Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data

Tyler N.A. Winkelman; Karen L. Margolis; Stephen Waring; Peter J. Bodurtha; Rohan Khazanchi; Stefan Gildemeister; Pamela J. Mink; Malini DeSilva; Anne M. Murray; Nayanjot Rai; Julie Sonier; Claire Neely; Steven G. Johnson; Alanna M. Chamberlain; Yue Yu; Lynn M. McFarling; R. Adams Dudley; Paul E. Drawz

doi:10.1177/00333549211061317

Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data

Tyler N.A. Winkelman, Karen L. Margolis, Stephen Waring, Peter J. Bodurtha, Rohan Khazanchi, Stefan Gildemeister, Pamela J. Mink, Malini DeSilva, Anne M. Murray, Nayanjot Rai, Julie Sonier, Claire Neely, Steven G. Johnson, Alanna M. Chamberlain, Yue Yu, Lynn M. McFarling, R. Adams Dudley, Paul E. Drawz

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

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.

Original language	English (US)
Pages (from-to)	263-271
Number of pages	9
Journal	Public health reports
Volume	137
Issue number	2
DOIs	https://doi.org/10.1177/00333549211061317
State	Published - Mar 2022

Bibliographical note

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health’s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health’s National Center for Advancing Translational Sciences.

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health?s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health?s National Center for Advancing Translational Sciences.

Publisher Copyright:
© 2022, Association of Schools and Programs of Public Health.

Keywords

COVID-19
health disparities
health informatics
infectious diseases
public health surveillance

PubMed: MeSH publication types

Research Support, Non-U.S. Gov't
Journal Article
Research Support, N.I.H., Extramural

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/00333549211061317

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Winkelman, T. N. A., Margolis, K. L., Waring, S., Bodurtha, P. J., Khazanchi, R., Gildemeister, S., Mink, P. J., DeSilva, M., Murray, A. M., Rai, N., Sonier, J., Neely, C., Johnson, S. G., Chamberlain, A. M., Yu, Y., McFarling, L. M., Dudley, R. A., & Drawz, P. E. (2022). Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data. Public health reports, 137(2), 263-271. https://doi.org/10.1177/00333549211061317

Winkelman, TNA, Margolis, KL, Waring, S, Bodurtha, PJ, Khazanchi, R, Gildemeister, S, Mink, PJ, DeSilva, M, Murray, AM, Rai, N, Sonier, J, Neely, C, Johnson, SG, Chamberlain, AM, Yu, Y, McFarling, LM, Dudley, RA & Drawz, PE 2022, 'Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data', Public health reports, vol. 137, no. 2, pp. 263-271. https://doi.org/10.1177/00333549211061317

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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.",

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author = "Winkelman, {Tyler N.A.} and Margolis, {Karen L.} and Stephen Waring and Bodurtha, {Peter J.} and Rohan Khazanchi and Stefan Gildemeister and Mink, {Pamela J.} and Malini DeSilva and Murray, {Anne M.} and Nayanjot Rai and Julie Sonier and Claire Neely and Johnson, {Steven G.} and Chamberlain, {Alanna M.} and Yue Yu and McFarling, {Lynn M.} and Dudley, {R. Adams} and Drawz, {Paul E.}",

note = "Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health{\textquoteright}s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health{\textquoteright}s National Center for Advancing Translational Sciences. Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health?s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health?s National Center for Advancing Translational Sciences. Publisher Copyright: {\textcopyright} 2022, Association of Schools and Programs of Public Health.",

year = "2022",

month = mar,

doi = "10.1177/00333549211061317",

language = "English (US)",

volume = "137",

pages = "263--271",

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T1 - Minnesota Electronic Health Record Consortium COVID-19 Project

T2 - Informing Pandemic Response Through Statewide Collaboration Using Observational Data

AU - Winkelman, Tyler N.A.

AU - Margolis, Karen L.

AU - Waring, Stephen

AU - Bodurtha, Peter J.

AU - Khazanchi, Rohan

AU - Gildemeister, Stefan

AU - Mink, Pamela J.

AU - DeSilva, Malini

AU - Murray, Anne M.

AU - Rai, Nayanjot

AU - Sonier, Julie

AU - Neely, Claire

AU - Johnson, Steven G.

AU - Chamberlain, Alanna M.

AU - Yu, Yue

AU - McFarling, Lynn M.

AU - Dudley, R. Adams

AU - Drawz, Paul E.

N1 - Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health’s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health’s National Center for Advancing Translational Sciences. Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Minnesota Department of Health and the National Institutes of Health?s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health?s National Center for Advancing Translational Sciences. Publisher Copyright: © 2022, Association of Schools and Programs of Public Health.

PY - 2022/3

Y1 - 2022/3

N2 - 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.

AB - 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.

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KW - public health surveillance

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Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data

Abstract

Bibliographical note

Keywords

PubMed: MeSH publication types

UN SDGs

Publisher link

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