Empirical study on application of machine learning techniques for resource allocation in health care using KPI
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Data analysis plays an important role in the health sector of any government in predicting the health conditions of their people and take measures to improve the health of their people. In this article, we present the problems faced by the department of health and family welfare in collecting and analyzing data from various directorates of the government of Tamilnadu in India. We then propose a framework that can collect data from various directorates of the government and analyze the data collected to predict the resources needed by the hospital to better serve their patients. Logistic regression and decision trees were used to analyze the data collected from various directorates. Further, the data are researched to identify potholes in the healthcare system to improve the existing system. In addition, we used five key performance indicator measures to evaluate the outcomes.
KeywordsHealth informatics KPI Data mining Decision support systems Open source stack
The authors would like to thank the Government of Tamilnadu for providing healthcare data from different directorates and also thank Dr. Darez Ahamed IAS for his support and guidance.
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