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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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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. |
format | Online Article Text |
id | pubmed-5870385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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