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Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes. / Patel, Pankaj C.; Tsionas, Mike G.; Devaraj, Srikant et al.
In: PLoS One, Vol. 18, No. 10, 0286210, 26.10.2023.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Patel, PC, Tsionas, MG, Devaraj, S & Khan, MM (ed.) 2023, 'Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes', PLoS One, vol. 18, no. 10, 0286210. https://doi.org/10.1371/journal.pone.0286210

APA

Patel, P. C., Tsionas, M. G., Devaraj, S., & Khan, M. M. (Ed.) (2023). Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes. PLoS One, 18(10), Article 0286210. https://doi.org/10.1371/journal.pone.0286210

Vancouver

Patel PC, Tsionas MG, Devaraj S, Khan MM, (ed.). Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes. PLoS One. 2023 Oct 26;18(10):0286210. doi: 10.1371/journal.pone.0286210

Author

Patel, Pankaj C. ; Tsionas, Mike G. ; Devaraj, Srikant et al. / Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes. In: PLoS One. 2023 ; Vol. 18, No. 10.

Bibtex

@article{3eae6c5bc9344aa48db5eddd4e92722d,
title = "Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes",
abstract = "Managing flexibility in the relative bed allocation for COVID-19 and non-COVID-19 patients was a key challenge for hospitals during the COVID-19 pandemic. Based on organizational information processing theory (OIPT), we propose that the local electronic health record (EHR) systems could improve patient outcomes through improved bed allocation in the local area. In an empirical analysis of county-level weekly hospital data in the US, relative capacity of beds in hospitals with higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 death rate at the county-level. Testing for cross-state variation in non-pharmaceutical interventions along contiguous county border-pair analysis to control for spatial correlation varying between state variations in non-pharmaceutical intervention policies, 2SLS analysis using quality ratings, and using foot-traffic data at the US hospitals our findings are generally supported. The findings have implications for policymakers and stakeholders of the local healthcare supply chains and EHR systems.",
author = "Patel, {Pankaj C.} and Tsionas, {Mike G.} and Srikant Devaraj and Khan, {M. Mahmud}",
year = "2023",
month = oct,
day = "26",
doi = "10.1371/journal.pone.0286210",
language = "English",
volume = "18",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "10",

}

RIS

TY - JOUR

T1 - Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes

AU - Patel, Pankaj C.

AU - Tsionas, Mike G.

AU - Devaraj, Srikant

A2 - Khan, M. Mahmud

PY - 2023/10/26

Y1 - 2023/10/26

N2 - Managing flexibility in the relative bed allocation for COVID-19 and non-COVID-19 patients was a key challenge for hospitals during the COVID-19 pandemic. Based on organizational information processing theory (OIPT), we propose that the local electronic health record (EHR) systems could improve patient outcomes through improved bed allocation in the local area. In an empirical analysis of county-level weekly hospital data in the US, relative capacity of beds in hospitals with higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 death rate at the county-level. Testing for cross-state variation in non-pharmaceutical interventions along contiguous county border-pair analysis to control for spatial correlation varying between state variations in non-pharmaceutical intervention policies, 2SLS analysis using quality ratings, and using foot-traffic data at the US hospitals our findings are generally supported. The findings have implications for policymakers and stakeholders of the local healthcare supply chains and EHR systems.

AB - Managing flexibility in the relative bed allocation for COVID-19 and non-COVID-19 patients was a key challenge for hospitals during the COVID-19 pandemic. Based on organizational information processing theory (OIPT), we propose that the local electronic health record (EHR) systems could improve patient outcomes through improved bed allocation in the local area. In an empirical analysis of county-level weekly hospital data in the US, relative capacity of beds in hospitals with higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 death rate at the county-level. Testing for cross-state variation in non-pharmaceutical interventions along contiguous county border-pair analysis to control for spatial correlation varying between state variations in non-pharmaceutical intervention policies, 2SLS analysis using quality ratings, and using foot-traffic data at the US hospitals our findings are generally supported. The findings have implications for policymakers and stakeholders of the local healthcare supply chains and EHR systems.

U2 - 10.1371/journal.pone.0286210

DO - 10.1371/journal.pone.0286210

M3 - Journal article

VL - 18

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 10

M1 - 0286210

ER -