Predicting 30-day readmissions in pneumonia patients using machine learning and residential greenness

We constructed prediction models for 30-day readmission of patients with pneumonia by incorporating residential greenness as a risk factor. The models demonstrated sufficient performance, and residential greenness was significant in predicting readmission. Incorporating residential greenness into the identification of groups at high risk for readmission can complement the possible loss of information when using data from electronic health records.