Data Collection Environment for Device-associated Infection Surveillance and Its Effectiveness

Abstract

　Medical device-associated infection surveillance is of crucial importance for the verification of infection risks and the devising of countermeasures. The implementation of such surveillance begins with the collection of clinical data, a task that requires significant time and effort. Until now, the process of extracting data from the infection control system and subsequently processing it has been time-consuming, thus preventing feedback and intervention at the most critical sites. Therefore, the aim of this study was to efficiently extract data and implement surveillance in all wards. The extraction of data from the infection control system enables the determination of the insertion period for each ward, patient and medical device. The data is then output by Robotic Process Automation (RPA), manually imported and aggregated by macros, and subsequently listed and graphed to create an environment in which analysis target data can be created. Consequently, the calculation of the usage ratio and infection rate of medical devices across all wards becomes feasible. Moreover, the substantial reduction in working time has paved the way for the implementation of medical device-related infection surveillance in all wards.