The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning: An Observational Cohort Study
dc.contributor.author | Wu L. | |
dc.contributor.author | Chen X. | |
dc.contributor.author | Khalemsky A. | |
dc.contributor.author | Li D. | |
dc.contributor.author | Zoubeidi T. | |
dc.contributor.author | Lauque D. | |
dc.contributor.author | Alsabri M. | |
dc.contributor.author | Boudi Z. | |
dc.contributor.author | Kumar V.A. | |
dc.contributor.author | Paxton J. | |
dc.contributor.author | Tsilimingras D. | |
dc.contributor.author | Kurland L. | |
dc.contributor.author | Schwartz D. | |
dc.contributor.author | Hachimi-Idrissi S. | |
dc.contributor.author | Camargo C.A. | |
dc.contributor.author | Liu S.W. | |
dc.contributor.author | Savioli G. | |
dc.contributor.author | Intas G. | |
dc.contributor.author | Soni K.D. | |
dc.contributor.author | Junhasavasdikul D. | |
dc.contributor.author | Cabello J.J.T. | |
dc.contributor.author | Rathlev N.K. | |
dc.contributor.author | Tazarourte K. | |
dc.contributor.author | Slagman A. | |
dc.contributor.author | Christ M. | |
dc.contributor.author | Singer A.J. | |
dc.contributor.author | Lang E. | |
dc.contributor.author | Ricevuti G. | |
dc.contributor.author | Li X. | |
dc.contributor.author | Liang H. | |
dc.contributor.author | Grossman S.A. | |
dc.contributor.author | Bellou A. | |
dc.contributor.other | Mahidol University | |
dc.date.accessioned | 2023-08-10T18:01:42Z | |
dc.date.available | 2023-08-10T18:01:42Z | |
dc.date.issued | 2023-07-01 | |
dc.description.abstract | 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. | |
dc.identifier.citation | Journal of Clinical Medicine Vol.12 No.14 (2023) | |
dc.identifier.doi | 10.3390/jcm12144750 | |
dc.identifier.eissn | 20770383 | |
dc.identifier.scopus | 2-s2.0-85166332423 | |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/123456789/88268 | |
dc.rights.holder | SCOPUS | |
dc.subject | Medicine | |
dc.title | The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning: An Observational Cohort Study | |
dc.type | Article | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85166332423&origin=inward | |
oaire.citation.issue | 14 | |
oaire.citation.title | Journal of Clinical Medicine | |
oaire.citation.volume | 12 | |
oairecerif.author.affiliation | Hadassah Academic College | |
oairecerif.author.affiliation | Renaissance School of Medicine at Stony Brook University | |
oairecerif.author.affiliation | Guangdong Provincial People’s Hospital of Southern Medical University | |
oairecerif.author.affiliation | Athens General Hospital | |
oairecerif.author.affiliation | Universitair Ziekenhuis Gent | |
oairecerif.author.affiliation | Université Toulouse III - Paul Sabatier | |
oairecerif.author.affiliation | Fondazione IRCCS Policlinico San Matteo | |
oairecerif.author.affiliation | Charité – Universitätsmedizin Berlin | |
oairecerif.author.affiliation | Wayne State University School of Medicine | |
oairecerif.author.affiliation | Faculty of Medicine Ramathibodi Hospital, Mahidol University | |
oairecerif.author.affiliation | Università degli Studi di Pavia | |
oairecerif.author.affiliation | CHU de Lyon | |
oairecerif.author.affiliation | Hospital Universitari Arnau de Vilanova de Lleida | |
oairecerif.author.affiliation | All India Institute of Medical Sciences, New Delhi | |
oairecerif.author.affiliation | United Arab Emirates University | |
oairecerif.author.affiliation | Örebro Universitet | |
oairecerif.author.affiliation | Brookdale University Hospital and Medical Center | |
oairecerif.author.affiliation | Bar-Ilan University | |
oairecerif.author.affiliation | Harvard Medical School | |
oairecerif.author.affiliation | University of Massachusetts Chan Medical School | |
oairecerif.author.affiliation | Cumming School of Medicine | |
oairecerif.author.affiliation | Dr. Suliman Alhabib Hospital | |
oairecerif.author.affiliation | Global Network on Emergency Medicine |