Service optimization with patient satisfaction in healthcare systems

Abstract

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.

Keywords:

• healthcare
• service systems
• discrete event simulation
• simulation optimization
• meta-heuristics
• Genetic Algorithm