Better Care Through Big Data

Data mining is yielding a treasure trove of insights that could lead to personalized — and more effective — coronavirus treatments.

Using a registry of deidentified health data from thousands of Cleveland Clinic patients who were tested for COVID-19, Michael Kattan, PhD, and Lara Jehi, MD, of the Lerner Research Institute collaborated with colleagues across Cleveland Clinic to create a COVID-19 risk prediction calculator. Dr. Jehi is Cleveland Clinic’s Chief Research Information Officer; Dr. Kattan holds the Dr. Keyhan and Dr. Jafar Mobasseri Endowed Chair for Innovations in Cancer Research.


Dr. Michael Kattan and Dr. Lara Jehi use predictive analytics to counter the pandemic with personalized medicine. | Photo: Stephen Travarca

By comparing a control group of patients who tested negative with those who tested positive, the researchers are determining risk and protective factors associated with the virus.

One study, for example, looked at the safety of common hypertension medications in relation to a person’s risk for COVID-19 complications. Earlier reports had questioned whether these medications, which target the renin-angiotensin-aldosterone system, could worsen the symptoms of COVID-19 or make a person more susceptible to contracting the virus. This study did not show an increase in a person’s risk for COVID-19 complications if they were taking one of these commonly prescribed medications.

In this episode of the Research Insider series, Michael Kattan, PhD, and Lara Jehi, MD, of Cleveland Clinic discuss how clinical data is facilitating unique COVID-19 investigations.