In the age of COVID-19, decisions that affect our day-to-day lives are influenced by analyzing numbers and data. For example, the COVID-19 positivity rate (the percentage of people who test positive for the virus out of the total number tested) influence whether or not businesses may open to the public, or, if schools should offer virtual, hybrid or in-class learning. Data are critical for strategizing, planning and implementing the policies and procedures needed to respond to the crisis and keep people safe. But what happens if different organizations are using different definitions to track the same data? Now, in a commentary published online Dec. 23, 2020, in the Journal of Hospital Medicine, J. Matthew Austin, Ph.D., M.S., and Allen Kachalia, M.D., J.D., highlight how the lack of standardized definitions for many key measures needed to manage the public health response can lead to debate, confusion and politicization of pandemic data.
During the early stages of the pandemic, Austin and Kachalia, at the Johns Hopkins Armstrong Institute for Patient Safety and Quality, began to question the methods used to report the number of positive COVID-19 cases in Maryland, as cases were being reported publically by the day the test result was known—not by the day the test was conducted. In turn, this got them thinking about how the decisions that were being made regarding how to collect and report these data could have a serious impact on how people work and live.
“This is not about a right way or a wrong way of collecting these data,” says Austin, a faculty member at the Armstrong Institute and assistant professor of anesthesiology and critical care medicine at the Johns Hopkins University School of Medicine. “What we’re advocating is a standardized way of collecting and analyzing data so that we can effectively manage this pandemic and future ones.”
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