Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation
The installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) mod...
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doaj-20c72019e7c7406f917db33ec238b0cf2020-11-25T03:23:05ZengMDPI AGProcesses2227-97172020-06-01866066010.3390/pr8060660Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event SimulationFélix Badilla-Murillo0Bernal Vargas-Vargas1Oscar Víquez-Acuña2Justo García-Sanz-Calcedo3Industrial Production Engineering, Instituto Tecnológico de Costa Rica, San Carlos 21002, Costa RicaIndustrial Production Engineering, Instituto Tecnológico de Costa Rica, San Carlos 21002, Costa RicaComputer Engineering, Instituto Tecnológico de Costa Rica, San Carlos 21002, Costa RicaEngineering Projects Area, University of Extremadura, 06007 Badajoz, SpainThe installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) model based on historical variables from the current system was created using computer software. The authors analyzed 2044 procedures performed between 2014 and 2015 in a hospital in San José, Costa Rica. The model was statistically validated to determine that it does not significantly differ from the current system, considering the DMAIC stages for continuous process improvement. In the current scenario, resource utilization is 0.99, and the waiting list increases every month. The results showed that the current capacity of the service could be doubled, and that resource utilization could be reduced to 0.64 and waiting times by 94%. An increase in service efficiency could be achieved by shortening maximum waiting times from 6.75 days to 3.70 h. DES simulation, therefore, allows optimizing of the use of healthcare systems’ resources and hospital management.https://www.mdpi.com/2227-9717/8/6/660discrete events simulationhospital managementprocess modelinstalled productive capacityhealthcare engineering |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Félix Badilla-Murillo Bernal Vargas-Vargas Oscar Víquez-Acuña Justo García-Sanz-Calcedo |
spellingShingle |
Félix Badilla-Murillo Bernal Vargas-Vargas Oscar Víquez-Acuña Justo García-Sanz-Calcedo Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation Processes discrete events simulation hospital management process model installed productive capacity healthcare engineering |
author_facet |
Félix Badilla-Murillo Bernal Vargas-Vargas Oscar Víquez-Acuña Justo García-Sanz-Calcedo |
author_sort |
Félix Badilla-Murillo |
title |
Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation |
title_short |
Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation |
title_full |
Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation |
title_fullStr |
Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation |
title_full_unstemmed |
Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation |
title_sort |
analysis of the installed productive capacity in a medical angiography room through discrete event simulation |
publisher |
MDPI AG |
series |
Processes |
issn |
2227-9717 |
publishDate |
2020-06-01 |
description |
The installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) model based on historical variables from the current system was created using computer software. The authors analyzed 2044 procedures performed between 2014 and 2015 in a hospital in San José, Costa Rica. The model was statistically validated to determine that it does not significantly differ from the current system, considering the DMAIC stages for continuous process improvement. In the current scenario, resource utilization is 0.99, and the waiting list increases every month. The results showed that the current capacity of the service could be doubled, and that resource utilization could be reduced to 0.64 and waiting times by 94%. An increase in service efficiency could be achieved by shortening maximum waiting times from 6.75 days to 3.70 h. DES simulation, therefore, allows optimizing of the use of healthcare systems’ resources and hospital management. |
topic |
discrete events simulation hospital management process model installed productive capacity healthcare engineering |
url |
https://www.mdpi.com/2227-9717/8/6/660 |
work_keys_str_mv |
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