Health IT Analytics October 28, 2020
Predictive analytics models can help public health officials complete missing demographic information, leading to more comprehensive COVID-19 data.
A predictive analytics tool has helped public health leaders in Chicago improve the quality of COVID-19 data, reducing the category of “unknown” race in tests from 47 percent to 11 percent.
While thousands of people are being tested for COVID-19 every day, collecting complete demographic information can be difficult. This presents a critical issue for the healthcare industry, as incomplete race and ethnicity data can cast a shadow over the disparities minority and underrepresented populations are experiencing during the pandemic.
“This information is essential for understanding inequities with COVID-19,” said Fernando De Maio, professor of sociology and founding co-director of the Center...