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Bed Capacity Planning Using Stochastic Simulation Approach in Cardiac-Surgery Department of Teaching Hospitals, Tehran, Iran



Torabipour A1, 2 ; Zeraati H3 ; Arab M2 ; Rashidian A2 ; Akbari Sari A2 ; Sarzaiem MR4
Authors
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Authors Affiliations
  1. 1. Dept. Of Health Services Management, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
  2. 2. Dept. Of Health Economics & Management, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Dept. Of Epidemiology & Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Dept. Of Cardiac Surgery, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Source: Iranian Journal of Public Health Published:2016

Abstract

Background: To determine the hospital required beds using stochastic simulation approach in cardiac surgery departments. Methods: This study was performed from Mar 2011 to Jul 2012 in three phases: First, collection data from 649 patients in cardiac surgery departments of two large teaching hospitals (in Tehran, Iran). Second, statistical analysis and formulate a multivariate linier regression model to determine factors that affect patient's length of stay. Third, develop a stochastic simulation system (from admission to discharge) based on key parameters to estimate required bed capacity. Results: Current cardiac surgery department with 33 beds can only admit patients in 90.7% of days. (4535 d) and will be required to over the 33 beds only in 9.3% of days (efficient cut off point). According to simulation method, studied cardiac surgery department will requires 41-52 beds for admission of all patients in the 12 next years. Finally, one-day reduction of length of stay lead to decrease need for two hospital beds annually. Conclusion: Variation of length of stay and its affecting factors can affect required beds. Statistic and stochastic simulation model are applied and useful methods to estimate and manage hospital beds based on key hospital parameters. © 2016 Iranian Journal of Public Health. All rights reserved.