Park Adam, Jung Se Young, Yune Ilha, Lee Ho-Young
Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
Department of Family Medicine, College of Medicine, Seoul National University, Seoul, Republic of Korea.
JMIR Med Inform. 2025 Mar 7;13:e59801. doi: 10.2196/59801.
Electronic medical records (EMRs) have undergone significant changes due to advancements in technology, including artificial intelligence, the Internet of Things, and cloud services. The increasing complexity within health care systems necessitates enhanced process reengineering and system monitoring approaches. Robotic process automation (RPA) provides a user-centric approach to monitoring system complexity by mimicking end user interactions, thus presenting potential improvements in system performance and monitoring.
This study aimed to explore the application of RPA in monitoring the complexities of EMR systems within a hospital environment, focusing on RPA's ability to perform end-to-end performance monitoring that closely reflects real-time user experiences.
The research was conducted at Seoul National University Bundang Hospital using a mixed methods approach. It included the iterative development and integration of RPA bots programmed to simulate and monitor typical user interactions with the hospital's EMR system. Quantitative data from RPA process outputs and qualitative insights from interviews with system engineers and managers were used to evaluate the effectiveness of RPA in system monitoring.
RPA bots effectively identified and reported system inefficiencies and failures, providing a bridge between end user experiences and engineering assessments. The bots were particularly useful in detecting delays and errors immediately following system updates or interactions with external services. Over 3 years, RPA monitoring highlighted discrepancies between user-reported experiences and traditional engineering metrics, with the bots frequently identifying critical system issues that were not evident from standard component-level monitoring.
RPA enhances system monitoring by providing insights that reflect true end user experiences, which are often overlooked by traditional monitoring methods. The study confirms the potential of RPA to act as a comprehensive monitoring tool within complex health care systems, suggesting that RPA can significantly contribute to the maintenance and improvement of EMR systems by providing a more accurate and timely reflection of system performance and user satisfaction.
由于包括人工智能、物联网和云服务在内的技术进步,电子病历(EMR)发生了重大变化。医疗保健系统日益复杂,这就需要加强流程再造和系统监控方法。机器人流程自动化(RPA)通过模仿最终用户交互提供了一种以用户为中心的方法来监控系统复杂性,从而在系统性能和监控方面展现出潜在的改进。
本研究旨在探索RPA在医院环境中监控EMR系统复杂性方面的应用,重点关注RPA执行端到端性能监控的能力,这种监控能密切反映实时用户体验。
该研究在首尔国立大学盆唐医院采用混合方法进行。研究包括迭代开发和集成RPA机器人,这些机器人被编程用来模拟和监控与医院EMR系统的典型用户交互。来自RPA流程输出的定量数据以及与系统工程师和管理人员访谈的定性见解被用于评估RPA在系统监控中的有效性。
RPA机器人有效地识别并报告了系统低效和故障,在最终用户体验和工程评估之间架起了一座桥梁。这些机器人在检测系统更新或与外部服务交互后立即出现的延迟和错误方面特别有用。在三年多的时间里,RPA监控突出了用户报告的体验与传统工程指标之间的差异,这些机器人经常识别出标准组件级监控中不明显的关键系统问题。
RPA通过提供反映真实最终用户体验的见解来增强系统监控,而这些体验往往被传统监控方法所忽视。该研究证实了RPA在复杂医疗保健系统中作为综合监控工具的潜力,表明RPA可以通过更准确、及时地反映系统性能和用户满意度,为EMR系统的维护和改进做出重大贡献。