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Kenya Health Information Systems and Confidential Enquiry Datasets to Analyse Facility-Based Maternal Mortality and Develop Models to Improve Quality Childbirth Care

Sikolia Wanyonyi of Aga Khan University in Kenya will analyze datasets on maternal mortality during hospital deliveries to determine the causes and to develop prediction models to help identify effective interventions in specific settings. Maternal mortality rates in Kenya are only slowly reducing, despite the increase in hospital deliveries, which may be due to a combination of different factors such as the quality of care and clinical characteristics. They have assembled available data from the Kenyan Ministry of Health for different counties over the last five years and will apply a hierarchical Bayesian model to identify the trends and their causes. They will also fit so-called generalizable estimating equations to the data to determine whether the risk of maternal mortality can be predicted from combinations of specific types of data, such as socio-demographic, which could be used to identify high-risk patients for more timely treatments.

More information about Data Science Approaches to Improve Maternal and Child Health in Africa

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