Optimization of Teleconsultation Using Discrete-Event Simulation from a Data-Driven Perspective

Background: Teleconsultation plays an increasingly important role to solve the health care problem in rural areas around the world. Teleconsultation resource optimization has become a new research topic. Materials and Methods: Given the complex teleconsultation process was difficult to be described by mathematical methods, a queuing simulation model was developed based on the data and teleconsultation empirical flow of Henan Telemedicine Center of China (HTCC) and we used kernel density estimation to solve the problem of arrival rate and service rate of teleconsultation. The data obtained from HTCC included 21,295 teleconsultation records over a 1-year period (February 27, 2016-March 25, 2017). Results: The average waiting time (WT) that primary hospitals requested for teleconsultation was obtained by simulation and compared with empirical average WT to verify this model. We found that Department of Internal Medicine (DIM) WT was the highest and we searched the optimized combination of teleconsultation rooms and DIM experts by sensitivity analyses. Conclusions: The existing resource allocation was not optimal and the hospital managers can improve it to reduce the hospitals' operating costs and the patients' waiting costs. We suggested that the teleconsultation rooms needed at least four and the DIM experts could increase from three to four.