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

Area of Science:

• Healthcare Management
• Operations Research
• Telemedicine

Background:

• Teleconsultation is crucial for rural healthcare access.
• Optimizing teleconsultation resources is a growing research area.
• Complex processes challenge traditional mathematical modeling.

Purpose of the Study:

• To develop a queuing simulation model for teleconsultation resource optimization.
• To analyze teleconsultation data from the Henan Telemedicine Center of China (HTCC).
• To identify bottlenecks and optimize resource allocation to reduce waiting times.

Main Methods:

• Developed a queuing simulation model based on HTCC data (21,295 records).
• Utilized kernel density estimation for arrival and service rates.
• Validated the model by comparing simulated and empirical average waiting times.
• Performed sensitivity analyses to determine optimal resource combinations.

Main Results:

• The simulation model accurately reflected empirical average waiting times.
• The Department of Internal Medicine (DIM) experienced the highest waiting times.
• Sensitivity analyses identified optimal configurations for teleconsultation rooms and DIM experts.

Conclusions:

• Current teleconsultation resource allocation is suboptimal.
• Increasing teleconsultation rooms to at least four and DIM experts from three to four can significantly reduce costs and waiting times.
• Hospital managers can leverage these findings to improve operational efficiency and patient satisfaction.