Analysis of Electronic Medical Records to Forecast Probable Disease Outbreaks in Bangladesh

Abstract

Electronic medical data repository system provides the research platform for interconnecting healthcare and fore-casting probable disease outbreak. It offers the opportunity to collect, organize and manage medical data for further usages. However, in an overpopulated country like Bangladesh, due to the lack of a centralized medical data repository and complex disease analysis, the prediction of the outbreak of deadly diseases (e.g., dengue fever) becomes difficult and time consuming. This paper attempts to describe a web-based development of a medical data repository system, named ‘Lifeline of Medical Data’ (LMD), aiming to improve the medical data storage system focusing on Bangladesh. It offers analysis on the data, particularly on usages of medicine data in a particular period or particular areas, and responds to epidemic outbreaks quickly. LMD extends multiple wings to collect, visualize and analyze diverse medicine usages through web and app-based profile creation and prescription generation of multiple stakeholders (e.g., patients, doctors, etc.). Moreover, it shows the possible impact in recurring disease outbreak prediction using the time series forecasting model, i.e., Autoregressive Integrated Moving Average (ARIMA). This paper also describes socio economic impact of this multi-functional web platform based on individual and national practice.