INTELLIGENT APPOINTMENT SCHEDULING TO REDUCE TURNAROUND TIME (TAT)

Abstract

Appointment system is employed in many different custom service industries to optimize the utilization of resources and to minimize the overall waiting time of the customers. Appointment scheduling is thus an important tool in the clinics to regulate the flow and availability of resources, including human resources (doctors and nurses) and physical resources (testing machines). An optimal appointment scheduling system can effectively balance doctor idling and doctor tardiness with respect to the patient waiting time. In this thesis, we proposed a series of appointment strategies based on patient classification of new patient and repeat patient, as well as their service requirement sequence in the clinic. The service durations and patient classification profile are derived from real data from the Atrium Eye Clinic of Tan Tock Sing Hospital. The objective of our research is to find an optimal appoint scheduling strategy that effectively utilizes the doctors and keeps the patient turnaround time in the clinic as short as possible. A simplified simulation model is constructed to test and compare the various strategies in the contest of single doctor’s session, load balancing and multiple doctors’ session. Recommendations are given based on these empirical finding.