Biermann Pascal, Baier Claas, Vietor Ann Christin, Zacher Benedikt, Baumgartl Tom, von Landesberger Tatiana, Behnke Michael, Storck Michael, Petzold Markus, Kaase Martin, Schlüter Dirk, Marschollek Michael, Scheithauer Simone, Wulff Antje
Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School, Hannover, Germany.
Big Data in Medicine, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
NPJ Digit Med. 2025 Jun 30;8(1):385. doi: 10.1038/s41746-025-01795-9.
Early outbreak detection, allowing rapid intervention, is essential to reduce the burden of healthcare-associated pathogen transmission, including multidrug-resistant bacteria. Digital, routine data-driven solutions are promising, but often proprietary, non-interoperable, or limited in functional scope. The open-source Smart Infection Control System (SmICS) offers automatic calculations and interactive views on patients' movement and lab data, epidemic curves, contact networks, complemented by temporal-spatial visualizations. It is an open-source software based on openEHR as an interoperability standard and was evaluated by assessing time efficiencies in performing basic infection control tasks (e.g., contact networks) and usability with the System Usability Scale (SUS). Evaluated at three sites, SmICS reduced the time needed for performing routine infection control tasks by up to 81.47% (68.5 min (95%CI [30.5-106.5])) reaching a SUS of 51.6 points. The study reveals time savings through the use of SmICS in daily tasks, but also identified usability issues and a need for minimizing query waiting times.
早期发现疫情，以便迅速采取干预措施，对于减轻包括耐多药细菌在内的医疗保健相关病原体传播的负担至关重要。数字化、基于常规数据的解决方案很有前景，但往往具有专有性、不可互操作或功能范围有限。开源的智能感染控制系统（SmICS）可对患者的活动和实验室数据、流行曲线、接触网络进行自动计算并提供交互式视图，并辅以时空可视化。它是一款基于openEHR作为互操作性标准的开源软件，通过评估执行基本感染控制任务（如接触网络）的时间效率以及使用系统可用性量表（SUS）评估其可用性进行了评估。在三个地点进行评估时，SmICS将执行常规感染控制任务所需的时间最多减少了81.47%（68.5分钟（95%CI [30.5 - 106.5]）），系统可用性量表得分为51.6分。该研究揭示了在日常任务中使用SmICS可节省时间，但也发现了可用性问题以及尽量减少查询等待时间的必要性。
