An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)

Author:

Liu Sijia1ORCID,Wen Andrew1ORCID,Wang Liwei1ORCID,He Huan1ORCID,Fu Sunyang1ORCID,Miller Robert2,Williams Andrew2ORCID,Harris Daniel3ORCID,Kavuluru Ramakanth3ORCID,Liu Mei4ORCID,Abu-el-Rub Noor4,Schutte Dalton5,Zhang Rui5ORCID,Rouhizadeh Masoud6ORCID,Osborne John D7ORCID,He Yongqun8ORCID,Topaloglu Umit9ORCID,Hong Stephanie S10,Saltz Joel H11ORCID,Schaffter Thomas12ORCID,Pfaff Emily13ORCID,Chute Christopher G10ORCID,Duong Tim14,Haendel Melissa A15ORCID,Fuentes Rafael16,Szolovits Peter17ORCID,Xu Hua18ORCID,Liu Hongfang118ORCID

Affiliation:

1. Department of Artificial Intelligence and Informatics, Mayo Clinic , Rochester, Minnesota, USA

2. Tufts Clinical and Translational Science Institute, Tufts Medical Center , Boston, Massachusetts, USA

3. Department of Internal Medicine, University of Kentucky , Lexington, Kentucky, USA

4. Department of Internal Medicine, University of Kansas Medical Center , Kansas City, Kansas, USA

5. Department of Pharmaceutical Care & Health Systems, University of Minnesota at Twin Cities , Minneapolis, Minnesota, USA

6. Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville , Florida, USA

7. Department of Computer Science, University of Alabama at Birmingham , Birmingham, Alabama, USA

8. Department of Computational Medicine and Bioinformatics, University of Michigan Medical School , Ann Arbor, Michigan, USA

9. Department of Cancer Biology, Wake Forest School of Medicine , Winston-Salem, North Carolina, USA

10. Department of Medicine, Johns Hopkins University , Baltimore, Maryland, USA

11. Department of Biomedical Informatics, Stony Brook University , Stony Brook, New York, USA

12. Sage Bionetwork , Seattle, Washington, USA

13. Department of Medicine, University of North Carolina Chapel Hill , Chapel Hill, North Carolina, USA

14. Department of Radiology, Albert Einstein College of Medicine , Bronx, New York, USA

15. Center for Health AI, University of Colorado Anschutz Medical Campus , Denver, Colorado, USA

16. Alex Informatics , North Bethesda, Maryland, USA

17. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology , Cambridge, Massachusetts, USA

18. School of Biomedical Informatics, University of Texas Health Science Center at Houston , Houston, Texas, USA

Abstract

Abstract Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.

Funder

National Center for Advancing Translational Sciences

National Institutes of Health

Bill & Melinda Gates Foundation

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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