Abstract
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.
Highlights
The mortality rate due to Non-communicable diseases (NCDs) is increasing and 75% of Indians in rural villages are the victims of non-communicable diseases (NCD) such as Diabetes, Hypertension and Obesity which represent global burden of diseases and cause deaths each year mainly in rural areas [1]
Data warehouse has been defined by Bill Inmon as a subjectoriented which can be used to analyze a particular subject area, integrated which integrates data from multiple sources, time-variant which enables to retrieve historical data and non-volatile collection of data in support of management's decision making process [4]
Data warehouse provides an effective way of analysis and statistics to the huge amount of data and helps in decision making
Summary
The mortality rate due to Non-communicable diseases (NCDs) is increasing and 75% of Indians in rural villages are the victims of NCDs such as Diabetes, Hypertension and Obesity which represent global burden of diseases and cause deaths each year mainly in rural areas [1] This is in turn affecting the economic conditions of the people. Data warehouse has been defined by Bill Inmon as a subjectoriented which can be used to analyze a particular subject area, integrated which integrates data from multiple sources, time-variant which enables to retrieve historical data and non-volatile collection of data in support of management's decision making process [4]. The bottleneck for all these programs has been the acute shortage of specialists and experts to screen analyze and report [8].The analysis of the data collected is manually done by Community medicine personnel and reports are generated
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