Outpatient Readmission in Rheumatology: A Machine Learning Predictive Model of Patient's Return to the Clinic.

ABSTRACT: Our objective is to develop and validate a predictive model based on the random forest algorithm to estimate the readmission risk to an outpatient rheumatology clinic after discharge. We included patients from the Hospital Clínico San Carlos rheumatology outpatient clinic, from 1 April 2007 to 30 November 2016, and followed-up until 30 November 2017. Only readmissions between 2 and 12 months after the discharge were analyzed. Discharge episodes were chronologically split into training, validation, and test datasets. Clinical and demographic variables (diagnoses, treatments, quality of life (QoL), and comorbidities) were used as predictors. Models were developed in the training dataset, using a grid search approach, and performance was compared using the area under the receiver operating ch

SUBMITTER: Madrid-Garcia A 

PROVIDER: S-EPMC6723392 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature