Tyler N A Winkelman1,2, Karen L Margolis3, Stephen Waring4, Peter J Bodurtha2, Rohan Khazanchi2,5,6, Stefan Gildemeister7, Pamela J Mink7, Malini DeSilva3, Anne M Murray8,9, Nayanjot Rai10, Julie Sonier11, Claire Neely12, Steven G Johnson13, Alanna M Chamberlain14, Yue Yu14, Lynn M McFarling15, R Adams Dudley13,16,17, Paul E Drawz10. 1. Division of General Internal Medicine, Department of Medicine, Hennepin Healthcare, Minneapolis, MN, USA. 2. Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, USA. 3. HealthPartners Institute, Minneapolis, MN, USA. 4. Essentia Health, Essentia Institute of Health, Duluth, MN, USA. 5. School of Public Health, University of Minnesota, Minneapolis, MN, USA. 6. College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA. 7. Minnesota Department of Health, Saint Paul, MN, USA. 8. Division of Geriatrics, Department of Internal Medicine, Hennepin Healthcare, Minneapolis, MN, USA. 9. Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Minneapolis, MN, USA. 10. Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN, USA. 11. MN Community Measurement, Minneapolis, MN, USA. 12. Institute for Clinical Systems Improvement, Minneapolis, MN, USA. 13. Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA. 14. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA. 15. CentraCare, St. Cloud, MN, USA. 16. Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA. 17. Minneapolis Veterans Affairs Medical Center, Minneapolis, MN, USA.
Abstract
OBJECTIVE: Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems. MATERIALS AND METHODS: In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics. RESULTS: Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time. PRACTICE IMPLICATIONS: We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.
OBJECTIVE: Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems. MATERIALS AND METHODS: In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics. RESULTS: Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time. PRACTICE IMPLICATIONS: We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.
Entities:
Keywords:
COVID-19; health disparities; health informatics; infectious diseases; public health surveillance
Authors: Michael C Grant; Luke Geoghegan; Marc Arbyn; Zakaria Mohammed; Luke McGuinness; Emily L Clarke; Ryckie G Wade Journal: PLoS One Date: 2020-06-23 Impact factor: 3.240
Authors: Tyler N A Winkelman; Nayanjot K Rai; Peter J Bodurtha; Alanna M Chamberlain; Malini DeSilva; Jessica Jeruzal; Steven G Johnson; Anupam Kharbanda; Niall Klyn; Pamela J Mink; Miriam Muscoplat; Stephen Waring; Yue Yu; Paul E Drawz Journal: JAMA Netw Open Date: 2022-03-01