International Journal of Preventive Medicine Research Vol. 1, No. 5, 2015, pp. 270-275 http://www.aiscience.org/journal/ijpmr ISSN: 2381-7038 (Print); ISSN: 2381-7046 (Online) * Corresponding author E-mail address: Xcarol.hargreaves@nus.edu.sg (C. A. Hargreaves) A Neonatal Mortality Risk Modelling Scoring System Carol Anne Hargreaves 1, * , Hoang Long Ngoc Nguyen 1 , Claudia Turner 2 , Leakhena Neou 3 , Sreymom Pol 2 1 Business Analytics, Institute of Systems Science, National University of Singapore, Singapore, Singapore 2 Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia 3 Neonatal Unit, Angkor Hospital for Children, Siem Reap, Cambodia Abstract Infections are the commonest cause of death in infants less than four weeks old. Treatment, in a neonate with signs of sepsis needs to be initiated as soon as possible, before the causative organism is known. In the developed world neonatal severity scores have been created to estimate the risk of a neonate having a poor outcome. These scores rely on biochemical and haematological parameters which are often unavailable in the developing world. The objective of this study is to derive a mortality severity score for neonates who live in developing countries. The neonate mortality risk score is based on clinical signs that predict the likelihood of death. Neonatal patient risk models are built applying two popular methodologies: Logistics Regression and Decision Tree. Input variables that were used in established models in literature was selected to build the neonatal mortality risk modelling scoring system. Important factors that contributed to the resulting neonatal mortality risk score was birth weight, temperature, heart rate and seizure. Model accuracy was at least 85% amongst all models built. Keywords Neonatal, Mortality Risk, Severity Score, Patient Risk Model, Sepsis, Infections Received: November 10, 2015 / Accepted: November 22, 2015 / Published online: December 14, 2015 @ 2015 The Authors. Published by American Institute of Science. This Open Access article is under the CC BY-NC license. http://creativecommons.org/licenses/by-nc/4.0/ 1. Introduction Neonatal mortality is increasingly recognized as an important global public health challenge that must be addressed if we are to reduce child health disparities between rich and poor countries [14]. There are many situations when a clinician, parent, nurse, manager, or researcher may wish to quantify the morbidity of a neonate. Poverty is an underlying cause of many neonatal deaths, either through increasing the prevalence of risk factors such as maternal infection, or through reducing access to effective care. However, poverty is not just a problem in poor countries. Results of a Canadian study [3] suggest a disparity in stillbirths and neonatal deaths between the richest and poorest 20% of the population that has persisted for almost 20 years. Further, Demographic and Health Survey (DHS) data from 20 countries in sub-Saharan Africa and three large countries in south Asia reveal consistently higher Neonatal Mortality Rate (NMR) for those in the poorest 20% of households than for those in the top quintile. Most of the estimated 4 million neonatal deaths per year occur in low and middle income countries. Three conditions: infection, birth asphyxia, and consequences of premature birth/low birth weight, are responsible for majority of these deaths. More than one-third are estimated to be due to severe infections, and a quarter are due to the clinical syndrome of neonatal sepsis/pneumonia. Case fatality rates for neonatal infections remain high among both hospitalized newborns and those in the community [15].