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Saturday, December 4 • 11:30am - 12:00pm
Keynote 6 - Who Has long-Covid? A Small and Big Data Approach - Melissa Haendel, PhD

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University of Colorado
United States

Biography (.pdf)

Who Has long-Covid? A Small and Big Data Approach

Post-acute sequelae of SARS-CoV-2 infection, or long-COVID, have severely impacted recovery from the pandemic for patients and society alike. This new disease is characterized by evolving, heterogeneous symptoms, which not only makes it a challenge to derive an unambiguous long-COVID definition but hampers clinicians' ability to offer effective and timely treatment. Clinicians and patients report distinct albeit overlapping spectra of symptoms making long-COVID classification difficult for diagnosis and care management. The clinical view is therefore incomplete. We have used the Human Phenotype Ontology to classify symptoms from patients and clinicians, which can provide subclasses of long-covid and the foundation for improved patient diagnosis and care management. Electronic health records (EHRs) could also be a good source of data for rapidly identifying patients with long-COVID. However, the aforementioned overlapping and incomplete spectra of symptoms make harvesting the correct data from heterogeneous EHR databases a significant challenge. Using the National COVID Cohort Collaborative’s (N3C) EHR repository, we developed XGBoost machine learning models to identify potential long-COVID patients. We examined demographics, healthcare utilization, diagnoses, and medications for 97,995 adult COVID-19 patients. Our models identified potential long-COVID patients with high accuracy, with important features including the rate of healthcare utilization, patient age, dyspnea, and other diagnosis and medications. Combinatorial approaches such as those presented here are especially useful in the face of a new disease with different patient trajectories and few treatment options and can provide the basis for research studies and treatment strategies.

avatar for Melissa Haendel

Melissa Haendel

Chief Research Informatics Officer, University of Colorado
Melissa Haendel is the Chief Research Informatics Officer at University of Colorado Anschutz Medical Campus. She directs the Center for Data to Health (CD2H), the Monarch Initiative, and the National Covid Cohort Collaborative. Her background is molecular genetics and developmental... Read More →

Saturday December 4, 2021 11:30am - 12:00pm MST
Ballroom Salon 1