GitHub repository: Amathdhari/Capstone-
Primary language: Jupyter Notebook
Created: 2022-07-10T11:58:14Z
Description: #Diabetes 130 US hospitals for years 1999–2008.  Diabetes is a chronic disease where a person suffers from an extended level of blood glucose in the body. Diabetes is affected by height, race, gender, age but a major reason is considered to be a sugar concentration. The present analysis of a large clinical database was undertaken to examine historical patterns of diabetes care in patients with diabetes admitted to a US hospital and to inform future directions which might lead to improvements in patient safety. Reducing early hospital readmissions is a policy priority aimed at improving healthcare quality. In this case study we will see how machine learning can help us solve the problems caused due to readmission.  It is estimated that 9.3% of the population in the United States have diabetes , 28% of which are undiagnosed. The 30-day readmission rate of diabetic patients is 14.4 to 22.7 % . Estimates of readmission rates beyond 30 days after hospital discharge are even higher, with over 26 % of diabetic patients being readmitted within 3 months and 30 % within 1 year. Costs associated with the hospitalization of diabetic patients in the USA were $124 billion, of which an estimated $25 billion was attributable to 30-day readmissions assuming a 20 % readmission rate. Therefore, reducing 30-day readmissions of patients with diabetes has the potential to greatly reduce healthcare costs while simultaneously improving care.