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Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab

Parveen Singh1 , Vibhakar Mansotra2

  1. Department of Computer Science and IT, University of Jammu, Jammu, India.
  2. Department of Computer Science and IT, University of Jammu, Jammu, India.

Correspondence should be addressed to: imparveen@yahoo.com .

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-11 , Page no. 212-216, Nov-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i11.212216

Online published on Nov 30, 2017

Copyright © Parveen Singh, Vibhakar Mansotra . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Parveen Singh, Vibhakar Mansotra, “Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.11, pp.212-216, 2017.

MLA Style Citation: Parveen Singh, Vibhakar Mansotra "Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab." International Journal of Computer Sciences and Engineering 5.11 (2017): 212-216.

APA Style Citation: Parveen Singh, Vibhakar Mansotra, (2017). Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab. International Journal of Computer Sciences and Engineering, 5(11), 212-216.

BibTex Style Citation:
@article{Singh_2017,
author = {Parveen Singh, Vibhakar Mansotra},
title = {Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2017},
volume = {5},
Issue = {11},
month = {11},
year = {2017},
issn = {2347-2693},
pages = {212-216},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1568},
doi = {https://doi.org/10.26438/ijcse/v5i11.212216}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i11.212216}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1568
TI - Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab
T2 - International Journal of Computer Sciences and Engineering
AU - Parveen Singh, Vibhakar Mansotra
PY - 2017
DA - 2017/11/30
PB - IJCSE, Indore, INDIA
SP - 212-216
IS - 11
VL - 5
SN - 2347-2693
ER -

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Abstract

A big benefit of using data mining and knowledge management techniques is to create a dynamic knowledge rich health care environment. The application of Knowledge Discovery in Databases (KDD) can be done by skilled employees with good knowledge of health care industry. Thus, meaningful patterns and strategic solutions can be developed while working with massive quantities of data which can help to improve the quality of healthcare services offered to patients. This function is particularly useful for Insurance companies, Physicians, Pharmaceutical companies and by the Government health planners and management personals for the formulation of effective policies. However, there are a many issues that arise while dealing with such massive data, especially how this data can be analyzed in a reliable manner. The basic aim of Health Informatics is to take medical data from the real world and from all levels of human existence to help advance our understanding of health care facilities, medicine and medical practices. In this paper, we explored the Health care data of one of the Northern State of India, Punjab, available with HMIS database, using Big Data tools and approaches, which help in answering several critical questions with respect to healthcare facilities, for effective utilization and policy formulation of resources available. Data of Indoor Patient Department (IPD) and Outdoor Patient Department (OPD) from 2010 to 2017 has been used to forecast the number of patients in advance for coming years, taking into consideration most efficient model based on the accuracy of the forecasts, so that the planning is done well in advance for providing better health care facilities for the forthcoming patients.

Key-Words / Index Term

Big Data, HMIS, Data mining, KDD, OPD, IPD, Time Series

References

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