Service optimization with patient satisfaction in healthcare systems

Market research on services and waiting lends support to the fact that waiting for service is an undesirable phenomenon adversely affecting customer satisfaction and consequently business enterprises. The simulation optimization strategy described in this study addresses both the subjective as well...

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Published in:Journal of simulation : JOS 2009-09, Vol.3 (3), p.150-162
Main Authors: Gonsalves, T, Itoh, K
Format: Article
Language:English
Subjects:
Business and Management
Collaboration
Customer satisfaction
Customer services
Decision making
discrete event simulation
Fuzzy sets
Genetic Algorithm
healthcare
Information Systems and Communication Service
Measurement techniques
meta-heuristics
Nurses
Operations management
Operations Research/Decision Theory
Optimization
Patient satisfaction
Perceptions
Physicians
Quality management
Quality of service
service systems
Simulation
Simulation and Modeling
simulation optimization
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cited_by cdi_FETCH-LOGICAL-c363t-4a1a0465e6f424e757ddefa385677b096ee950ae2e36e991c430927e44806b123
cites cdi_FETCH-LOGICAL-c363t-4a1a0465e6f424e757ddefa385677b096ee950ae2e36e991c430927e44806b123
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container_title Journal of simulation : JOS
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creator Gonsalves, T
Itoh, K
description Market research on services and waiting lends support to the fact that waiting for service is an undesirable phenomenon adversely affecting customer satisfaction and consequently business enterprises. The simulation optimization strategy described in this study addresses both the subjective as well as the objective elements in the patients' evaluation of healthcare services. The cost function simulates the average sojourn time of the patients in the healthcare system, whereas the fuzzy constraints quantitatively estimate the overall waiting and service experience of the patients. Minimization of the cost function (objective element in the patients' evaluation of service) subject to the fuzzy constraints (subjective elements in the patients' evaluation of service) leads to an increased patient satisfaction, increased efficiency of system operation and consequently increased profits. The proposed method makes a topological cum functional model of the healthcare system, simulates the operation via discrete event simulation and optimizes it using the Genetic Algorithm.
doi_str_mv 10.1057/jos.2009.2
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subjects Business and Management
Collaboration
Customer satisfaction
Customer services
Decision making
discrete event simulation
Fuzzy sets
Genetic Algorithm
healthcare
Information Systems and Communication Service
Measurement techniques
meta-heuristics
Nurses
Operations management
Operations Research/Decision Theory
Optimization
Patient satisfaction
Perceptions
Physicians
Quality management
Quality of service
service systems
Simulation
Simulation and Modeling
simulation optimization
title Service optimization with patient satisfaction in healthcare systems
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