Design of a Patient-Centered Appointment Scheduling with Artificial Neural Network and Discrete Event Simulation

Abstract

Quality of medical services is even more critical than ever in a highly competitive health care industry. Long waiting time is a major source of patient dissatisfaction, thus, the issue of how to reduce waiting time to improve service quality is very important. A well-designed appointment scheduling system can effectively shorten the patient waiting time and enhance their satisfaction. This study aims to propose a framework for individualized outpatient appointment scheduling (OAS) in a dental clinic which composed of one attending dentist and two resident dentists. To design the OAS, firstly, the prediction model of the treatment duration of an individual patient was established by using artificial neural network. Secondly, discrete event simulation method was used to develop the simulation model which simulates the operations of the studied dental clinic. Finally, the established simulation model was used to evaluate the performance of the appointment scheduling. The proposed model consists of numbers of main features: 1) the service providers composed of multiple dentists with different professional competence levels; 2) there are two types of patients (return and not-return patients); 3) patient no-shows was considered; and 4) a variety of medical treatments (requiring different treatment time) are provided to the patients. The results of the study show that the proposed OAS can effectively improve the service performance of the dental clinic, this could be caused by patient’s characteristics were taken into consideration of building an appropriated appointment interval.