Volume : V, Issue : IX, September - 2016

Predicting patient readmissions within 30 days

Niranjan Singh, Y. S Kumaraswamy

Abstract :

 Readmissions of patients within 30 days of discharge cost millions of dollars of tax payers’ money and pose a significant challenge to the quality of healthcare service providers. In order to mitigate the problem posed by unwanted readmissions of patients for the same diagnosis and to increase the quality of healthcare services we seek to develop machine learning models to predict patients who are likely to get readmitted within 30 days of discharge. This research paper describes the methodologies used to build the predictive models for predicting the likelihood of patients getting readmitted within 30 days of discharge. The work presented here provides the process to build various predictive models for predicting the likelihood of patients getting readmitted and in the process compare the accuracies of the various predictive models side by side and provide ways to improve the accuracies of the various predictive models .This paper further seeks to provide insights into the variables or the predictors which contribute the most in predicting the target variable

Keywords :

Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Niranjan Singh, Y.S Kumaraswamy Predicting patient readmissions within 30 days International Journal of Scientific Research,Volume : 5 | Issue : 9 |September 2016

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