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设计并验证一种低成本实时定位系统,以持续评估患者等待时间。

Designing and validating a low-cost real time locating system to continuously assess patient wait times.

作者信息

Newman-Casey Paula Anne, Musser John, Niziol Leslie M, Shedden Kerby, Burke David, Cohn Amy

机构信息

Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, MI, United States.

Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, MI, United States.

出版信息

J Biomed Inform. 2020 Jun;106:103428. doi: 10.1016/j.jbi.2020.103428. Epub 2020 Apr 24.

Abstract

OBJECTIVE

Outpatient clinics lack infrastructure to easily measure and understand patient wait times. Our objective was to design a low-cost, portable passive real time locating system within an outpatient clinic setting to measure patient wait times and patient-provider interactions.

MATERIALS AND METHODS

Direct observation was used to determine workflow in an outpatient glaucoma clinic at the University of Michigan. We used off-the shelf, antenna-integrated ultra-high frequency (UHF) RFID readers (ThingMagic, Astra-Ex, Woburn, MA) and UHF re-useable passive RFID tags (Zebra Impinj Monza 4QT, Seattle, WA). We designed a custom RFID management application in the Java programming language that was equipped with 'live' device administration to collect time and location data from patients and providers. These hardware choices enabled low cost system installation. Hidden Markov Modeling (HMM) was used to smooth patient and provider location data. Location data were validated against direct observations and EHR evaluation.

RESULTS

The HMM smoothed RFID system data accurately predicted patient location 80.6% of the time and provider location 79.1% of the time, compared to direct observation locations, an improvement over the raw RFID location data (65.0% and 77.9% accurate, respectively). Patient process time was on average 42.8 min (SD = 27.5) and wait time was 47.9 min (SD = 33.1). The installation and recurring capital costs of the system are approximately 10% of available commercially-supplied patient/provider tracking systems.

DISCUSSION

Passive RFID time study systems can enable real-time localization of people in clinic, facilitating continuous capture of patient wait times and patient-provider interactions. The system must be tailored to the clinic to accurately reflect patient and provider movement.

CONCLUSIONS

Capturing wait time data continuously and passively can empower continuous clinical quality improvement initiatives to enhance the patient experience.

摘要

目的

门诊诊所缺乏便于测量和了解患者候诊时间的基础设施。我们的目标是在门诊诊所环境中设计一种低成本、便携式无源实时定位系统,以测量患者候诊时间以及患者与医护人员的互动情况。

材料与方法

采用直接观察法来确定密歇根大学门诊青光眼诊所的工作流程。我们使用了现成的、集成天线的超高频(UHF)射频识别(RFID)阅读器(ThingMagic公司,Astra-Ex型号,马萨诸塞州沃本)以及UHF可重复使用的无源RFID标签(斑马技术Impinj Monza 4QT型号,华盛顿州西雅图)。我们用Java编程语言设计了一个定制的RFID管理应用程序,该程序配备了“实时”设备管理功能,用于收集患者和医护人员的时间及位置数据。这些硬件选择使得系统安装成本较低。使用隐马尔可夫模型(HMM)对患者和医护人员的位置数据进行平滑处理。将位置数据与直接观察结果及电子健康记录(EHR)评估结果进行验证。

结果

与直接观察到的位置相比,HMM平滑后的RFID系统数据准确预测患者位置的时间占比为80.6%,预测医护人员位置的时间占比为79.1%,相较于原始RFID位置数据(分别为65.0%和77.9%的准确率)有了提高。患者诊疗过程平均耗时42.8分钟(标准差 = 27.5),候诊时间为47.9分钟(标准差 = 33.1)。该系统的安装和经常性资本成本约为市售患者/医护人员跟踪系统成本的10%。

讨论

无源RFID时间研究系统能够实现诊所内人员的实时定位,有助于持续获取患者候诊时间以及患者与医护人员的互动情况。该系统必须根据诊所情况进行定制,以准确反映患者和医护人员的移动情况。

结论

持续被动地获取候诊时间数据能够推动持续的临床质量改进举措,提升患者体验。

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