Data Analytics and Operational Data Integration to reach out to Rural Masses for Early Detection of Non-communicable DiseasesVanishri Arun1*, Shyam V2 and Padma SK1
- Corresponding Author:
- Vanishri Arun
Department of Information Science and Engineering
Sri Jayachamarajendra College of Engineering
E-mail: [email protected]
Received date: October 06, 2015; Accepted date: November 06, 2015; Published date: November 13, 2015
Citation: Arun V, Shyam V, Padma SK (2015) Data Analytics and Operational Data Integration to reach out to Rural Masses for Early Detection of Non-communicable Diseases. Primary Health Care 5:210. doi:10.4172/2167-1079.1000210
Copyright: © 2015 Arun V, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
This paper demonstrates the analysis of healthcare data and integration of operational data to abate the prevalence incidence of non-communicable diseases (NCD). Pilot experiments have been carried out in Suttur village, by screening the masses for early detection of NCDs. An app has been developed to record patient profile onto a tablet. The record is synchronized to update the database on the cloud where the repository is maintained. This provides an efficient way of analysis and statistics to the huge amount of health data. ETL (Extract, Transform and Load) is a process used to extract data from data repository and transform the data based on user requirements and store in a target database as a single repository which helps to achieve goals proactively and on time. The main aim of this paper is to generate reports from the collection of health data by using tools like QlikView for Business Objects as a front end tool for generation of reports and charts, Oracle 11g as backend tool for creation of data repository and Talend Open Studio 5.4 as an ETL tool. We conclude that ETL systems enable a smooth migration from one system to another. By creating an ETL script for each system, data can be stored in a consistent format in the repository. The source system can then be changed, without any impact on the repository or the reporting/analysis systems. Therefore there are phenomenal improvements in turnaround time for data access and reporting. The entire health data can be standardized as there will be one view of information. Health data synced by various sources from different places can be merged to create a more comprehensive information source. This leads to reduction in costs to create and distribute information and reports and also helps in reduction of prevalence incidence of NCDs.