Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae

Eleanor S. Click; Donald Malec; Jennifer R. Chevinsky; Guoyu Tao; Michael Melgar; Jennifer E. Giovanni; Adi V. Gundlapalli; S. Deblina Datta; Karen K. Wong

Disclosures

Emerging Infectious Diseases. 2023;29(2):389-392. 

In This Article

Abstract and Introduction

Abstract

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre– and post–COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post–COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

Introduction

SARS-CoV-2 causes acute COVID-19 and may cause post–COVID-19 conditions, which include a range of long-term sequelae.[1,2] Review of multiple studies describes ongoing symptoms after acute COVID-19.[3] Post–COVID-19 conditions might include symptoms of nonspecific chest pain, fatigue, and malaise, as well as cardiomyopathy, renal failure, lung disease, and venous thromboembolism. Identifying possible sequelae of an emerging disease has traditionally required aggregating clinical experiences; this approach might miss sequelae that are rare or where the increase above baseline is not obvious.[4]

Large electronic health information databases might aid in detecting these early signals, especially when potential sequelae events are temporally and geographically dispersed. The International Classification of Diseases, 10th revision (ICD-10), code for post–COVID-19 conditions was not available for use in the United States until October 2021; thus, examining other diagnosis codes is needed to infer potential sequelae.[5] We evaluated feasibility of a method comparing pre– and post–COVID-19 diagnosis healthcare codes to identify possible sequelae from a large national database of healthcare encounters.

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