An integrated algorithm for performance optimization of neurosurgical ICUs. (January 2016)

• Record Type: Journal Article
• Authors: Azadeh, Ali; Tohidi, Hossein; Zarrin, Mansour; Pashapour, Shima; Moghaddam, Mohsen
• Is Part Of: Expert systems with applications. Volume 43(2016)
• Page Start: 142
• Page End: 153
• Publication Date: 2016-01
• Subjects: Intensive care unit (ICU) -- Performance optimization -- Computer simulation -- Data envelopment analysis (DEA); Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2015.08.042
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: The aim of this study is performance optimization of neurosurgical ICUs. This study presents an integrated approach based on computer simulation and DEA. The required data is collected from a large hospital in Tehran, Iran. This approach can be generalized to any hospital organization. Previous studies did not incorporate all stated indicators considered in this study. Abstract: This study presents an integrated simulation and data envelopment analysis (DEA) approach to increase the quality of service in a neurosurgical intensive care unit (ICU). The aim of this study is to capture the main factors which have negatively affects the patients' satisfactions and figure out their optimized levels. In order to avoid any interruption in ICU's routine functions and being able to convince the hospital's principals about the project's outcomes, a simulation model is developed and run for different scenarios. Then DEA is used to compare the outputs of different scenarios. These scenarios are generated by observing the effects of various parameters such as lengthening or shortening treatment times, decreasing or increasing patient volumes and removing or adding staff members. As the best of our knowledge, this is the first study that presents an integrated approach based on computer simulation and DEA to concurrently incorporate the stated factors and parameters for optimization of complex ICUs in developing countries. Therefore, the results of this study are more precise and reliable than previous studies because of concurrent consideration of the stated factors.