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A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study

BACKGROUND: The aim of this study was the development and evaluation of an algorithm-based diagnosis-tool, applicable on mobile phones, to support guardians in providing appropriate care to sick children. METHODS: The algorithm was developed on the basis of the Integrated Management of Childhood Ill...

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Autores principales: Franke, Konstantin H., Krumkamp, Ralf, Mohammed, Aliyu, Sarpong, Nimako, Owusu-Dabo, Ellis, Brinkel, Johanna, Fobil, Julius N., Marinovic, Axel Bonacic, Asihene, Philip, Boots, Mark, May, Jürgen, Kreuels, Benno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870385/
https://www.ncbi.nlm.nih.gov/pubmed/29580278
http://dx.doi.org/10.1186/s12911-018-0600-3
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author Franke, Konstantin H.
Krumkamp, Ralf
Mohammed, Aliyu
Sarpong, Nimako
Owusu-Dabo, Ellis
Brinkel, Johanna
Fobil, Julius N.
Marinovic, Axel Bonacic
Asihene, Philip
Boots, Mark
May, Jürgen
Kreuels, Benno
author_facet Franke, Konstantin H.
Krumkamp, Ralf
Mohammed, Aliyu
Sarpong, Nimako
Owusu-Dabo, Ellis
Brinkel, Johanna
Fobil, Julius N.
Marinovic, Axel Bonacic
Asihene, Philip
Boots, Mark
May, Jürgen
Kreuels, Benno
author_sort Franke, Konstantin H.
collection PubMed
description BACKGROUND: The aim of this study was the development and evaluation of an algorithm-based diagnosis-tool, applicable on mobile phones, to support guardians in providing appropriate care to sick children. METHODS: The algorithm was developed on the basis of the Integrated Management of Childhood Illness (IMCI) guidelines and evaluated at a hospital in Ghana. Two hundred and thirty-seven guardians applied the tool to assess their child’s symptoms. Data recorded by the tool and health records completed by a physician were compared in terms of symptom detection, disease assessment and treatment recommendation. To compare both assessments, Kappa statistics and predictive values were calculated. RESULTS: The tool detected the symptoms of cough, fever, diarrhoea and vomiting with good agreement to the physicians’ findings (kappa = 0.64; 0.59; 0.57 and 0.42 respectively). The disease assessment barely coincided with the physicians’ findings. The tool’s treatment recommendation correlated with the physicians’ assessments in 93 out of 237 cases (39.2% agreement, kappa = 0.11), but underestimated a child’s condition in only seven cases (3.0%). CONCLUSIONS: The algorithm-based tool achieved reliable symptom detection and treatment recommendations were administered conformably to the physicians’ assessment. Testing in domestic environment is envisaged. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-018-0600-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-58703852018-03-29 A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study Franke, Konstantin H. Krumkamp, Ralf Mohammed, Aliyu Sarpong, Nimako Owusu-Dabo, Ellis Brinkel, Johanna Fobil, Julius N. Marinovic, Axel Bonacic Asihene, Philip Boots, Mark May, Jürgen Kreuels, Benno BMC Med Inform Decis Mak Research Article BACKGROUND: The aim of this study was the development and evaluation of an algorithm-based diagnosis-tool, applicable on mobile phones, to support guardians in providing appropriate care to sick children. METHODS: The algorithm was developed on the basis of the Integrated Management of Childhood Illness (IMCI) guidelines and evaluated at a hospital in Ghana. Two hundred and thirty-seven guardians applied the tool to assess their child’s symptoms. Data recorded by the tool and health records completed by a physician were compared in terms of symptom detection, disease assessment and treatment recommendation. To compare both assessments, Kappa statistics and predictive values were calculated. RESULTS: The tool detected the symptoms of cough, fever, diarrhoea and vomiting with good agreement to the physicians’ findings (kappa = 0.64; 0.59; 0.57 and 0.42 respectively). The disease assessment barely coincided with the physicians’ findings. The tool’s treatment recommendation correlated with the physicians’ assessments in 93 out of 237 cases (39.2% agreement, kappa = 0.11), but underestimated a child’s condition in only seven cases (3.0%). CONCLUSIONS: The algorithm-based tool achieved reliable symptom detection and treatment recommendations were administered conformably to the physicians’ assessment. Testing in domestic environment is envisaged. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-018-0600-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-27 /pmc/articles/PMC5870385/ /pubmed/29580278 http://dx.doi.org/10.1186/s12911-018-0600-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Franke, Konstantin H.
Krumkamp, Ralf
Mohammed, Aliyu
Sarpong, Nimako
Owusu-Dabo, Ellis
Brinkel, Johanna
Fobil, Julius N.
Marinovic, Axel Bonacic
Asihene, Philip
Boots, Mark
May, Jürgen
Kreuels, Benno
A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title_full A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title_fullStr A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title_full_unstemmed A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title_short A mobile phone based tool to identify symptoms of common childhood diseases in Ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
title_sort mobile phone based tool to identify symptoms of common childhood diseases in ghana: development and evaluation of the integrated clinical algorithm in a cross-sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870385/
https://www.ncbi.nlm.nih.gov/pubmed/29580278
http://dx.doi.org/10.1186/s12911-018-0600-3
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