Visualization of Waiting Times and Evaluation of Workload Congestion Mitigation in General Imaging

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Key Points

The study aims to analyze characteristics of waiting times in general imaging and quantitatively assess the effectiveness of operational improvements.
Analyzed waiting times using timestamps from a radiology information system.
Visualized the distribution of waiting times by day of the week and identified influencing factors with machine learning.
Developed a discrete event simulation considering patient arrival intervals, exam durations, number of technicians, and rooms.
Waiting times showed significant differences across days of the week.
Analysis indicated strong involvement of exam type and operator factors in waiting times.
Simulation revealed that merely increasing technicians had limited effect on reducing waiting times, with excess staffing potentially lowering efficiency.

Evaluates workload improvements to reduce waiting times in general imaging, indicating effective strategies for time management.

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Ganjitsuda et al. (2026) studied this question.

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