Hospital Readmission and Machine Learning

 

Before delving into the specific Machine Learning Applications, it’s also crucial to look into why a project would be needed in this area.

As mentioned previously, the variations in early signs and symptoms make CHD harder to recognize. As such, it’s essential to look into preventative rather than reactive measures. In addition, looking into a patient’s risk factors and using them to determine whether they would be at risk of CHD in the next decade allows significant room for lifestyle changes.

 

Hospital Readmission is when a patient is discharged from the hospital and readmitted in a short span. This process can be expensive and potentially harmful to patients when they go through it multiple times. Like CHD, the risk of a patient’s readmission can be reduced with accurate prediction. Just as with CHD prediction, Hospital Readmission has risk factors that contribute to the span in which a patient is readmitted as well as the length of that readmission

​

Currently, there has been very little work on hospital readmission prediction, especially pertaining to CHD or merging other datasets.​

​

Many of these risk factors can be improved with lifestyle changes, necessitating early prediction.