Challenges in Studying Long COVID with Real-World Data

Real-world data (RWD) has been used extensively throughout the COVID-19 pandemic, with significant data generated regarding long COVID,  symptoms of the disease that persist after the initial infection. However, there are significant challenges that remain when implementing RWD in studying the chronic condition. In a newly published paper in Nature, authors identify three major points of improvement to better utilize RWD in long-COVID research.

According to the authors, “We are an international consortium that has operationalized definitions of long COVID using health-agency guidelines, and established a chart-review procedure based on these definitions. During this process, we identified three major challenges in using real-world data to study long COVID: ambiguity and heterogeneity in clinical coding of long COVID; inadequacy of diagnostic codes in capturing the constellation of symptoms; and biases in EHR data arising from variability in the number and kind of contacts with the healthcare system. These challenges warrant special attention if the clinical community wishes to arrive at a robust understanding of long COVID using evidence derived from real-world data.”

To read more, click here.

(Source: Nature, April 13^th, 2023)