An Optimized Data Management Model for Maternal Mortality in Bayelsa State

Abstract

Maternal Mortality Rate (MMR) is the quantity of maternal deaths in a given duration per 100,000 of reproductive aged (15-49) women. This amounts to both the obstetric risk and the rate of recurrence at which women are unprotected to this risk. In Bayelsa State, the maternal mortality has high rates. The driving reasons for death are related with hypertensive disorder, severe bleeding, infection and other complications of delivery that could be avoided. This research aims to develop a maternal mortality system using Data mining techniques; estimation of maternal mortality rate in Otuasega Cottage Hospital in Ogbia Local Government Area in Bayelsa State was carried out by analyzing the causes of death during pregnancy; Naive Bayes was used in Bayes Server to classify Hypertensive diseases into preeclampsia and gestational, identifying the symptoms and risk factors. Among other causes of maternal death evaluated, Hypertensive disease was the highest cause of maternal death in Bayelsa State between 2012 to 2018. We developed a Bayesian maternal mortality estimation model, that catches increasing speeds and deceleration in the rate of progress in the maternal death rate. Result shows that the trend was as low as 2 maternal deaths in every 202 live births in 2012 but increased to 12 per 210 live births in 2016. The maternal mortality rate continued its upward trend and increased to 14 deaths per 172 live births in the year 2018. Maternal mortality rate which was very low have increased significantly, and most death were caused by Hypertensive, followed by bleeding, complications and little of infections.

Keywords: Naïve Bayes, Bayesian Estimation Model, Maternal Mortality

DOI: 10.7176/CEIS/10-5-02

Publication date:June 30^th 2019