Application management and effectiveness analysis of intelligent logistics robots in hospital drug and specimen delivery scenarios

To address the limitations of traditional manual logistics in hospitals, this study evaluated an intelligent logistics robot system for drug and specimen delivery. We conducted a six-month single-center parallel-controlled study in a tertiary hospital. The system consisted of 10 autonomous mobile robots using a hierarchical algorithm framework: Dijkstra’s algorithm for global path planning, A* algorithm with Dynamic Window Approach for local navigation, and M/M/c queuing model for multi-robot coordination. Compared with manual delivery, robot delivery reduced delivery time by 32% to 36% (p < 0.001). The robot group achieved 100% verification accuracy and item integrity rate, with significantly lower omission rate (p = 0.011). The 10-robot fleet completed 7.3 times more delivery trips than 19 manual workers over six months. Both nurse and patient satisfaction were significantly higher in the robot group (p < 0.05). Over a 10-year lifecycle, the robot system saved 6.928 million RMB, with sensitivity analysis confirming economic robustness. The intelligent logistics robot system demonstrated significant advantages in delivery efficiency, quality, scalability, user satisfaction, and long-term cost-effectiveness.