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
Nestrasil, Igor; Ahmed, Alia; Utz, Josephine M et al. (2018) Distinct progression patterns of brain disease in infantile and juvenile gangliosidoses: Volumetric quantitative MRI study. Mol Genet Metab 123:97-104
Smith, Julia R; Hillman, Lisa; Drawz, Paul E (2018) Pharmacist-based antihypertensive medication review and assignment of morning versus evening dosing of once-daily antihypertensive medications: A pilot study to assess feasibility and efficacy in chronic kidney disease patients. Clin Exp Hypertens 40:569-573
Borden, Amy R; Satrom, Katie M; Wratkowski, Paul et al. (2018) Variation in the Phototherapy Practices and Irradiance of Devices in a Major Metropolitan Area. Neonatology 113:269-274
Logan, Jacqueline; Nederhoff, Dawn; Koch, Brandon et al. (2018) 'What have you HEARD about the HERD?' Does education about local influenza vaccination coverage and herd immunity affect willingness to vaccinate? Vaccine 36:4118-4125
Pi, Chia-Hsing; Yu, Guanglin; Petersen, Ashley et al. (2018) Characterizing the ""sweet spot"" for the preservation of a T-cell line using osmolytes. Sci Rep 8:16223
Garcia-Huidobro, Diego; Diaspro-Higuera, Maria O; Palma, Dora et al. (2018) Adaptive Recruitment and Parenting Interventions for Immigrant Latino Families with Adolescents. Prev Sci :
Sjaastad, Louisa E; Fay, Elizabeth J; Fiege, Jessica K et al. (2018) Distinct antiviral signatures revealed by the magnitude and round of influenza virus replication in vivo. Proc Natl Acad Sci U S A 115:9610-9615
Ryder, J R; Gross, A C; Fox, C K et al. (2018) Factors associated with long-term weight-loss maintenance following bariatric surgery in adolescents with severe obesity. Int J Obes (Lond) 42:102-107
Santi, Andrea; Bosch, Tyler A; Bantle, Anne E et al. (2018) High Body Mass Index Masks Body Composition Differences in Physically Active Versus Sedentary Participants. Metab Syndr Relat Disord 16:483-489
Byiers, Breanne; Barney, Chantel; Ehrhardt, Michael et al. (2018) Initial Observations of Salivary Brain-Derived Neurotrophic Factor Levels in Rett Syndrome. Pediatr Neurol 80:88-89

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