Abstract: A readmission risk prediction model is generated and used for identifying patients having elevated risk of readmission and determining inpatient treatment and outpatient activities based on readmission risk. Readmission risk prediction models may be generated for a variety of different clinical conditions using logistic regression techniques. When a patient is admitted to a hospital, the patient's condition is identified and a corresponding readmission risk prediction model is employed to identify the patient's risk of readmission. The readmission risk may be presented to a clinician and employed to recommend interventions intended to treat the patient and reduce the probability of readmission for the patient. The patient's readmission risk may also be calculated after the patient has been discharged and used for planning outpatient activities for the patient.

Abstract: A readmission risk prediction model is generated and used for identifying patients having elevated risk of readmission and determining inpatient treatment and outpatient activities based on readmission risk. Readmission risk prediction models may be generated for a variety of different clinical conditions using logistic regression techniques. When a patient is admitted to a hospital, the patient's condition is identified and a corresponding readmission risk prediction model is employed to identify the patient's risk of readmission. The readmission risk may be presented to a clinician and employed to recommend interventions intended to treat the patient and reduce the probability of readmission for the patient. The patient's readmission risk may also be calculated after the patient has been discharged and used for planning outpatient activities for the patient.