Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits

Atefehsadat Haghighathoseini; Janusz Wojtusiak; Nirup M. Menon; Hua Min; Cara Frankenfeld; Timothy Leslie; Adam B. Wilcox; Adam M. Lee; Alexis Graves; Alfred Anzalone; Amin Manna; Amit Saha; Amy Olex; Andrea Zhou; 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; Don Brown; 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; Joel Saltz; Johanna Loomba; 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/BigData62323.2024.10825471

Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits

Atefehsadat Haghighathoseini, Janusz Wojtusiak, Nirup M. Menon, Hua Min, Cara Frankenfeld, Timothy Leslie, Adam B. Wilcox, Adam M. Lee, Alexis Graves, Alfred Anzalone, Amin Manna, Amit Saha, Amy Olex, Andrea Zhou, Andrew E. Williams, Andrew Southerland, Andrew T. Girvin, Anita Walden, Anjali A. Sharathkumar, Benjamin AmorBenjamin 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, Don Brown, 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, Joel Saltz, Johanna Loomba, 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

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

Abstract

The COVID-19 pandemic has had a disproportionate impact on certain racial and ethnic groups, resulting in significant health outcome disparities. The National COVID Cohort Collaborative (N3C) provides a valuable resource for exploring these disparities through big data analytics. This study belongs to a broader work that examines decisions made during data processing and their impact on the analyses performed. Central to our analysis is the introduction of the Continuous Inpatient Encounter (CIE) concept - a novel method we propose for aggregating inpatient visits. By utilizing big data analytics, we aim to identify potential disparities in CIE rates among different racial groups. The results of this study are critical for enhancing the equity of data-driven decision-making in healthcare and for addressing the racial disparities observed in COVID-19 outcomes.

Original language	English
Title of host publication	Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024
Editors	Wei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6452-6459
Number of pages	8
ISBN (Electronic)	9798350362480
DOIs	https://doi.org/10.1109/BigData62323.2024.10825471
State	Published - 2024
Event	2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States Duration: Dec 15 2024 → Dec 18 2024

Publication series

Name	Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024

Conference

Conference	2024 IEEE International Conference on Big Data, BigData 2024
Country/Territory	United States
City	Washington
Period	12/15/24 → 12/18/24

Keywords

Big Data Analytics
Data Processing
Decision-Making
Inpatient Encounter
Macrovisits
National COVID Cohort Collaborative (N3C)
Racial Disparities

Access to Document

10.1109/BigData62323.2024.10825471

Cite this

Haghighathoseini, A., Wojtusiak, J., Menon, N. M., Min, H., Frankenfeld, C., Leslie, T., Wilcox, A. B., Lee, A. M., Graves, A., Anzalone, A., Manna, A., Saha, A., Olex, A., Zhou, A., Williams, A. E., Southerland, A., Girvin, A. T., Walden, A., Sharathkumar, A. A., ... Zhang, X. T. (2024). Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits. In W. Ding, C.-T. Lu, F. Wang, L. Di, K. Wu, J. Huan, R. Nambiar, J. Li, F. Ilievski, R. Baeza-Yates, & X. Hu (Eds.), Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024 (pp. 6452-6459). (Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData62323.2024.10825471

Haghighathoseini, Atefehsadat ; Wojtusiak, Janusz ; Menon, Nirup M. et al. / Big Data Decision-Making and Racial Disparities : A Case Study Among COVID-19 Inpatient Visits. Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024. editor / Wei Ding ; Chang-Tien Lu ; Fusheng Wang ; Liping Di ; Kesheng Wu ; Jun Huan ; Raghu Nambiar ; Jundong Li ; Filip Ilievski ; Ricardo Baeza-Yates ; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 6452-6459 (Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024).

@inproceedings{9379de8390f64ed9bf46edcf0fad228b,

title = "Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits",

abstract = "The COVID-19 pandemic has had a disproportionate impact on certain racial and ethnic groups, resulting in significant health outcome disparities. The National COVID Cohort Collaborative (N3C) provides a valuable resource for exploring these disparities through big data analytics. This study belongs to a broader work that examines decisions made during data processing and their impact on the analyses performed. Central to our analysis is the introduction of the Continuous Inpatient Encounter (CIE) concept - a novel method we propose for aggregating inpatient visits. By utilizing big data analytics, we aim to identify potential disparities in CIE rates among different racial groups. The results of this study are critical for enhancing the equity of data-driven decision-making in healthcare and for addressing the racial disparities observed in COVID-19 outcomes.",

keywords = "Big Data Analytics, Data Processing, Decision-Making, Inpatient Encounter, Macrovisits, National COVID Cohort Collaborative (N3C), Racial Disparities",

author = "Atefehsadat Haghighathoseini and Janusz Wojtusiak and Menon, \{Nirup M.\} and Hua Min and Cara Frankenfeld and Timothy Leslie and Wilcox, \{Adam B.\} and Lee, \{Adam M.\} and Alexis Graves and Alfred Anzalone and Amin Manna and Amit Saha and Amy Olex and Andrea Zhou 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 Don Brown 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 Hayanga, \{J. W.Awori\} and Jami Pincavitch and Jaylyn Clark and Harper, \{Jeremy Richard\} and Jessica Islam and Jin Ge and Joel Gagnier and Saltz, \{Joel H.\} and Joel Saltz and Johanna Loomba 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} 2024 IEEE.; 2024 IEEE International Conference on Big Data, BigData 2024 ; Conference date: 15-12-2024 Through 18-12-2024",

year = "2024",

doi = "10.1109/BigData62323.2024.10825471",

language = "English",

series = "Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024",

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

pages = "6452--6459",

editor = "Wei Ding and Chang-Tien Lu and Fusheng Wang and Liping Di and Kesheng Wu and Jun Huan and Raghu Nambiar and Jundong Li and Filip Ilievski and Ricardo Baeza-Yates and Xiaohua Hu",

booktitle = "Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024",

}

Haghighathoseini, A, Wojtusiak, J, Menon, NM, Min, H, Frankenfeld, C, Leslie, T, Wilcox, AB, Lee, AM, Graves, A, Anzalone, A, Manna, A, Saha, A, Olex, A, Zhou, 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, Brown, 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, Hayanga, JWA, Pincavitch, J, Clark, J, Harper, JR, Islam, J, Ge, J, Gagnier, J, Saltz, JH, Saltz, J, Loomba, J, 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 2024, Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits. in W Ding, C-T Lu, F Wang, L Di, K Wu, J Huan, R Nambiar, J Li, F Ilievski, R Baeza-Yates & X Hu (eds), Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024. Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024, Institute of Electrical and Electronics Engineers Inc., pp. 6452-6459, 2024 IEEE International Conference on Big Data, BigData 2024, Washington, United States, 12/15/24. https://doi.org/10.1109/BigData62323.2024.10825471

Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits. / Haghighathoseini, Atefehsadat; Wojtusiak, Janusz; Menon, Nirup M. et al.
Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024. ed. / Wei Ding; Chang-Tien Lu; Fusheng Wang; Liping Di; Kesheng Wu; Jun Huan; Raghu Nambiar; Jundong Li; Filip Ilievski; Ricardo Baeza-Yates; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2024. p. 6452-6459 (Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024).

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

TY - GEN

T1 - Big Data Decision-Making and Racial Disparities

T2 - 2024 IEEE International Conference on Big Data, BigData 2024

AU - Haghighathoseini, Atefehsadat

AU - Wojtusiak, Janusz

AU - Menon, Nirup M.

AU - Min, Hua

AU - Frankenfeld, Cara

AU - Leslie, Timothy

AU - Wilcox, Adam B.

AU - Lee, Adam M.

AU - Graves, Alexis

AU - Anzalone, Alfred

AU - Manna, Amin

AU - Saha, Amit

AU - Olex, Amy

AU - Zhou, Andrea

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

AU - Dillon, Christopher

AU - Wu, Chunlei

AU - Schmitt, Clare

AU - Takemoto, Cliff

AU - Housman, Dan

AU - Gabriel, Davera

AU - Eichmann, David A.

AU - Mazzotti, Diego

AU - Brown, Don

AU - Boudreau, Eilis

AU - Hill, Elaine

AU - Zampino, Elizabeth

AU - Marti, Emily Carlson

AU - Pfaff, Emily R.

AU - French, Evan

AU - Koraishy, Farrukh M.

AU - Mariona, Federico

AU - Prior, Fred

AU - Sokos, George

AU - Martin, Greg

AU - Lehmann, Harold

AU - Spratt, Heidi

AU - Mehta, Hemalkumar

AU - Liu, Hongfang

AU - Sidky, Hythem

AU - Hayanga, J. W.Awori

AU - Pincavitch, Jami

AU - Clark, Jaylyn

AU - Harper, Jeremy Richard

AU - Islam, Jessica

AU - Ge, Jin

AU - Gagnier, Joel

AU - Saltz, Joel H.

AU - Saltz, Joel

AU - Loomba, Johanna

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 - 2024

Y1 - 2024

N2 - The COVID-19 pandemic has had a disproportionate impact on certain racial and ethnic groups, resulting in significant health outcome disparities. The National COVID Cohort Collaborative (N3C) provides a valuable resource for exploring these disparities through big data analytics. This study belongs to a broader work that examines decisions made during data processing and their impact on the analyses performed. Central to our analysis is the introduction of the Continuous Inpatient Encounter (CIE) concept - a novel method we propose for aggregating inpatient visits. By utilizing big data analytics, we aim to identify potential disparities in CIE rates among different racial groups. The results of this study are critical for enhancing the equity of data-driven decision-making in healthcare and for addressing the racial disparities observed in COVID-19 outcomes.

AB - The COVID-19 pandemic has had a disproportionate impact on certain racial and ethnic groups, resulting in significant health outcome disparities. The National COVID Cohort Collaborative (N3C) provides a valuable resource for exploring these disparities through big data analytics. This study belongs to a broader work that examines decisions made during data processing and their impact on the analyses performed. Central to our analysis is the introduction of the Continuous Inpatient Encounter (CIE) concept - a novel method we propose for aggregating inpatient visits. By utilizing big data analytics, we aim to identify potential disparities in CIE rates among different racial groups. The results of this study are critical for enhancing the equity of data-driven decision-making in healthcare and for addressing the racial disparities observed in COVID-19 outcomes.

KW - Big Data Analytics

KW - Data Processing

KW - Decision-Making

KW - Inpatient Encounter

KW - Macrovisits

KW - National COVID Cohort Collaborative (N3C)

KW - Racial Disparities

UR - http://www.scopus.com/inward/record.url?scp=85218057887&partnerID=8YFLogxK

U2 - 10.1109/BigData62323.2024.10825471

DO - 10.1109/BigData62323.2024.10825471

M3 - Conference contribution

AN - SCOPUS:85218057887

T3 - Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024

SP - 6452

EP - 6459

BT - Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024

A2 - Ding, Wei

A2 - Lu, Chang-Tien

A2 - Wang, Fusheng

A2 - Di, Liping

A2 - Wu, Kesheng

A2 - Huan, Jun

A2 - Nambiar, Raghu

A2 - Li, Jundong

A2 - Ilievski, Filip

A2 - Baeza-Yates, Ricardo

A2 - Hu, Xiaohua

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 15 December 2024 through 18 December 2024

ER -

Haghighathoseini A, Wojtusiak J, Menon NM, Min H, Frankenfeld C, Leslie T et al. Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits. In Ding W, Lu CT, Wang F, Di L, Wu K, Huan J, Nambiar R, Li J, Ilievski F, Baeza-Yates R, Hu X, editors, Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024. Institute of Electrical and Electronics Engineers Inc. 2024. p. 6452-6459. (Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024). doi: 10.1109/BigData62323.2024.10825471

Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits

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