Tools & Strategies News

Predictive Analytics Use EHR Data for Hospital Readmissions

Researchers have developed a suite of predictive analytics tools to reliably identify all-cause 30-day pediatric readmission risk before hospital discharge.

Two hands on a red background, one adult and one child. The adult's hand is white, and is holding the child's hand, which is red

Source: Getty Images

By Shania Kennedy

- In a new study published last week in JAMA Network Open, researchers found that a suite of predictive analytics tools leveraging readily available EHR data can accurately identify all-cause 30-day readmission risk for pediatric patients prior to hospital discharge.

The study authors noted that despite the fact that hospital readmission is widely used as a quality care measure and that models to predict adult readmission exist, there are no such tools to predict risk of pediatric hospital readmission.

To address this gap, researchers set out to develop and validate a tool identifying pediatric patients before hospital discharge who are at risk for all-cause 30-day subsequent readmission. To do so, they leveraged EHR-derived data from admissions at Ann & Robert H. Lurie Children’s Hospital of Chicago (LCH) from January 1, 2016, to December 31, 2019.