Prediction of 30-Day Hospital Readmissions for All-Cause Dental Conditions using Machine Learning.
Man HungWei LiEric S HonSharon SuWeicong SuYao HeXiaoming ShengRichard HolubkovMartin S LipskyPublished in: Risk management and healthcare policy (2020)
Our results demonstrate that readmission after hospitalization with ACDC is fairly common. If one-third of the 30-day readmission cases can be avoided, there is a potential annual saving of over $25 million among the twenty-one states represented in the NRD. The ML algorithms can predict hospital readmission in dental patients and should be further tested to aid the reduction of hospital readmission and enhancement of patient-centered care.