Institute of Biomedical Informatics, National Yang Ming University, Taipei, Taiwan.
Int J Med Inform. 2011 Dec;80(12):872-80. doi: 10.1016/j.ijmedinf.2011.09.006. Epub 2011 Oct 20.
Nosocomial infections (NIs) are among the important indicators used for evaluating patients' safety and hospital performance during accreditation of hospitals. NI rate is higher in Intensive Care Units (ICUs) than in the general wards because patients require intense care involving both invasive and non-invasive clinical procedures. The emergence of Superbugs is motivating health providers to enhance infection control measures. Contact behavior between health caregivers and patients is one of the main causes of cross infections. In this technology driven era remote monitoring of patients and caregivers in the hospital setting can be performed reliably, and thus is in demand. Proximity sensing using radio frequency identification (RFID) technology can be helpful in capturing and keeping track on all contact history between health caregivers and patients for example.
This study intended to extend the use of proximity sensing of radio frequency identification technology by proposing a model for inferring RFID tag reader recordings into clinical events. The aims of the study are twofold. The first aim is to set up a Contact History Inferential Model (CHIM) between health caregivers and patients. The second is to verify CHIM with real-time observation done at the ICU ward.
A pre-study was conducted followed by two study phases. During the pre-study proximity sensing of RFID was tested, and deployment of the RFID in the Clinical Skill Center in one of the medical centers in Taiwan was done. We simulated clinical events and developed CHIM using variables such as duration of time, frequency, and identity (tag) numbers assigned to caregivers. All clinical proximity events are classified into close-in events, contact events and invasive events. During the first phase three observers were recruited to do real time recordings of all clinical events in the Clinical Skill Center with the deployed automated RFID interaction recording system. The observations were used to verify the CHIM recordings. In second phase the first author conducted 40 h of participatory observation in the ICU, and observed values that were used as golden standard to validate CHIM.
There were a total of 193 events to validate the CHIM in the second phase. The sensitivity, specificity, and accuracy of close-in events were 73.8%, 83.8%, and 81.6%; contact events were 81.4%, 78.8%, and 80.7%; and invasive events were 90.9%, 98.0%, and 97.5% respectively.
The results of the study indicated that proximity sensing of the RFID detects proximity events effectively, and the CHIM can infer proximity events accurately. RFID technology can be used for recording complete clinical contact history between caregivers and patients thus assisting in tracing cause of NIs. Since this model could infer the ICU activities accurately, we are convinced that the CHIM can also be applied in other wards and can be used for additional purposes.
医院评审期间，医院感染（NI）是评估患者安全和医院绩效的重要指标之一。由于患者需要涉及侵入性和非侵入性临床操作的强化护理，因此重症监护病房（ICU）的感染发生率高于普通病房。超级细菌的出现促使医疗保健提供者加强感染控制措施。医护人员与患者之间的接触行为是交叉感染的主要原因之一。在这个技术驱动的时代，可以可靠地对医院环境中的患者和医护人员进行远程监控，因此需求很大。使用射频识别（RFID）技术进行接近感应可以帮助捕获和跟踪医护人员与患者之间的所有接触历史，例如。
本研究旨在通过提出一种将射频识别标签读取器记录推断为临床事件的模型来扩展射频识别接近感应的使用。本研究的目的有两个。第一个目的是建立医护人员与患者之间的接触历史推断模型（CHIM）。第二个目的是通过在 ICU 病房进行实时观察来验证 CHIM。
进行了预研究，然后进行了两个研究阶段。在预研究中，测试了 RFID 的接近感应，并在台湾的一家医疗中心的临床技能中心部署了 RFID。我们使用持续时间、频率和分配给护理人员的身份（标签）号等变量来开发 CHIM。所有临床接近事件都分为近距离事件、接触事件和侵入性事件。在第一阶段，招募了三名观察员在临床技能中心使用部署的自动 RFID 交互记录系统对所有临床事件进行实时记录。观察结果用于验证 CHIM 记录。在第二阶段，第一作者在 ICU 进行了 40 小时的参与式观察，并观察了作为验证 CHIM 的金标准的值。
在第二阶段，共有 193 个事件验证了 CHIM。近距离事件的灵敏度、特异性和准确性分别为 73.8%、83.8%和 81.6%；接触事件分别为 81.4%、78.8%和 80.7%；侵入性事件分别为 90.9%、98.0%和 97.5%。
研究结果表明，RFID 的接近感应可以有效地检测接近事件，CHIM 可以准确推断接近事件。RFID 技术可用于记录医护人员与患者之间完整的临床接触历史，从而有助于追踪医院感染的原因。由于该模型可以准确推断 ICU 活动，我们相信 CHIM 也可以应用于其他病房，并可用于其他目的。
