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An agent-based simulation combined with group decision-making technique for improving the performance of an emergency department
Yousefi, M; Ferreira, RPM.
  • Yousefi, M; Universidade Federal de Minas Gerais. Departamento de Engenharia Mecânica. Belo Horizonte. BR
  • Ferreira, RPM; Universidade Federal de Minas Gerais. Departamento de Engenharia Mecânica. Belo Horizonte. BR
Braz. j. med. biol. res ; 50(5): e5955, 2017. tab, graf
Article in English | LILACS | ID: biblio-839300
ABSTRACT
This study presents an agent-based simulation modeling in an emergency department. In a traditional approach, a supervisor (or a manager) allocates the resources (receptionist, nurses, doctors, etc.) to different sections based on personal experience or by using decision-support tools. In this study, each staff agent took part in the process of allocating resources based on their observation in their respective sections, which gave the system the advantage of utilizing all the available human resources during the workday by being allocated to a different section. In this simulation, unlike previous studies, all staff agents took part in the decision-making process to re-allocate the resources in the emergency department. The simulation modeled the behavior of patients, receptionists, triage nurses, emergency room nurses and doctors. Patients were able to decide whether to stay in the system or leave the department at any stage of treatment. In order to evaluate the performance of this approach, 6 different scenarios were introduced. In each scenario, various key performance indicators were investigated before and after applying the group decision-making. The outputs of each simulation were number of deaths, number of patients who leave the emergency department without being attended, length of stay, waiting time and total number of discharged patients from the emergency department. Applying the self-organizing approach in the simulation showed an average of 12.7 and 14.4% decrease in total waiting time and number of patients who left without being seen, respectively. The results showed an average increase of 11.5% in total number of discharged patients from emergency department.
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Full text: Available Index: LILACS (Americas) Main subject: Computer Simulation / Decision Making, Computer-Assisted / Decision Support Techniques / Emergency Service, Hospital Type of study: Prognostic study Limits: Humans Language: English Journal: Braz. j. med. biol. res Journal subject: Biology / Medicine Year: 2017 Type: Article / Project document Affiliation country: Brazil Institution/Affiliation country: Universidade Federal de Minas Gerais/BR

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Full text: Available Index: LILACS (Americas) Main subject: Computer Simulation / Decision Making, Computer-Assisted / Decision Support Techniques / Emergency Service, Hospital Type of study: Prognostic study Limits: Humans Language: English Journal: Braz. j. med. biol. res Journal subject: Biology / Medicine Year: 2017 Type: Article / Project document Affiliation country: Brazil Institution/Affiliation country: Universidade Federal de Minas Gerais/BR