The National COVID Cohort Collaborative (N3C) is a project that is funded by NCATS to build a central registry of patients who have been tested for COVID-19 or have a clinical diagnosis of COVID-19. The Observational Medical Outcomes Partnership (OMOP) data model is the representational format used in the full N3C repository. This project proposes to develop a COVID-19 data extract from the University of Minnesota COVID-19 Registry by mapping it to the OMOP data model in order to support optimal participation in the N3C. The OMOP format will allow us to contribute all of our COVID-19 patient data at a level of detail necessary to study this disease. The University of Minnesota has developed and maintains a CDR that contains the EHR records and ancillary data for 3M patients from affiliated clinics and hospitals of the M Health Fairview System. The CDR was created in 2012 and uses a proprietary data model developed at the University of Minnesota which has served our researchers well. In 2017, Fairview Health Systems merged with another healthcare organization, HealthEast. As of 2020, the HealthEast EHR has not been integrated into the overall Fairview Epic system and no HealthEast EHR records are available in the CDR. In March 2020, one of the HealthEast hospitals, Bethesda, was designated as the COVID hospital to treat COVID-19 ICU patients for the combined health system. Because of this, only 50% of our COVID-19 patients' data is available in the CDR. In order to serve the immediate needs of our COVID-19 researchers, a process for extracting COVID-19 related data from the HealthEast system into a University of Minnesota COVID-19 Registry has been implemented. The University of Minnesota has signed the N3C data transfer agreement and will begin participation by extracting data from our ACT i2b2 instance to the N3C. However, none of the HealthEast data is incorporated into our ACT i2b2 database. For complete participation, we propose to map the University of Minnesota COVID-19 Registry to OMOP in order to support optimal participation in the N3C. The OMOP data model provides the optimal mapping with the most detail and gives the N3C the most benefits from our data. This approach will also allow all of the HealthEast COVID-19 patient data to be included in a complete extract of all COVID-19 patients across our entire health system to the N3C with data represented at a level of detail necessary to study this disease.

Public Health Relevance

This project will enhance the University of Minnesota COVID-19 Registry by mapping it to the Observational Medical Outcomes Partnership (OMOP) data model in order to support optimal participation in the N3C. The OMOP format will allow us to contribute all of our COVID-19 patient data at a level of detail necessary to study this disease.

Agency
National Institute of Health (NIH)
Institute
National Center for Advancing Translational Sciences (NCATS)
Type
Linked Specialized Center Cooperative Agreement (UL1)
Project #
3UL1TR002494-03S5
Application #
10228268
Study Section
Program Officer
Zhang, Xinzhi
Project Start
2018-03-30
Project End
2023-02-28
Budget Start
2020-09-23
Budget End
2021-02-28
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Pediatrics
Type
Schools of Medicine
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Hart, Allyson; Patzer, Rachel E (2018) Equity in kidney transplantation: Policy change is only the first step. Am J Transplant 18:1839-1840
Vangay, Pajau; Johnson, Abigail J; Ward, Tonya L et al. (2018) US Immigration Westernizes the Human Gut Microbiome. Cell 175:962-972.e10
Purani, Himal; Friedrichsen, Samantha; Allen, Alicia M (2018) Sleep quality in cigarette smokers: Associations with smoking-related outcomes and exercise. Addict Behav 90:71-76
Hultman, Gretchen; McEwan, Reed; Pakhomov, Serguei et al. (2018) Usability Evaluation of an Unstructured Clinical Document Query Tool for Researchers. AMIA Jt Summits Transl Sci Proc 2017:84-93
Schweigert, Anna; Lunos, Scott; Connett, John et al. (2018) Changes in refractive errors in albinism: a longitudinal study over the first decade of life. J AAPOS 22:462-466
Tulstrup, Morten; Grosjean, Marie; Nielsen, Stine Nygaard et al. (2018) NT5C2 germline variants alter thiopurine metabolism and are associated with acquired NT5C2 relapse mutations in childhood acute lymphoblastic leukaemia. Leukemia 32:2527-2535
Allen, Alicia; Carlson, Samantha C; Bosch, Tyler A et al. (2018) High-intensity Interval Training and Continuous Aerobic Exercise Interventions to Promote Self-initiated Quit Attempts in Young Adults Who Smoke: Feasibility, Acceptability, and Lessons Learned From a Randomized Pilot Trial. J Addict Med 12:373-380
Ho, Yen-Yi; Nhu Vo, Tien; Chu, Haitao et al. (2018) A Bayesian hierarchical model for demand curve analysis. Stat Methods Med Res 27:2038-2049
Aldekhyyel, Raniah N; Melton, Genevieve B; Lindgren, Bruce et al. (2018) Linking Pediatrics Patients and Nurses With the Pharmacy and Electronic Health Record System Through the Inpatient Television: A Novel Interactive Pain-Management Tool. Hosp Pediatr 8:588-592
Chen, Chao-Ying; McGee, Corey W; Rich, Tonya L et al. (2018) Reference values of intrinsic muscle strength of the hand of adolescents and young adults. J Hand Ther 31:348-356

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