Gorkem SariyerMustafa Gökalp Atamanİlker Kızıloğlu2025-10-06202020479700, 204797192047-97002047-971910.1080/20479700.2018.1489992https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098883072&doi=10.1080%2F20479700.2018.1489992&partnerID=40&md5=f01fee736ccc98724e14d24d5287486ahttps://gcris.yasar.edu.tr/handle/123456789/9274Background: Due to the persistent increase inpatient volumes of emergency departments improving the timeliness of emergency care delivery has become more important from an operational viewpoint. Objectives: To determine the main factors affecting length of stay (LOS) in an ED of a large-scale training hospital. Methods: This was a retrospective study set in an urban ED. The outcome variable of the study was LOS, demographic status-based and time-based predictor variables were gender age arrival type diagnosis month day of the week and period of the day. The descriptive statistics are presented. The hypotheses of this study were tested with an independent group t-test and ANOVA. A multivariate linear regression model was built to identify the dependence of LOS on the predictor variables. Results: LOS significantly differed based on diagnosis day of the week and period of the day. Weekends and evening periods had higher ED volumes and a decrease in mean LOS. In the regression model with the exception of month all predictor variables were observed to be significant. As a result it is concluded that understanding time based factors and preparing the staffing schedule according to these could improve the timeliness of emergency care delivery. © 2020 Elsevier B.V. All rights reserved.EnglishEmergency Department, Hospital, Length Of Stay, Operations Management, Time-based Factors, Analysis Of Variance, Article, Controlled Study, Demography, Emergency Care, Emergency Ward, Female, Gender, Human, Length Of Stay, Linear Regression Analysis, Male, Outcome Variable, Predictor Variable, Retrospective Study, Timelinessanalysis of variance, article, controlled study, demography, emergency care, emergency ward, female, gender, human, length of stay, linear regression analysis, male, outcome variable, predictor variable, retrospective study, timelinessArticle