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

Asihene, Philip

Boots, Mark

Brinkel, Johanna

Fobil, Julius N

Franke, Konstantin H

Kreuels, Benno

Krumkamp, Ralf

Marinovic, Axel Bonacic

May, Jürgen

Mohammed, Aliyu

Owusu-Dabo, Ellis

Sarpong, Nimako

BMC Medical Informatics and Decision Making

Abstract 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

Konstantin H. Franke

Ralf Krumkamp

Aliyu Mohammed

Nimako Sarpong

Ellis Owusu-Dabo

Johanna Brinkel

Julius N. Fobil

Axel Bonacic Marinovic

Philip Asihene

Mark Boots

Jürgen May

Benno Kreuels

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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

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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.

Franke KH, Krumkamp R, Mohammed A, et al. 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. BMC MEDICAL INFORMATICS AND DECISION MAKING. 2018;18(1): 23.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

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.

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