relatively inexpensive clinical data management (CDM) framework within a low-income setting that aims to deliver quality pediatric data useful for supporting research, strengthening the information culture and informing improvement efforts in local clinical practice. MATERIALS AND

methodsThe authors implemented a CDM framework to support a Clinical Information Network (CIN) using Research Electronic Data Capture (REDCap), a noncommercial software solution designed for rapid development and deployment of electronic data capture tools. It was used for collection of standardized data from case records of multiple hospitals' pediatric wards. R, an open-source statistical language, was used for data quality enhancement, analysis, and report generation for the hospitals.

resultsIn the first year of CIN, the authors have developed innovative solutions to support the implementation of a secure, rapid pediatric data collection system spanning 14 hospital sites with stringent data quality checks. Data have been collated on over 37 000 admission episodes, with considerable improvement in clinical documentation of admissions observed. Using meta-programming techniques in R, coupled with branching logic, randomization, data lookup, and Application Programming Interface (API) features offered by REDCap, CDM tasks were configured and automated to ensure quality data was delivered for clinical improvement and research use.

conclusionA low-cost clinically focused but geographically dispersed quality CDM (Clinical Data Management) in a long-term, multi-site, and real world context can be achieved and sustained and challenges can be overcome through thoughtful design and implementation of open-source tools for handling data and supporting research.

Indexed as

Biomedical ResearchPediatricsSoftwareChildClinical Trials as TopicData CollectionHospitalizationHumansInformation Storage and RetrievalKenyaOwnershipclinical data managementclinical researchmetaprogrammingopen sourcequality assurance

Identifiers

PMID26063746
PMCPMC4681113
OpenAlexW2169168708

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.