Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources

Mohamed Elshal, Hazim El-Mounayri, Rapeepan Promyoo, Alice Mitchell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A simulation optimization approach is proposed through the collaboration with a mid-size hospital in central Indiana state namely, Eskenazi Health; in order to find the optimum allocation of their human resources and estimate the optimal investment in resourcing budget. The discrete-event simulation model is developed using Tecnomatix® plant simulation from Siemens with the aid of Genetic Algorithm (GA) optimization tool. Sensitivity analysis is conducted on two types of patients that come to the ED: high acuity and low acuity patients as a function of the ED staffing budget, while human resources are considered as a control variable in our experiment. The problem is analyzed by addressing the effect of allocating resources, and the effect of adding more staff on the average length of stay (LOS) for patients during their treatment. The simulation is validated in two ways. First, optimization results are compared with the predictions from a mathematical-based optimization tool, namely I Sight®. Second, the model is validated by comparing its predictions with the output data from the ED; as well as through feedback from ED stakeholders and ED management. Our approach aims at helping the ED management and chief physicians in making the decision to invest in their human resources; where the optimum investment is determined from simulation output to be 30% percent additional human resourcing budget.

Original languageEnglish (US)
Title of host publication2016 Simulation Innovation Workshop, SIW 2016
PublisherSISO - Simulation Interoperability Standards Organization
StatePublished - 2016
Event1st Simulation Innovation Workshop, SIW 2016 - Orlando, United States
Duration: Sep 12 2016Sep 16 2016

Other

Other1st Simulation Innovation Workshop, SIW 2016
CountryUnited States
CityOrlando
Period9/12/169/16/16

Fingerprint

Human Resources
Emergency
Personnel
Optimization
Simulation
Simulation Optimization
Optimal Investment
Prediction
Output
Discrete Event Simulation
Percent
Sensitivity Analysis
Discrete event simulation
Simulation Model
Health
Genetic Algorithm
Sensitivity analysis
Resources
Genetic algorithms
Feedback

Keywords

  • Data analysis
  • ED operation
  • Resource management
  • Simulation optimization
  • Systems engineering
  • Workflow modeling

ASJC Scopus subject areas

  • Modeling and Simulation

Cite this

Elshal, M., El-Mounayri, H., Promyoo, R., & Mitchell, A. (2016). Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources. In 2016 Simulation Innovation Workshop, SIW 2016 SISO - Simulation Interoperability Standards Organization.

Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources. / Elshal, Mohamed; El-Mounayri, Hazim; Promyoo, Rapeepan; Mitchell, Alice.

2016 Simulation Innovation Workshop, SIW 2016. SISO - Simulation Interoperability Standards Organization, 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Elshal, M, El-Mounayri, H, Promyoo, R & Mitchell, A 2016, Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources. in 2016 Simulation Innovation Workshop, SIW 2016. SISO - Simulation Interoperability Standards Organization, 1st Simulation Innovation Workshop, SIW 2016, Orlando, United States, 9/12/16.
Elshal M, El-Mounayri H, Promyoo R, Mitchell A. Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources. In 2016 Simulation Innovation Workshop, SIW 2016. SISO - Simulation Interoperability Standards Organization. 2016
Elshal, Mohamed ; El-Mounayri, Hazim ; Promyoo, Rapeepan ; Mitchell, Alice. / Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources. 2016 Simulation Innovation Workshop, SIW 2016. SISO - Simulation Interoperability Standards Organization, 2016.
@inproceedings{04a3cd1338bd44f39e24f734172bd8be,
title = "Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources",
abstract = "A simulation optimization approach is proposed through the collaboration with a mid-size hospital in central Indiana state namely, Eskenazi Health; in order to find the optimum allocation of their human resources and estimate the optimal investment in resourcing budget. The discrete-event simulation model is developed using Tecnomatix{\circledR} plant simulation from Siemens™ with the aid of Genetic Algorithm (GA) optimization tool. Sensitivity analysis is conducted on two types of patients that come to the ED: high acuity and low acuity patients as a function of the ED staffing budget, while human resources are considered as a control variable in our experiment. The problem is analyzed by addressing the effect of allocating resources, and the effect of adding more staff on the average length of stay (LOS) for patients during their treatment. The simulation is validated in two ways. First, optimization results are compared with the predictions from a mathematical-based optimization tool, namely I Sight{\circledR}. Second, the model is validated by comparing its predictions with the output data from the ED; as well as through feedback from ED stakeholders and ED management. Our approach aims at helping the ED management and chief physicians in making the decision to invest in their human resources; where the optimum investment is determined from simulation output to be 30{\%} percent additional human resourcing budget.",
keywords = "Data analysis, ED operation, Resource management, Simulation optimization, Systems engineering, Workflow modeling",
author = "Mohamed Elshal and Hazim El-Mounayri and Rapeepan Promyoo and Alice Mitchell",
year = "2016",
language = "English (US)",
booktitle = "2016 Simulation Innovation Workshop, SIW 2016",
publisher = "SISO - Simulation Interoperability Standards Organization",

}

TY - GEN

T1 - Application of simulation based-approach in allocation and optimization of a mid-size emergency department human resources

AU - Elshal, Mohamed

AU - El-Mounayri, Hazim

AU - Promyoo, Rapeepan

AU - Mitchell, Alice

PY - 2016

Y1 - 2016

N2 - A simulation optimization approach is proposed through the collaboration with a mid-size hospital in central Indiana state namely, Eskenazi Health; in order to find the optimum allocation of their human resources and estimate the optimal investment in resourcing budget. The discrete-event simulation model is developed using Tecnomatix® plant simulation from Siemens™ with the aid of Genetic Algorithm (GA) optimization tool. Sensitivity analysis is conducted on two types of patients that come to the ED: high acuity and low acuity patients as a function of the ED staffing budget, while human resources are considered as a control variable in our experiment. The problem is analyzed by addressing the effect of allocating resources, and the effect of adding more staff on the average length of stay (LOS) for patients during their treatment. The simulation is validated in two ways. First, optimization results are compared with the predictions from a mathematical-based optimization tool, namely I Sight®. Second, the model is validated by comparing its predictions with the output data from the ED; as well as through feedback from ED stakeholders and ED management. Our approach aims at helping the ED management and chief physicians in making the decision to invest in their human resources; where the optimum investment is determined from simulation output to be 30% percent additional human resourcing budget.

AB - A simulation optimization approach is proposed through the collaboration with a mid-size hospital in central Indiana state namely, Eskenazi Health; in order to find the optimum allocation of their human resources and estimate the optimal investment in resourcing budget. The discrete-event simulation model is developed using Tecnomatix® plant simulation from Siemens™ with the aid of Genetic Algorithm (GA) optimization tool. Sensitivity analysis is conducted on two types of patients that come to the ED: high acuity and low acuity patients as a function of the ED staffing budget, while human resources are considered as a control variable in our experiment. The problem is analyzed by addressing the effect of allocating resources, and the effect of adding more staff on the average length of stay (LOS) for patients during their treatment. The simulation is validated in two ways. First, optimization results are compared with the predictions from a mathematical-based optimization tool, namely I Sight®. Second, the model is validated by comparing its predictions with the output data from the ED; as well as through feedback from ED stakeholders and ED management. Our approach aims at helping the ED management and chief physicians in making the decision to invest in their human resources; where the optimum investment is determined from simulation output to be 30% percent additional human resourcing budget.

KW - Data analysis

KW - ED operation

KW - Resource management

KW - Simulation optimization

KW - Systems engineering

KW - Workflow modeling

UR - http://www.scopus.com/inward/record.url?scp=85018995143&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018995143&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85018995143

BT - 2016 Simulation Innovation Workshop, SIW 2016

PB - SISO - Simulation Interoperability Standards Organization

ER -