Background Nursing care in isolation environments requires strict infection control protocols, which increase nurses’ physical and psychological burden. Frequent entry into isolation rooms for routine tasks, such as adjusting infusion pumps, exposes healthcare workers to infectious agents, increases consumption of personal protective equipment, and results in inefficient use of nursing resources. Aims This study aimed to develop and evaluate the usability of an Internet of Things (IoT) remote control system for infusion pumps (IRCSIP) to support infection prevention, improve nursing efficiency, and enable effective use of resources in isolation care. Design Simulation-based, single-group pre-post usability study. Methods IRCSIP developed using existing commercial IoT devices. Twelve registered nurses with experience in infusion pump operations and isolation nursing care completed two scenarios: (1) remote operation using the IRCSIP and (2) traditional infusion pump operation. The time required to complete infusion rate adjustment, operational success, and subjective usability were measured. Data were analyzed using paired t-tests and descriptive statistics. Results All participants successfully adjusted the infusion rate on their first attempt in both scenarios. Compared with traditional operation, the IRCSIP significantly reduced adjustment time, saving an average of 90.67 s. Usability ratings were positive across all domains: effectiveness “Very good” (58.33%) or “Good” (41.67%); efficiency “Very good” (91.67%); satisfaction “Very good” (66.67%) or “Good” (25.00%); safety “Very good” (41.67%) or “Good” (16.67%); and ease of use “Very good” (58.33%) or “Good” (33.33%). Conclusion IRCSIP demonstrated high usability and significantly improved workflow efficiency by reducing the time needed for infusion rate adjustments. This suggests that the system may help reduce nurse workload related to routine infusion pump management. A key strength of the IRCSIP is compatibility with existing infusion pumps, which allows for cost-effective and scalable implementation without the need for new medical equipment.
Park et al. (Sun,) studied this question.