TY - JOUR
T1 - The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning
T2 - An Observational Cohort Study
AU - Wu, Lijuan
AU - Chen, Xuanhui
AU - Khalemsky, Anna
AU - Li, Deyang
AU - Zoubeidi, Taoufik
AU - Lauque, Dominique
AU - Alsabri, Mohammed
AU - Boudi, Zoubir
AU - Kumar, Vijaya Arun
AU - Paxton, James
AU - Tsilimingras, Dionyssios
AU - Kurland, Lisa
AU - Schwartz, David
AU - Hachimi-Idrissi, Said
AU - Camargo, Carlos A.
AU - Liu, Shan W.
AU - Savioli, Gabriele
AU - Intas, Geroge
AU - Soni, Kapil Dev
AU - Junhasavasdikul, Detajin
AU - Cabello, Jose Javier Trujillano
AU - Rathlev, Niels K.
AU - Tazarourte, Karim
AU - Slagman, Anna
AU - Christ, Michael
AU - Singer, Adam J.
AU - Lang, Eddy
AU - Ricevuti, Giovanni
AU - Li, Xin
AU - Liang, Huiying
AU - Grossman, Shamai A.
AU - Bellou, Abdelouahab
N1 - Publisher Copyright: © 2023 by the authors.
PY - 2023/7/18
Y1 - 2023/7/18
N2 - The association between emergency department (ED) length of stay (EDLOS) with in-hospital mortality (IHM) in older patients remains unclear. This retrospective study aims to delineate the relationship between EDLOS and IHM in elderly patients. From the ED patients (n = 383,586) who visited an urban academic tertiary care medical center from January 2010 to December 2016, 78,478 older patients (age (Formula presented.)) were identified and stratified into three age subgroups: 60–74 (early elderly), 75–89 (late elderly), and ≥90 years (longevous elderly). We applied multiple machine learning approaches to identify the risk correlation trends between EDLOS and IHM, as well as boarding time (BT) and IHM. The incidence of IHM increased with age: 60–74 (2.7%), 75–89 (4.5%), and ≥90 years (6.3%). The best area under the receiver operating characteristic curve was obtained by Light Gradient Boosting Machine model for age groups 60–74, 75–89, and ≥90 years, which were 0.892 (95% CI, 0.870–0.916), 0.886 (95% CI, 0.861–0.911), and 0.838 (95% CI, 0.782–0.887), respectively. Our study showed that EDLOS and BT were statistically correlated with IHM (p < 0.001), and a significantly higher risk of IHM was found in low EDLOS and high BT. The flagged rate of quality assurance issues was higher in lower EDLOS (Formula presented.) h (9.96%) vs. higher EDLOS 7 h (Formula presented.) 8 h (1.84%). Special attention should be given to patients admitted after a short stay in the ED and a long BT, and new concepts of ED care processes including specific areas and teams dedicated to older patients care could be proposed to policymakers.
AB - The association between emergency department (ED) length of stay (EDLOS) with in-hospital mortality (IHM) in older patients remains unclear. This retrospective study aims to delineate the relationship between EDLOS and IHM in elderly patients. From the ED patients (n = 383,586) who visited an urban academic tertiary care medical center from January 2010 to December 2016, 78,478 older patients (age (Formula presented.)) were identified and stratified into three age subgroups: 60–74 (early elderly), 75–89 (late elderly), and ≥90 years (longevous elderly). We applied multiple machine learning approaches to identify the risk correlation trends between EDLOS and IHM, as well as boarding time (BT) and IHM. The incidence of IHM increased with age: 60–74 (2.7%), 75–89 (4.5%), and ≥90 years (6.3%). The best area under the receiver operating characteristic curve was obtained by Light Gradient Boosting Machine model for age groups 60–74, 75–89, and ≥90 years, which were 0.892 (95% CI, 0.870–0.916), 0.886 (95% CI, 0.861–0.911), and 0.838 (95% CI, 0.782–0.887), respectively. Our study showed that EDLOS and BT were statistically correlated with IHM (p < 0.001), and a significantly higher risk of IHM was found in low EDLOS and high BT. The flagged rate of quality assurance issues was higher in lower EDLOS (Formula presented.) h (9.96%) vs. higher EDLOS 7 h (Formula presented.) 8 h (1.84%). Special attention should be given to patients admitted after a short stay in the ED and a long BT, and new concepts of ED care processes including specific areas and teams dedicated to older patients care could be proposed to policymakers.
KW - boarding time
KW - emergency department
KW - in-hospital mortality
KW - length of stay
KW - machine learning
KW - older adults
UR - http://www.scopus.com/inward/record.url?scp=85166332423&partnerID=8YFLogxK
U2 - https://doi.org/10.3390/jcm12144750
DO - https://doi.org/10.3390/jcm12144750
M3 - مقالة
C2 - 37510865
SN - 2077-0383
VL - 12
JO - Journal of Clinical Medicine
JF - Journal of Clinical Medicine
IS - 14
M1 - 4750
ER -