Using Data mining for Forecasting Public Healthcare Services in India: a case study of Punjab
DOI:
https://doi.org/10.26438/ijcse/v5i11.212216Keywords:
Big Data, HMIS, Data mining, KDD, OPD, IPD, Time SeriesAbstract
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.
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