Predicting Future Hospitalizations

Some patient visits, either to the emergency room (ER) or in-patient admissions, could be prevented through timely outpatient interventions by healthcare providers. By identifying such situations early, we can not only improve a patient’s end outcomes and quality of life, but significantly reduce healthcare resource utilization and the high costs associated with such visits. Working with UCLA’s Faculty Practice Group (FPG), we have developed new predictive models from the electronic health record (EHR) to identify those patients who are at high risk for admission within the next year. Based on this risk prediction, UCLA healthcare providers and staff reach out periodically to check on the individual and provide guidance and monitoring to prevent subsequent healthcare issues that will result in the need for admission. Being deployed across UCLA’s primary care clinics, this new risk assessment tool is being consider for broader adoption across the entire UC Health system.