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Using big data to target preventable readmissions

By Joseph Conn Modern Healthcare August 2, 2014
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Since fall 2012, more than 14,000 patients admitted to one Texas hospital have had a computer program analyze their medical records to help clinicians predict what type of care would improve their outcomes.

The software used at 213-bed Texas Health Harris Methodist Hospital Hurst-Euless-Bedford scans each patient's electronic health record  within 24 hours of admission, looking at multiple data elements such as blood-pressure readings and blood-glucose levels.

“It takes all these pieces of data from the EHR, and it has an algorithm, and tells us which patient is at higher risk for heart failure,” said Dr. Susann Land, chief medical officer of the Bedford, Texas hospital. 

Armed with 30-day readmission risk scores for heart failure, the hospital is better able to target intensive follow-up care to those patients who need it most. Interventions include prompt callbacks, a follow-up consultation with a cardiologist, a talk with a social worker and the provision of educational materials. “We only have so many resources,” Land said. “We have to pick and choose which (patients) we manage more intensely.”

Read the full article here.