Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/339435
Title: Decision support system in health care analytics using key performance indicator
Researcher: Skylakha, S
Guide(s): Sakthivel, P
Keywords: Engineering and Technology
Computer Science
Computer Science Information Systems
University: Anna University
Completed Date: 2020
Abstract: The Health Care System is undergoing a sea change with its focus being to change the life style of individuals in order to prevent diseases, so that, they have a longer life. To achieve this objective, it has become very important to effectively manage the Health Care Data which has thrown a challenge to the Health Care Organizations. The role of Data Analytical tools is very important to effectively manage the voluminous health data in order to improve the health care, to assist disease care prediction and to optimize the cost involved. In the above said context, the Government of Tamilnadu has started storage of health data in digital form from the year 1996 which was used for preparing Monthly and Annual Reports. These data were stored by various Directorates functioning under the Health Department of Government of Tamilnadu. The most important lacunae in this form of storage was that there was only vertical integration of data within the Directorates and there was no horizontal integration of data across the various Directorates of the Health Department. This has lead to a situation, where the Department was not in a position to have a holistic view of health care in the absence of integration of data among the various Directorates. This research study proposed to make an attempt for data integration of various Directorates of the Health Department of the Government of Tamilnadu. To make a beginning, out of the 21 Directorates functioning under the Health Department, data have been obtained from 4 Directorates viz. Directorate of Public Health and Preventive Medicine CMCHIS TN (Chief Minister s Comprehensive Health Insurance Scheme Tamilnadu) Directorate of Medical and Rural Health Services 108 (Emergency Ambulance Service) The study proposes to design a Data Warehouse wherein, the data from this four Directorates are to be integrated and analyzed for generation of outputs which will provide real-time information to the Directorates for taking quick decisions and also formulating policies with a future prospective. It is proposed to use data integration tool, Pentaho in order to transform the raw data obtained from the Directorates and to improve its quality and to load the data in the Data Warehouse in Rows and Columns. The study also proposes to use the PostgreSQL data base which is a relational data base which consist of Data Marts and which facilitates Multi Dimensional Analysis. The study also proposes to use the Business Intelligence Tool Tableau and Statistical Tool R for analysis of the data in order to generate reports and charts which provide insight to the trends relating to various health issues which is proposed to be taken as Case Studies in the research work. Based on the results of the research work, it is proposed to integrate the data of the remaining 17 Directorates, so that real-time information is available in respect of all health related issues to the Health Department in order to ensure the goal of healthy life to the entire population of the State of Tamilnad newline
Pagination: xviii,135 p.
URI: http://hdl.handle.net/10603/339435
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File28.01 kBAdobe PDFView/Open
02_certificates.pdf133.21 kBAdobe PDFView/Open
03_vivaproceedings.pdf284.91 kBAdobe PDFView/Open
04_bonafidecertificate.pdf228.7 kBAdobe PDFView/Open
05_abstracts.pdf140.88 kBAdobe PDFView/Open
06_acknowledgements.pdf214.59 kBAdobe PDFView/Open
07_contents.pdf136.1 kBAdobe PDFView/Open
08_listoftables.pdf129.3 kBAdobe PDFView/Open
09_listoffigures.pdf129.42 kBAdobe PDFView/Open
10_listofabbreviations.pdf126.24 kBAdobe PDFView/Open
11_chapter1.pdf191.41 kBAdobe PDFView/Open
12_chapter2.pdf256.9 kBAdobe PDFView/Open
13_chapter3.pdf344.53 kBAdobe PDFView/Open
14_chapter4.pdf869.66 kBAdobe PDFView/Open
15_chapter5.pdf1.66 MBAdobe PDFView/Open
16_conclusion.pdf155.54 kBAdobe PDFView/Open
17_references.pdf168.62 kBAdobe PDFView/Open
18_listofpublications.pdf126.63 kBAdobe PDFView/Open
80_recommendation.pdf112 kBAdobe PDFView/Open
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