The effect of an IoT-based intelligent infusion monitoring system on the intravenous infusion safety of hospitalized patients: a retrospective study.

BACKGROUND

Intravenous infusion is a key part of nursing practice, and its scientific reliability and safety directly affect nursing quality and patient satisfaction. Currently, most hospitals still use traditional gravity infusion, with inherent limitations that burden nursing staff. Therefore, information management is an effective strategy to enhance medication safety.

AIM: This study aimed to explore the effect of intelligent infusion monitoring systems in improving patient infusion safety.

METHODS

The study used a retrospective study design. A collaborative development of an intelligent infusion monitoring system using Internet of Things (IoT) technology was conducted. Data from two pilot wards were retrospectively analyzed, including on-time infusion completion rates, infusion-related complications, and patient satisfaction 1 year before and after system implementation. Additionally, infusion abnormalities and nurses' system satisfaction were recorded during application.

RESULTS

After the application of the intelligent infusion monitoring system, the on-time completion rates of patient infusions significantly improved in both Ward A and Ward B independently, as well as in both wards combined. The occurrence of complications related to infusion significantly reduced in Ward A and in both wards combined. Patient satisfaction also improved after the system application. Most infusion abnormality alerts (74.33%, 85,322 cases) involved blockages or rate abnormalities, with a mean response time of 2.12 min. Nurses' satisfaction with the system was 75% (33/44).

CONCLUSION

The application of the intelligent infusion monitoring system effectively improved the on-time completion rates of intravenous infusions and effectively reduced the incidence of complications related to infusion. Through real-time monitoring and alert functions, the system facilitated the timely detection and management of infusion abnormalities, enhancing the quality of infusion management for patients, ensuring infusion safety, and improving patient satisfaction. However, there is still room for improvement in the intelligence and convenience of the system. Therefore, future efforts should focus on further research and investment in intelligent infusion equipment to improve the safety of clinical patient infusions and enhance nursing efficiency.