Intelligent System for Predicting Healthcare Readmissions

Abstract

Hospitalization costs accrue a huge burden on the economy; thus, we need a hospital readmission system for predicting treatment costs associated with the patient admitted at the hospital. A novel prediction model for readmissions of patients suffering from disabilities and for patients with comorbidities that pose critical health risks thereby escalating healthcare costs and posing a threat on the survival of patients is highly recommended for patients at high risk of readmission to be proactive during treatment thereby reducing readmission cost. As per data of the National Health Protection Mission hospitalized between 2016 and 2022 in India, more than 9000 patients were readmitted and took treatment after a significant lapse. This chapter proposed a machine learning framework with all key elements of patients resulting discrimination ability and predicting financial analysis to estimate targeted patients thereby identifying risk factors, and a model was tested on an Indian government repository of healthcare dataset and achieved 97.9% correct prediction readmission in hospitals.