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Feasibility of autonomous medication delivery robots considering elevator utilization in high-traffic hospital
Yourack Lee1, Song-Ee Kim2, Jeong Su Kim2
1Biomedical Research Center, Korea University Guro Hospital, Seoul, Republic of Korea.
Background:
Autonomous medication delivery robots can streamline hospital logistics. However, their feasibility under elevator congestion remains uncertain.
Objective:
To evaluate the feasibility of medication delivery robots in a tertiary hospital and quantify how the elevator operating rate (EOR, %) affects delivery success, delay, and user experience.
Methods:
A prospective feasibility study was conducted in a tertiary hospital where a robot is used for delivering medicine. We analyzed 122 non-urgent missions from June 18-29, 2025, spanning weekdays and weekends. Data included the Elevator Operating Rate (EOR), passenger and cargo counts, Elevator Waiting Time, and Elevator Travel Time. The delivery outcomes were recorded, and a Monte Carlo simulation was used to model the failure probabilities under different congestion scenarios. The staff usability and workload were assessed using the System Usability Scale (SUS) and NASA Task Load Index (NASA-TLX).
Results:
A Higher EOR was strongly associated with more delivery failures. Most failures resulted from physical obstruction by passengers or cargo. The data also confirmed that a high EOR coincided with greater elevator occupancy. Simulations incorporating space occupancy reproduced failure patterns similar to the in situ observations. An increased EOR also prolonged the delivery time. The staff reported relatively high usability, but the NASA-TLX scores indicated that frequent robot users felt greater time-related pressure, likely reflecting delays during congestion.
Conclusions:
Autonomous medication delivery is feasible. However, its performance is sensitive to elevator congestion. Effective deployment requires consideration of elevator usage rates, and robotic medication delivery should be scheduled when congestion is below critical thresholds to ensure reliability and minimize the staff burden.
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