National COVID Cohort Collaborative data enhancements: a path for expanding common data models
Authors: Walters Kellie M , Clark Marshall , Dard Sofia , Hong Stephanie S , Kelly Elizabeth , Kostka Kristin , Lee Adam M , Miller Robert T , Morris Michele , Palchuk Matvey B , Pfaff Emily R ,   N3C and RECOVER Consortia, Wilcox Adam B , Graves Alexis , Anzalone Alfred (Jerrod) , Manna Amin , Saha Amit , Olex Amy , Zhou Andrea , Williams Andrew E , Southerland Andrew , Girvin Andrew T , Walden Anita , Sharathkumar Anjali A , Amor Benjamin , Bates Benjamin , Hendricks Brian , Patel Brijesh , Alexander Caleb , Bramante Carolyn , Ward-Caviness Cavin , Madlock-Brown Charisse , Suver Christine , Chute Christopher , Dillon Christopher , Wu Chunlei , Schmitt Clare , Takemoto Cliff , Housman Dan , Gabriel Davera , Eichmann David A , Mazzotti Diego , Brown Don , Boudreau Eilis , Hill Elaine , Zampino Elizabeth , Marti Emily Carlson , French Evan , Koraishy Farrukh M , Mariona Federico , Prior Fred , Sokos George , Martin Greg , Lehmann Harold , Spratt Heidi , Mehta Hemalkumar , Liu Hongfang , Sidky Hythem , Hayanga J W Awori , Pincavitch Jami , Clark Jaylyn , Harper Jeremy Richard , Islam Jessica , Ge Jin , Gagnier Joel , Saltz Joel H , Saltz Joel , Loomba Johanna , Buse John , Mathew Jomol , Rutter Joni L , McMurry Julie A , Guinney Justin , Starren Justin , Crowley Karen , Bradwell Katie Rebecca , Wilkins Ken , Gersing Kenneth R , Cato Kenrick Dwain , Murray Kimberly , Northington Lavance , Pyles Lee Allan , Misquitta Leonie , Cottrell Lesley , Portilla Lili , Deacy Mariam , Bissell Mark M , Emmett Mary , Saltz Mary Morrison , Haendel Melissa A , Adams Meredith , Temple-O'Connor Meredith , Kurilla Michael G , Qureshi Nabeel , Safdar Nasia , Garbarini Nicole , Sharafeldin Noha , Sadan Ofer , Francis Patricia A , Burgoon Penny Wung , Robinson Peter , Payne Philip R O , Fuentes Rafael , Jawa Randeep , Erwin-Cohen Rebecca , Patel Rena , Moffitt Richard A , Zhu Richard L , Kamaleswaran Rishi , Hurley Robert , Pyarajan Saiju , Michael Sam G , Bozzette Samuel , Mallipattu Sandeep , Vedula Satyanarayana , Chapman Scott , O'Neil Shawn T , Setoguchi Soko , Johnson Steve , Bennett Tellen D , Callahan Tiffany , Topaloglu Umit , Sheikh Usman , Gordon Valery , Subbian Vignesh , Kibbe Warren A , Hernandez Wenndy , Beasley Will , Cooper Will , Hillegass William , Zhang Xiaohan Tanner 
Published: November 2024

Abstract

Objective
To support long COVID research in National COVID Cohort Collaborative (N3C), the N3C Phenotype and Data Acquisition team created data designs to aid contributing sites in enhancing their data. Enhancements include long COVID specialty clinic indicator; Admission, Discharge, and Transfer transactions; patient-level social determinants of health; and in-hospital use of oxygen supplementation.

Materials and Methods
For each enhancement, we defined the scope and wrote guidance on how to prepare and populate the data in a standardized way.

Results
As of June 2024, 29 sites have added at least one data enhancement to their N3C pipeline.

Discussion
The use of common data models is critical to the success of N3C; however, these data models cannot account for all needs. Project-driven data enhancement is required. This should be done in a standardized way in alignment with common data model specifications. Our approach offers a useful pathway for enhancing data to improve fit for purpose.

Conclusion
In this initiative, we rapidly produced project-specific data modeling guidance and documentation in support of long COVID research while maintaining a commitment to terminology standards and harmonized data.