Browsing by Author "Ataman, Mustafa Gökalp"

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Citation - Scopus: 2
An (s S) inventory optimization problem: A case study for a hospital
(IGI Global, 2019) Gizem Sağol; Gorkem Sariyer; Banu Yetkin Yetkin Ekren; Mustafa Gökalp Ataman; Ataman, Mustafa Gökalp; Sariyer, Görkem; Sağol, Gizem; Ekren, Banu Yetkin
Inventory management is one essential lever to use the resources efficiently. However managing inventories in hospitals is a challenging task because of the several issues: a high service level of medical supplies is required under the unpredictable demand medical products constitute a significant portion of the overall costs and the management of these supplies requires considerable effort to check the levels to track usage and to distribute them. Therefore it is pertinence to apply operations research tools to cope with the managerial issues of the hospital inventory system. In this chapter the authors implement an (s S) inventory model by using simulation in a case study of a hospital in Izmir Turkey. They aim to analyze the unpredictable nature of demand of medical supplies in this hospital and its implications on the developed inventory policy. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 18
Citation - Scopus: 19
Factors affecting length of stay in the emergency department: A research from an operational viewpoint
(ROUTLEDGE JOURNALS TAYLOR & FRANCIS LTD, 2018-06-27) Gorkem Sariyer; Mustafa Gokalp Ataman; Ilker Kiziloglu; Ataman, Mustafa Gökalp; Sarıyer, Görkem; Kızıloğlu, İlker
Background: 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.