Data Analysis of Ambient Intelligence in a Healthcare Simulation System: A Pilot Study in High-end Health Screening Process Improvement
Abstract This study aimed to reduce the total waiting time for high-end health screening processes. The subjects of this study were recruited from a health screening center in a tertiary hospital in northern Taiwan from September 2016 to February 2017 and a total of 2,342 high-end customers were collected. Arena software was used to simulate the examination process. We presented the simulation results of three different policies and compared those results to the current state. The first policy presented a predetermined proportion of customer types, in which the total waiting time was increased from 72.29 to 83.04 mins. The second policy was based on increased bottleneck resources and provided significant improvement, with the total waiting time was decreased from 72.29 to 28.39 mins. However, this policy also caused the cost to increase dramatically, while lowering the utilization of this exam station. The third policy was adjusting customer arrival times, which reduced the waiting time significantly, as the total waiting time was reduced from 72.29 to 55.02 mins. Although the wait time of this policy was slightly longer than that of the second policy, the additional cost was much lower than the second plan. Scheduled arrival intervals could help to reduce customer waiting time in the health screening department base on FIFO rule. The simulation model of this study could be utilized and the parameters could be modified to comply with different health examination centers to improve process and service quality.