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Arch Dis Child ; 105(1): 32-39, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31362946

RESUMO

BACKGROUND: Scaling up improved management of severe acute malnutrition (SAM) has been identified as the nutrition intervention with the greatest potential to reduce child mortality but it requires improved operational capacity. OBJECTIVE: To investigate whether an eLearning course, which can be used at scale in resource-poor countries, leads to improved diagnosis, clinical management and survival of children with SAM. DESIGN: A 2-year preintervention and postintervention study between January 2015 and February 2017. SETTING: Eleven healthcare facilities: nine in Ghana, one in Guatemala, and one in El Salvador. INTERVENTION: Scenario-based eLearning course 'Caring for infants and young children with severe malnutrition'. MAIN OUTCOME MEASURES: Identification of children with SAM, quality of care, case-fatality rate. METHODS: Medical record reviews of children aged 0-60 months attending eleven hospitals between August 2014 and July 2016, observations in paediatric wards, and interviews with senior hospital personnel. RESULTS: Postintervention there was a significant improvement in the identification of SAM: more children had the requisite anthropometric data (34.9% (1300/3723) vs 15.9% (629/3953)) and more were correctly diagnosed (58.5% (460/786) vs 47.1% (209/444)). Improvements were observed in almost all aspects of the WHO 'Ten Steps' of case-management, and case-fatality fell from 5.8% (26/449) to 1.9% (14/745) (Post-pre difference=-3.9%, 95% CI -6.6 to -1.7, p<0.001). CONCLUSIONS: High quality, interactive eLearning can be an effective intervention in scaling up capacity building of health professionals to manage SAM effectively, leading to a reduction in mortality.


Assuntos
Transtornos da Nutrição Infantil/terapia , Instrução por Computador , Melhoria de Qualidade , Fortalecimento Institucional/métodos , Transtornos da Nutrição Infantil/diagnóstico , Transtornos da Nutrição Infantil/mortalidade , Pré-Escolar , Instrução por Computador/métodos , El Salvador/epidemiologia , Gana/epidemiologia , Guatemala/epidemiologia , Política de Saúde , Humanos , Lactente , Melhoria de Qualidade/organização & administração , Melhoria de Qualidade/estatística & dados numéricos , Qualidade da Assistência à Saúde , Resultado do Tratamento
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