Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data

Madeleine Jones; Aubrey Winger; Christian Wernz; Jonathan Michel; Sihang Jiang; Andrea Zhou; Ebony Jade Hilton; Mikhail Zemmel; Saurav Sengupta; Kierah Barnes; Johanna Loomba; Donald E. Brown; Adam B. Wilcox; Adam M. Lee; Alexis Graves; Alfred Anzalone; Amin Manna; Amit Saha; Amy Olex; Andrew E. Williams; Andrew Southerland; Andrew T. Girvin; Anita Walden; Anjali A. Sharathkumar; Benjamin Amor; Benjamin Bates; Brian Hendricks; Brijesh Patel; Caleb Alexander; Carolyn Bramante; Cavin Ward-Caviness; Charisse Madlock-Brown; Christine Suver; Christopher Chute; Christopher Dillon; Chunlei Wu; Clare Schmitt; Cliff Takemoto; Dan Housman; Davera Gabriel; David A. Eichmann; Diego Mazzotti; Eilis Boudreau; Elaine Hill; Elizabeth Zampino; Emily Carlson Marti; Emily R. Pfaff; Evan French; Farrukh M. Koraishy; Federico Mariona; Fred Prior; George Sokos; Greg Martin; Harold Lehmann; Heidi Spratt; Hemalkumar Mehta; Hongfang Liu; Hythem Sidky; J. W. Awori Hayanga; Jami Pincavitch; Jaylyn Clark; Jeremy Richard Harper; Jessica Islam; Jin Ge; Joel Gagnier; Joel H. Saltz; John Buse; Jomol Mathew; Joni L. Rutter; Julie A. McMurry; Justin Guinney; Justin Starren; Karen Crowley; Katie Rebecca Bradwell; Kellie M. Walters; Ken Wilkins; Kenneth R. Gersing; Kenrick Dwain Cato; Kimberly Murray; Kristin Kostka; Lavance Northington; Lee Allan Pyles; Leonie Misquitta; Lesley Cottrell; Lili Portilla; Mariam Deacy; Mark M. Bissell; Marshall Clark; Mary Emmett; Mary Morrison Saltz; Matvey B. Palchuk; Melissa A. Haendel; Meredith Adams; Meredith Temple-O'Connor; Michael G. Kurilla; Michele Morris; Nabeel Qureshi; Nasia Safdar; Nicole Garbarini; Noha Sharafeldin; Ofer Sadan; Patricia A. Francis; Penny Wung Burgoon; Peter Robinson; Philip R.O. Payne; Rafael Fuentes; Randeep Jawa; Rebecca Erwin-Cohen; Rena Patel; Richard A. Moffitt; Richard L. Zhu; Rishi Kamaleswaran; Robert Hurley; Robert T. Miller; Saiju Pyarajan; Sam G. Michael; Samuel Bozzette; Sandeep Mallipattu; Satyanarayana Vedula; Scott Chapman; Shawn T. O'Neil; Soko Setoguchi; Stephanie S. Hong; Steve Johnson; Tellen D. Bennett; Tiffany Callahan; Umit Topaloglu; Usman Sheikh; Valery Gordon; Vignesh Subbian; Warren A. Kibbe; Wenndy Hernandez; Will Beasley; Will Cooper; William Hillegass; Xiaohan Tanner Zhang

doi:10.1109/SIEDS58326.2023.10137801

Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data

Madeleine Jones, Aubrey Winger, Christian Wernz, Jonathan Michel, Sihang Jiang, Andrea Zhou, Ebony Jade Hilton, Mikhail Zemmel, Saurav Sengupta, Kierah Barnes, Johanna Loomba, Donald E. Brown, Adam B. Wilcox, Adam M. Lee, Alexis Graves, Alfred Anzalone, Amin Manna, Amit Saha, Amy Olex, Andrew E. WilliamsAndrew Southerland, Andrew T. Girvin, Anita Walden, Anjali A. Sharathkumar, Benjamin Amor, Benjamin Bates, Brian Hendricks, Brijesh Patel, Caleb Alexander, Carolyn Bramante, Cavin Ward-Caviness, Charisse Madlock-Brown, Christine Suver, Christopher Chute, Christopher Dillon, Chunlei Wu, Clare Schmitt, Cliff Takemoto, Dan Housman, Davera Gabriel, David A. Eichmann, Diego Mazzotti, Eilis Boudreau, Elaine Hill, Elizabeth Zampino, Emily Carlson Marti, Emily R. Pfaff, Evan French, Farrukh M. Koraishy, Federico Mariona, Fred Prior, George Sokos, Greg Martin, Harold Lehmann, Heidi Spratt, Hemalkumar Mehta, Hongfang Liu, Hythem Sidky, J. W. Awori Hayanga, Jami Pincavitch, Jaylyn Clark, Jeremy Richard Harper, Jessica Islam, Jin Ge, Joel Gagnier, Joel H. Saltz, John Buse, Jomol Mathew, Joni L. Rutter, Julie A. McMurry, Justin Guinney, Justin Starren, Karen Crowley, Katie Rebecca Bradwell, Kellie M. Walters, Ken Wilkins, Kenneth R. Gersing, Kenrick Dwain Cato, Kimberly Murray, Kristin Kostka, Lavance Northington, Lee Allan Pyles, Leonie Misquitta, Lesley Cottrell, Lili Portilla, Mariam Deacy, Mark M. Bissell, Marshall Clark, Mary Emmett, Mary Morrison Saltz, Matvey B. Palchuk, Melissa A. Haendel, Meredith Adams, Meredith Temple-O'Connor, Michael G. Kurilla, Michele Morris, Nabeel Qureshi, Nasia Safdar, Nicole Garbarini, Noha Sharafeldin, Ofer Sadan, Patricia A. Francis, Penny Wung Burgoon, Peter Robinson, Philip R.O. Payne, Rafael Fuentes, Randeep Jawa, Rebecca Erwin-Cohen, Rena Patel, Richard A. Moffitt, Richard L. Zhu, Rishi Kamaleswaran, Robert Hurley, Robert T. Miller, Saiju Pyarajan, Sam G. Michael, Samuel Bozzette, Sandeep Mallipattu, Satyanarayana Vedula, Scott Chapman, Shawn T. O'Neil, Soko Setoguchi, Stephanie S. Hong, Steve Johnson, Tellen D. Bennett, Tiffany Callahan, Umit Topaloglu, Usman Sheikh, Valery Gordon, Vignesh Subbian, Warren A. Kibbe, Wenndy Hernandez, Will Beasley, Will Cooper, William Hillegass, Xiaohan Tanner Zhang

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

National COVID Cohort Collaborative (N3C) enclave provides health researchers with a rich dataset from 76 contributing clinical sites. However, the harmonized data lacks certain details available in sites' local electronic health records (EHRs), such as the principal diagnosis code for reported emergency department (ED) and inpatient (IP) visits. This means a principal diagnosis of COVID-19 can only be inferred by applying a time relationship between the visit dates and the record of infection and diagnosis. The purpose of this study is to perform a single-site sensitivity analysis modeled after an N3C study examining potential race-ethnicity based bias in hospitalization decisions during COVID-19 related ED visits. The analytic pipeline was first run in N3C, then reproduced locally with N3C data fields from a single-site, and finally run a third time using the additional principal diagnosis data. We find the effects of patient comorbidities and race-ethnicity groups on direct IP admittance to be consistent among the three cohorts with varying levels of statistical significance due to different sample sizes.

Original language	English (US)
Title of host publication	2023 Systems and Information Engineering Design Symposium, SIEDS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	297-302
Number of pages	6
ISBN (Electronic)	9798350300642
DOIs	https://doi.org/10.1109/SIEDS58326.2023.10137801
State	Published - 2023
Event	2023 Systems and Information Engineering Design Symposium, SIEDS 2023 - Charlottesville, United States Duration: Apr 27 2023 → Apr 28 2023

Publication series

Name	2023 Systems and Information Engineering Design Symposium, SIEDS 2023

Conference

Conference	2023 Systems and Information Engineering Design Symposium, SIEDS 2023
Country/Territory	United States
City	Charlottesville
Period	4/27/23 → 4/28/23

ASJC Scopus subject areas

Computer Science Applications
Hardware and Architecture
Information Systems
Decision Sciences (miscellaneous)
Information Systems and Management
Control and Systems Engineering

Access to Document

10.1109/SIEDS58326.2023.10137801

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Jones, M., Winger, A., Wernz, C., Michel, J., Jiang, S., Zhou, A., Hilton, E. J., Zemmel, M., Sengupta, S., Barnes, K., Loomba, J., Brown, D. E., Wilcox, A. B., Lee, A. M., Graves, A., Anzalone, A., Manna, A., Saha, A., Olex, A., ... Zhang, X. T. (2023). Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data. In 2023 Systems and Information Engineering Design Symposium, SIEDS 2023 (pp. 297-302). (2023 Systems and Information Engineering Design Symposium, SIEDS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIEDS58326.2023.10137801

Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data. / Jones, Madeleine; Winger, Aubrey; Wernz, Christian et al.
2023 Systems and Information Engineering Design Symposium, SIEDS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 297-302 (2023 Systems and Information Engineering Design Symposium, SIEDS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jones, M, Winger, A, Wernz, C, Michel, J, Jiang, S, Zhou, A, Hilton, EJ, Zemmel, M, Sengupta, S, Barnes, K, Loomba, J, Brown, DE, Wilcox, AB, Lee, AM, Graves, A, Anzalone, A, Manna, A, Saha, A, Olex, A, Williams, AE, Southerland, A, Girvin, AT, Walden, A, Sharathkumar, AA, Amor, B, Bates, B, Hendricks, B, Patel, B, Alexander, C, Bramante, C, Ward-Caviness, C, Madlock-Brown, C, Suver, C, Chute, C, Dillon, C, Wu, C, Schmitt, C, Takemoto, C, Housman, D, Gabriel, D, Eichmann, DA, Mazzotti, D, Boudreau, E, Hill, E, Zampino, E, Marti, EC, Pfaff, ER, French, E, Koraishy, FM, Mariona, F, Prior, F, Sokos, G, Martin, G, Lehmann, H, Spratt, H, Mehta, H, Liu, H, Sidky, H, Awori Hayanga, JW, Pincavitch, J, Clark, J, Richard Harper, J, Islam, J, Ge, J, Gagnier, J, Saltz, JH, Buse, J, Mathew, J, Rutter, JL, McMurry, JA, Guinney, J, Starren, J, Crowley, K, Bradwell, KR, Walters, KM, Wilkins, K, Gersing, KR, Cato, KD, Murray, K, Kostka, K, Northington, L, Pyles, LA, Misquitta, L, Cottrell, L, Portilla, L, Deacy, M, Bissell, MM, Clark, M, Emmett, M, Saltz, MM, Palchuk, MB, Haendel, MA, Adams, M, Temple-O'Connor, M, Kurilla, MG, Morris, M, Qureshi, N, Safdar, N, Garbarini, N, Sharafeldin, N, Sadan, O, Francis, PA, Burgoon, PW, Robinson, P, Payne, PRO, Fuentes, R, Jawa, R, Erwin-Cohen, R, Patel, R, Moffitt, RA, Zhu, RL, Kamaleswaran, R, Hurley, R, Miller, RT, Pyarajan, S, Michael, SG, Bozzette, S, Mallipattu, S, Vedula, S, Chapman, S, O'Neil, ST, Setoguchi, S, Hong, SS, Johnson, S, Bennett, TD, Callahan, T, Topaloglu, U, Sheikh, U, Gordon, V, Subbian, V, Kibbe, WA, Hernandez, W, Beasley, W, Cooper, W, Hillegass, W & Zhang, XT 2023, Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data. in 2023 Systems and Information Engineering Design Symposium, SIEDS 2023. 2023 Systems and Information Engineering Design Symposium, SIEDS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 297-302, 2023 Systems and Information Engineering Design Symposium, SIEDS 2023, Charlottesville, United States, 4/27/23. https://doi.org/10.1109/SIEDS58326.2023.10137801

Jones M, Winger A, Wernz C, Michel J, Jiang S, Zhou A et al. Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data. In 2023 Systems and Information Engineering Design Symposium, SIEDS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 297-302. (2023 Systems and Information Engineering Design Symposium, SIEDS 2023). doi: 10.1109/SIEDS58326.2023.10137801

Jones, Madeleine ; Winger, Aubrey ; Wernz, Christian et al. / Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19 : Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data. 2023 Systems and Information Engineering Design Symposium, SIEDS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 297-302 (2023 Systems and Information Engineering Design Symposium, SIEDS 2023).

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title = "Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data",

abstract = "National COVID Cohort Collaborative (N3C) enclave provides health researchers with a rich dataset from 76 contributing clinical sites. However, the harmonized data lacks certain details available in sites' local electronic health records (EHRs), such as the principal diagnosis code for reported emergency department (ED) and inpatient (IP) visits. This means a principal diagnosis of COVID-19 can only be inferred by applying a time relationship between the visit dates and the record of infection and diagnosis. The purpose of this study is to perform a single-site sensitivity analysis modeled after an N3C study examining potential race-ethnicity based bias in hospitalization decisions during COVID-19 related ED visits. The analytic pipeline was first run in N3C, then reproduced locally with N3C data fields from a single-site, and finally run a third time using the additional principal diagnosis data. We find the effects of patient comorbidities and race-ethnicity groups on direct IP admittance to be consistent among the three cohorts with varying levels of statistical significance due to different sample sizes.",

author = "Madeleine Jones and Aubrey Winger and Christian Wernz and Jonathan Michel and Sihang Jiang and Andrea Zhou and Hilton, {Ebony Jade} and Mikhail Zemmel and Saurav Sengupta and Kierah Barnes and Johanna Loomba and Brown, {Donald E.} and Wilcox, {Adam B.} and Lee, {Adam M.} and Alexis Graves and Alfred Anzalone and Amin Manna and Amit Saha and Amy Olex and Williams, {Andrew E.} and Andrew Southerland and Girvin, {Andrew T.} and Anita Walden and Sharathkumar, {Anjali A.} and Benjamin Amor and Benjamin Bates and Brian Hendricks and Brijesh Patel and Caleb Alexander and Carolyn Bramante and Cavin Ward-Caviness and Charisse Madlock-Brown and Christine Suver and Christopher Chute and Christopher Dillon and Chunlei Wu and Clare Schmitt and Cliff Takemoto and Dan Housman and Davera Gabriel and Eichmann, {David A.} and Diego Mazzotti and Eilis Boudreau and Elaine Hill and Elizabeth Zampino and Marti, {Emily Carlson} and Pfaff, {Emily R.} and Evan French and Koraishy, {Farrukh M.} and Federico Mariona and Fred Prior and George Sokos and Greg Martin and Harold Lehmann and Heidi Spratt and Hemalkumar Mehta and Hongfang Liu and Hythem Sidky and {Awori Hayanga}, {J. W.} and Jami Pincavitch and Jaylyn Clark and {Richard Harper}, Jeremy and Jessica Islam and Jin Ge and Joel Gagnier and Saltz, {Joel H.} and John Buse and Jomol Mathew and Rutter, {Joni L.} and McMurry, {Julie A.} and Justin Guinney and Justin Starren and Karen Crowley and Bradwell, {Katie Rebecca} and Walters, {Kellie M.} and Ken Wilkins and Gersing, {Kenneth R.} and Cato, {Kenrick Dwain} and Kimberly Murray and Kristin Kostka and Lavance Northington and Pyles, {Lee Allan} and Leonie Misquitta and Lesley Cottrell and Lili Portilla and Mariam Deacy and Bissell, {Mark M.} and Marshall Clark and Mary Emmett and Saltz, {Mary Morrison} and Palchuk, {Matvey B.} and Haendel, {Melissa A.} and Meredith Adams and Meredith Temple-O'Connor and Kurilla, {Michael G.} and Michele Morris and Nabeel Qureshi and Nasia Safdar and Nicole Garbarini and Noha Sharafeldin and Ofer Sadan and Francis, {Patricia A.} and Burgoon, {Penny Wung} and Peter Robinson and Payne, {Philip R.O.} and Rafael Fuentes and Randeep Jawa and Rebecca Erwin-Cohen and Rena Patel and Moffitt, {Richard A.} and Zhu, {Richard L.} and Rishi Kamaleswaran and Robert Hurley and Miller, {Robert T.} and Saiju Pyarajan and Michael, {Sam G.} and Samuel Bozzette and Sandeep Mallipattu and Satyanarayana Vedula and Scott Chapman and O'Neil, {Shawn T.} and Soko Setoguchi and Hong, {Stephanie S.} and Steve Johnson and Bennett, {Tellen D.} and Tiffany Callahan and Umit Topaloglu and Usman Sheikh and Valery Gordon and Vignesh Subbian and Kibbe, {Warren A.} and Wenndy Hernandez and Will Beasley and Will Cooper and William Hillegass and Zhang, {Xiaohan Tanner}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Systems and Information Engineering Design Symposium, SIEDS 2023 ; Conference date: 27-04-2023 Through 28-04-2023",

year = "2023",

doi = "10.1109/SIEDS58326.2023.10137801",

language = "English (US)",

series = "2023 Systems and Information Engineering Design Symposium, SIEDS 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "297--302",

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T1 - Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19

T2 - 2023 Systems and Information Engineering Design Symposium, SIEDS 2023

AU - Jones, Madeleine

AU - Winger, Aubrey

AU - Wernz, Christian

AU - Michel, Jonathan

AU - Jiang, Sihang

AU - Zhou, Andrea

AU - Hilton, Ebony Jade

AU - Zemmel, Mikhail

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AU - Loomba, Johanna

AU - Brown, Donald E.

AU - Wilcox, Adam B.

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AU - Graves, Alexis

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AU - Manna, Amin

AU - Saha, Amit

AU - Olex, Amy

AU - Williams, Andrew E.

AU - Southerland, Andrew

AU - Girvin, Andrew T.

AU - Walden, Anita

AU - Sharathkumar, Anjali A.

AU - Amor, Benjamin

AU - Bates, Benjamin

AU - Hendricks, Brian

AU - Patel, Brijesh

AU - Alexander, Caleb

AU - Bramante, Carolyn

AU - Ward-Caviness, Cavin

AU - Madlock-Brown, Charisse

AU - Suver, Christine

AU - Chute, Christopher

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AU - Mariona, Federico

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AU - Martin, Greg

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AU - Mehta, Hemalkumar

AU - Liu, Hongfang

AU - Sidky, Hythem

AU - Awori Hayanga, J. W.

AU - Pincavitch, Jami

AU - Clark, Jaylyn

AU - Richard Harper, Jeremy

AU - Islam, Jessica

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AU - Saltz, Joel H.

AU - Buse, John

AU - Mathew, Jomol

AU - Rutter, Joni L.

AU - McMurry, Julie A.

AU - Guinney, Justin

AU - Starren, Justin

AU - Crowley, Karen

AU - Bradwell, Katie Rebecca

AU - Walters, Kellie M.

AU - Wilkins, Ken

AU - Gersing, Kenneth R.

AU - Cato, Kenrick Dwain

AU - Murray, Kimberly

AU - Kostka, Kristin

AU - Northington, Lavance

AU - Pyles, Lee Allan

AU - Misquitta, Leonie

AU - Cottrell, Lesley

AU - Portilla, Lili

AU - Deacy, Mariam

AU - Bissell, Mark M.

AU - Clark, Marshall

AU - Emmett, Mary

AU - Saltz, Mary Morrison

AU - Palchuk, Matvey B.

AU - Haendel, Melissa A.

AU - Adams, Meredith

AU - Temple-O'Connor, Meredith

AU - Kurilla, Michael G.

AU - Morris, Michele

AU - Qureshi, Nabeel

AU - Safdar, Nasia

AU - Garbarini, Nicole

AU - Sharafeldin, Noha

AU - Sadan, Ofer

AU - Francis, Patricia A.

AU - Burgoon, Penny Wung

AU - Robinson, Peter

AU - Payne, Philip R.O.

AU - Fuentes, Rafael

AU - Jawa, Randeep

AU - Erwin-Cohen, Rebecca

AU - Patel, Rena

AU - Moffitt, Richard A.

AU - Zhu, Richard L.

AU - Kamaleswaran, Rishi

AU - Hurley, Robert

AU - Miller, Robert T.

AU - Pyarajan, Saiju

AU - Michael, Sam G.

AU - Bozzette, Samuel

AU - Mallipattu, Sandeep

AU - Vedula, Satyanarayana

AU - Chapman, Scott

AU - O'Neil, Shawn T.

AU - Setoguchi, Soko

AU - Hong, Stephanie S.

AU - Johnson, Steve

AU - Bennett, Tellen D.

AU - Callahan, Tiffany

AU - Topaloglu, Umit

AU - Sheikh, Usman

AU - Gordon, Valery

AU - Subbian, Vignesh

AU - Kibbe, Warren A.

AU - Hernandez, Wenndy

AU - Beasley, Will

AU - Cooper, Will

AU - Hillegass, William

AU - Zhang, Xiaohan Tanner

PY - 2023

Y1 - 2023

N2 - National COVID Cohort Collaborative (N3C) enclave provides health researchers with a rich dataset from 76 contributing clinical sites. However, the harmonized data lacks certain details available in sites' local electronic health records (EHRs), such as the principal diagnosis code for reported emergency department (ED) and inpatient (IP) visits. This means a principal diagnosis of COVID-19 can only be inferred by applying a time relationship between the visit dates and the record of infection and diagnosis. The purpose of this study is to perform a single-site sensitivity analysis modeled after an N3C study examining potential race-ethnicity based bias in hospitalization decisions during COVID-19 related ED visits. The analytic pipeline was first run in N3C, then reproduced locally with N3C data fields from a single-site, and finally run a third time using the additional principal diagnosis data. We find the effects of patient comorbidities and race-ethnicity groups on direct IP admittance to be consistent among the three cohorts with varying levels of statistical significance due to different sample sizes.

AB - National COVID Cohort Collaborative (N3C) enclave provides health researchers with a rich dataset from 76 contributing clinical sites. However, the harmonized data lacks certain details available in sites' local electronic health records (EHRs), such as the principal diagnosis code for reported emergency department (ED) and inpatient (IP) visits. This means a principal diagnosis of COVID-19 can only be inferred by applying a time relationship between the visit dates and the record of infection and diagnosis. The purpose of this study is to perform a single-site sensitivity analysis modeled after an N3C study examining potential race-ethnicity based bias in hospitalization decisions during COVID-19 related ED visits. The analytic pipeline was first run in N3C, then reproduced locally with N3C data fields from a single-site, and finally run a third time using the additional principal diagnosis data. We find the effects of patient comorbidities and race-ethnicity groups on direct IP admittance to be consistent among the three cohorts with varying levels of statistical significance due to different sample sizes.

UR - http://www.scopus.com/inward/record.url?scp=85161859782&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85161859782&partnerID=8YFLogxK

U2 - 10.1109/SIEDS58326.2023.10137801

DO - 10.1109/SIEDS58326.2023.10137801

M3 - Conference contribution

AN - SCOPUS:85161859782

T3 - 2023 Systems and Information Engineering Design Symposium, SIEDS 2023

SP - 297

EP - 302

BT - 2023 Systems and Information Engineering Design Symposium, SIEDS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 27 April 2023 through 28 April 2023

ER -

Investigating the Impact of Temporal Labeling of Emergency Department Visits for COVID-19: Comparing Healthcare Disparities Analyses Using Comprehensive, Single-Site Data with National COVID Cohort Collaborative (N3C) Data

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