Patient Identification Techniques - Approaches, Implications, and Findings.
Patient Identification Techniques - Approaches, Implications, and Findings.
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DOI：
10.1055/s-0040-1701984
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发表时间：
2020-08-01
影响因子：
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通讯作者：
Dooling, Julie Pursley
中科院分区：
文献类型：
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作者：
Riplinger, Lauren;Piera-Jimenez, Jordi;Dooling, Julie Pursley
目的：确定当今世界范围内在医疗保健环境中使用的当前患者识别技术和方法。方法：对2015年1月至2019年10月发表的相关同行评议和灰色文献进行文献综述，为论文提供参考。重点放在：1)患者身份识别技术和2)未解决的患者身份识别问题的意外后果和分支。结果：文献综述显示了全球实施的6种常见的患者身份识别技术，包括唯一的患者身份识别、算法方法、参考匹配软件、生物识别、射频识别设备(RFID)系统和混合模型。这篇综述揭示了与未解决的患者身份识别相关的三个主题：1)治疗、护理提供和患者安全错误，2)成本和资源考虑，以及3)数据共享和互操作性挑战。结论：患者身份识别中的错误会影响患者的护理和安全、支付以及数据共享和互操作性。从独特的患者识别符和算法到混合模型，不同的患者识别技术已在全球范围内实施。然而，目前还没有一种患者识别技术能够达到100%的匹配率。应进一步研究通过数据标准化和参考匹配软件优化算法匹配，以确定增强患者识别技术和方法的机会。改进患者身份管理的进一步努力包括在登记时采用患者的照片、命名约定以及记录患者的人口统计数据属性的标准化流程。
OBJECTIVES: To identify current patient identification techniques and approaches used worldwide in today's healthcare environment. To identify challenges associated with improper patient identification.METHODS: A literature review of relevant peer-reviewed and grey literature published from January 2015 to October 2019 was conducted to inform the paper. The focus was on: 1) patient identification techniques and 2) unintended consequences and ramifications of unresolved patient identification issues.RESULTS: The literature review showed six common patient identification techniques implemented worldwide ranging from unique patient identifiers, algorithmic approaches, referential matching software, biometrics, radio frequency identification device (RFID) systems, and hybrid models. The review revealed three themes associated with unresolved patient identification: 1) treatment, care delivery, and patient safety errors, 2) cost and resource considerations, and 3) data sharing and interoperability challenges.CONCLUSIONS: Errors in patient identification have implications for patient care and safety, payment, as well as data sharing and interoperability. Different patient identification techniques ranging from unique patient identifiers and algorithms to hybrid models have been implemented worldwide. However, no current patient identification techniques have resulted in a 100% match rate. Optimizing algorithmic matching through data standardization and referential matching software should be studied further to identify opportunities to enhance patient identification techniques and approaches. Further efforts to improve patient identity management include adoption of patients' photos at registration, naming conventions, and standardized processes for recording patients' demographic data attributes.