Epic has launched a COVID-19 risk prediction model designed by Cleveland Clinic researchers, according to a news release from the software company.
The tool was developed and tested using clinical data from more than 11,000 Cleveland Clinic patients, the model uses information from patients’ comprehensive health records combined with patient-entered information in Epic’s patient-facing app, MyChart, to show an individual’s likelihood of testing positive for COVID-19. Predicting positive COVID-19 tests could help direct limited healthcare resources, encourage those who are likely to have the virus to get tested, and tailor decision-making about care, Epic said.
“We have developed the first validated prediction model that can forecast an individual’s risk for testing positive with COVID-19 and then simplified this tool while retaining exceptional accuracy for easy adoption,” said Lara Jehi, MD, Chief Research Information Officer at Cleveland Clinic. “
Patients complete a short self-assessment in MyChart, documenting information like symptoms they are experiencing and potential exposure to COVID-19. The model uses that information, as well as clinical and demographic data already in their electronic chart, to calculate their score. Patients with high risk for having COVID-19 are advised to receive a test, and their care team members can be automatically notified of a high-risk score.
Cleveland Clinic’s model was developed and validated using retrospective patient data from patients tested for COVID-19 at Cleveland Clinic locations in Northeast Ohio and Florida. Data scientists used statistical algorithms to transform data from patients’ electronic medical records into the first-of-its-kind risk-prediction model. All data collected was housed in a secure database.
