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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

机译:用于识别加纳儿童常见疾病症状的基于手机的工具:综合研究中综合临床算法的开发和评估

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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. 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. 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%). The algorithm-based tool achieved reliable symptom detection and treatment recommendations were administered conformably to the physicians’ assessment. Testing in domestic environment is envisaged.
机译:这项研究的目的是开发和评估一种适用于手机的基于算法的诊断工具,以支持监护人为患病的儿童提供适当的护理。该算法是根据儿童疾病综合管理(IMCI)指南开发的,并在加纳的一家医院进行了评估。 237名监护人使用了该工具来评估孩子的症状。该工具记录的数据和医师完成的健康记录在症状检测,疾病评估和治疗建议方面进行了比较。为了比较两种评估,计算了Kappa统计数据和预测值。该工具检测到咳嗽,发烧,腹泻和呕吐的症状,与医生的发现非常吻合(kappa =?0.64; 0.59; 0.57和0.42)。疾病评估几乎与医师的发现不符。该工具的治疗建议与237例病例中的93例与医生的评估相关(同意率为39.2%,kappa =?0.11),但只有7例(3.0%)低估了儿童的状况。基于算法的工具可实现可靠的症状检测,并根据医师的评估对治疗建议进行了管理。设想在家庭环境中进行测试。

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