Artificial Intelligence Triggers Fast, Lifesaving Care for COVID-19 Patients

“This is helping save lives. The model predicts which patients are getting worse and will need more care. It shows us if things are changing rapidly,” said Dr. Daniel David, Clinical Professor of Medicine at Confluence Health, an integrated healthcare organization serving North Central Washington.

Hundreds of hospitals are using the predictive model. It evaluates patients’ risk of getting sicker in real time by tracking thousands of pieces of data generated by heart rate, blood pressure, temperature, and other monitors. The model helps clinicians by rapidly analyzing data from these sources and notifying staff if things are getting worse. Notifications are displayed on screen, included in reporting dashboards, or pushed out to clinicians’ smartphones.

“Frontline healthcare workers are busy caring for patients. By keeping a watchful eye, the system helps clinicians direct their attention to patients who need it most,” said Seth Hain, Epic data scientist and Senior Vice President of Research and Development.

Epic has enlisted research organizations like Stanford Health Care to validate the model for COVID-19. Many organizations, such as Confluence Health, have completed validation and are already using it for these patients.

The predictive model is one of many analytics tools Epic and its customers are bringing to the fight against COVID-19. Another tool, SlicerDicer allows doctors to combine and sort through data in different ways. For example, if a doctor suspects that there is a COVID-19 hotspot in her community, she can verify it by using the system to cross-reference positive tests with patient ZIP Codes. She can then alert public health officials.

Epic is also working with its customers to find an easy way to get the right data to public health officials in order to help them understand and limit the spread of the pandemic.