National Clinical Cohort Collaborative (N3C) and NIH RECOVER

Long COVID research in the National Clinical Cohort Collaborative (N3C, formerly the National COVID Cohort Collaborative) and NIH RECOVER, using harmonized multi-site EHR data. Contributions include machine-learning phenotyping, ICD-10-based characterization, and target trial emulations of antiviral treatment.

Past Aug 2021 – 2025 Pfaff Lab Clinical Informatics Website
Details
Role
Graduate Research Assistant
Lab
Pfaff Lab · UNC Chapel Hill
Funder
NIH/NCATS
With
Emily Pfaff
Methods
statistical learningcausal inference
Years
Aug 2021 – 2025

Related Publications

2025

Effect of Paxlovid Treatment during Acute COVID-19 on Long COVID Onset: An EHR-Based Target Trial Emulation from the N3C and RECOVER Consortia

Alexander Preiss, Abhishek Bhatia, Leyna V. Aragon, John M. Baratta, Monika Baskaran, Frank Blancero, M. Daniel Brannock, Robert F. Chew, Ivan Diaz, Megan Fitzgerald, Elizabeth P. Kelly, Andrea Zhou, Thomas W. Carton, Fei Wang, Rainu Kaushal, Christopher G. Chute, Melissa Haendel, Richard Moffitt, Emily Pfaff, N3C Consortium, the RECOVER Cohort

PLOS Medicine PDF for Effect of Paxlovid Treatment during Acute COVID-19 on Long COVID Onset: An EHR-Based Target Trial Emulation from the N3C and RECOVER Consortia Project for Effect of Paxlovid Treatment during Acute COVID-19 on Long COVID Onset: An EHR-Based Target Trial Emulation from the N3C and RECOVER Consortia

2025

Re-engineering a Machine Learning Phenotype to Adapt to the Changing COVID-19 Landscape: A Machine Learning Modelling Study from the N3C and RECOVER Consortia

Miles Crosskey, Tomas McIntee, Sandy Preiss, Daniel Brannock, Yun Jae Yoo, Emily Hadley, Frank Blancero, Rob Chew, Johanna Loomba, Abhishek Bhatia, Christopher G. Chute, Melissa Haendel, Richard Moffitt, Emily R. Pfaff, N3C Consortium, the RECOVER EHR Cohort

The Lancet Digital Health Article for Re-engineering a Machine Learning Phenotype to Adapt to the Changing COVID-19 Landscape: A Machine Learning Modelling Study from the N3C and RECOVER Consortia Project for Re-engineering a Machine Learning Phenotype to Adapt to the Changing COVID-19 Landscape: A Machine Learning Modelling Study from the N3C and RECOVER Consortia

2025

Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort

John P. Powers, Tomas J. McIntee, Abhishek Bhatia, Charisse R. Madlock-Brown, Jaime Seltzer, Anisha Sekar, Nita Jain, Mady Hornig, Elle Seibert, Peter J. Leese, Melissa Haendel, Richard Moffitt, Emily R. Pfaff, N3C Consortium, the RECOVER EHR Cohort

Communications Medicine Article for Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort Project for Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort

2025

Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: An EHR-Based Target Trial Emulation from N3C

Abhishek Bhatia, Alexander J. Preiss, Xuya Xiao, M. Daniel Brannock, G. Caleb Alexander, Robert F. Chew, Megan Fitzgerald, Elaine Hill, Elizabeth P. Kelly, Hemalkumar B. Mehta, Charisse Madlock-Brown, Kenneth J. Wilkins, Christopher G. Chute, Melissa Haendel, Richard Moffitt, Emily R. Pfaff

PLOS Medicine PDF for Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: An EHR-Based Target Trial Emulation from N3C Project for Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: An EHR-Based Target Trial Emulation from N3C

2023

Coding Long COVID: Characterizing a New Disease through an ICD-10 Lens

Emily R. Pfaff, Charisse Madlock-Brown, John M. Baratta, Abhishek Bhatia, Hannah Davis, Andrew Girvin, Elaine Hill, Elizabeth Kelly, Kristin Kostka, Johanna Loomba, Julie A. McMurry, Rachel Wong, Tellen D. Bennett, Richard Moffitt, Christopher G. Chute, Melissa Haendel, {The N3C Consortium}, {The RECOVER Consortium}

BMC Medicine PDF for Coding Long COVID: Characterizing a New Disease through an ICD-10 Lens Project for Coding Long COVID: Characterizing a New Disease through an ICD-10 Lens

2022

Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data

Emily R. Pfaff, Andrew T. Girvin, Tellen D. Bennett, Abhishek Bhatia, Ian M. Brooks, Rachel R. Deer, Jonathan P. Dekermanjian, Sarah Elizabeth Jolley, Michael G. Kahn, Kristin Kostka, Julie A. McMurry, Richard Moffitt, Anita Walden, Christopher G. Chute, Melissa A. Haendel, Carolyn Bramante, David Dorr, Michele Morris, Ann M. Parker, Hythem Sidky, Ken Gersing, Stephanie Hong, Emily Niehaus

The Lancet Digital Health PDF for Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data Project for Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data Code for Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data

Talks & presentations

  • Talk “Considerations for long-COVID research using real-world data.” Panel Presentation at the American Medical Informatics Association Informatics Summit, Seattle, WA. (2023)
  • Poster “Harnessing Electronic Health Record data for Causal Inference through Target Trial Emulation: lessons from N3C-RECOVER.” American Medical Informatics Association Annual Symposium, New Orleans, LA. (2023)
  • Invited “Effectiveness of Paxlovid in Protecting Against Long COVID: EHR Insights.” RECOVER Research Review (R3) Seminar Series, The RECOVER Initiative — United States National Institutes of Health, Virtual. (2025)

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