A Guide for the Holistic Application of Data Analytics to Improve Management of Preeclampsia

One of the main causes of maternal and neonatal morbidity and mortality in the globe is preeclampsia. Because of its complex structure and variable clinical presentation, it is still difficult to diagnose and treat despite medical advancements. Data analytics provides a novel way to deal with these issues, enabling a deeper comprehension of the illness and better decision-making. Although data analysis is well established in medical statistics, to the best of our knowledge, only one study has combined all analytics in the context of preeclampsia and univariate time series. Thus, for those who are just starting to use data analytics in this and other diseases, this manuscript explores the holistic application of descriptive, diagnostic, predictive, and prescriptive analytical approaches in the context of preeclampsia, and not only in univariate time series. It also provides guidelines for the holistic application of data analytic approaches to improve the management of preeclampsia in Ecuador, mentioning its advantages and limitations.