TY - JOUR
T1 - A mobile phone based tool to identify symptoms of common childhood diseases in Ghana
T2 - Development and evaluation of the integrated clinical algorithm in a cross-sectional study
AU - Franke, Konstantin H.
AU - Krumkamp, Ralf
AU - Mohammed, Aliyu
AU - Sarpong, Nimako
AU - Owusu-Dabo, Ellis
AU - Brinkel, Johanna
AU - Fobil, Julius N.
AU - Marinovic, Axel Bonacic
AU - Asihene, Philip
AU - Boots, Mark
AU - May, Jürgen
AU - Kreuels, Benno
N1 - Publisher Copyright:
© 2018 The Author(s).
PY - 2018/3/27
Y1 - 2018/3/27
N2 - 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.
AB - 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.
KW - Africa
KW - Algorithm
KW - Children
KW - Decision making, computer assisted
KW - Interactive voice response
KW - mHealth
KW - Symptom assessment
UR - http://www.scopus.com/inward/record.url?scp=85045222754&partnerID=8YFLogxK
U2 - 10.1186/s12911-018-0600-3
DO - 10.1186/s12911-018-0600-3
M3 - Article
C2 - 29580278
AN - SCOPUS:85045222754
SN - 1472-6947
VL - 18
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
IS - 1
M1 - 23
ER -