Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case

Heather M Whitney^{1

2}, Rachel Baccile³, Hui Li^{4

5}, Karen Drukker^{4

5}, Christopher Meyer^{5

6}, Nicholas P Gruszauskas^{4

5}, Weijie Chen^{5

7}, Diane S Lauderdale^{5

8}, Sandy Napel^{5

9}, Seyed Kahaki^{5

7}, Rui Carlos Sá¹⁰, Chris Beesley¹¹, Brandy Phalora¹¹, Sam Michael¹², Robert L Grossman^{5

6}, Ken Gersing¹², Maryellen L Giger^{4

5}; National COVID Cohort Collaborative (N3C) Consortium

Collaborators, Affiliations

Collaborators

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

Affiliations

¹ Department of Radiology, University of Chicago, Chicago, IL, USA. hwhitney@uchicago.edu.
² Medical Imaging and Data Resource Center, Chicago, IL, USA. hwhitney@uchicago.edu.
³ Institute for Translational Medicine, Chicago, IL, USA.
⁴ Department of Radiology, University of Chicago, Chicago, IL, USA.
⁵ Medical Imaging and Data Resource Center, Chicago, IL, USA.
⁶ Center for Translational Data Science, University of Chicago, Chicago, IL, USA.
⁷ Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH, US FDA, Silver Spring, MD, USA.
⁸ Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
⁹ Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA.
¹¹ Regenstreif Institute, Indianapolis, IN, USA.
¹² Office of the Director, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA.

PMID: 40813937
DOI: 10.1007/s10278-025-01605-4

Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case

Heather M Whitney et al. J Imaging Inform Med. 2025.

. 2025 Aug 14.

doi: 10.1007/s10278-025-01605-4. Online ahead of print.

Authors

Collaborators

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

Affiliations

¹ Department of Radiology, University of Chicago, Chicago, IL, USA. hwhitney@uchicago.edu.
² Medical Imaging and Data Resource Center, Chicago, IL, USA. hwhitney@uchicago.edu.
³ Institute for Translational Medicine, Chicago, IL, USA.
⁴ Department of Radiology, University of Chicago, Chicago, IL, USA.
⁵ Medical Imaging and Data Resource Center, Chicago, IL, USA.
⁶ Center for Translational Data Science, University of Chicago, Chicago, IL, USA.
⁷ Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH, US FDA, Silver Spring, MD, USA.
⁸ Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
⁹ Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA.
¹¹ Regenstreif Institute, Indianapolis, IN, USA.
¹² Office of the Director, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA.

PMID: 40813937
DOI: 10.1007/s10278-025-01605-4

Abstract

Interoperability between data sources, one of the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management, can enable multi-modality research. The purpose of our study was to investigate the potential for interoperability between an imaging resource, the Medical Imaging and Data Resource Center (MIDRC), and a clinical record resource, the National COVID Cohort Collaborative (N3C). The use case was the prediction of COVID-19 severity, defined as evidence for invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice in the N3C clinical record. Patient-level matching between MIDRC and N3C was identified using Privacy Preserving Record Linking via an honest broker. We identified positive COVID-19 tests and chest radiograph procedures in N3C and used the interval between them to identify images with matching intervals in MIDRC. Of the 236 patients (306 unique images) meeting initial inclusion criteria in MIDRC, 117 patients (and 139 unique images) remained after date interval matching between repositories and exclusion of patients with multiple potential matches. The Charlson Comorbidity Index (CCI) and the minimum mean arterial pressure (MAP) on the day of the chest radiograph were used as clinical indicators. The AUC in the task of predicting severe COVID-19 was evaluated using the computer-extracted imaging index alone (MIDRC), clinical indicators alone (N3C), and both together. Our model combining imaging and clinical indicators (CCI over 2 and MAP below 70) to predict severe COVID had an AUC of 0.73 (95% CI 0.62-0.84), and the models including imaging or clinical indicators alone were 0.67 (95% CI 0.56-0.79) and 0.69 (95% CI 0.59-0.80), respectively. This study highlights the potential for cross-platform data sharing to facilitate future multi-modality research and broader collaborative studies.

Keywords: COVID-19; Comorbidity; Interoperability; Multi-modality.

PubMed Disclaimer

Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

References

1. MIDRC [Internet]. [cited 2023 Jun 1]. The Medical Imaging and Data Resource Center. Available from: https://www.midrc.org
1. National Covid Cohort Collaborative [Internet]. [cited 2023 Dec 29]. Available from: https://covid.cd2h.org/
1. Chen W, Sá RC, Bai Y, Napel S, Gevaert O, Lauderdale DS, et al. Machine learning with multimodal data for COVID-19. Heliyon. 2023 Jul 1;9(7):e17934. - DOI - PubMed - PMC
1. Perlin JB. Health Information Technology Interoperability and Use for Better Care and Evidence. JAMA. 2016 Oct 25;316(16):1667–8. - DOI - PubMed
1. Lehne M, Sass J, Essenwanger A, Schepers J, Thun S. Why digital medicine depends on interoperability. npj Digit Med. 2019 Aug 20;2(1):1–5. - DOI

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Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case

Collaborators

Affiliations

Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case

Authors

Collaborators

Affiliations

Abstract

Conflict of interest statement

References

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