A Research Agenda for Using Machine Translation in Clinical Medicine.
A Research Agenda for Using Machine Translation in Clinical Medicine.
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在临床医学中使用机器翻译的研究议程。
DOI：
10.1007/s11606-021-07164-y
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发表时间：
2022
影响因子：
5.7
通讯作者：
Rodriguez,JorgeA
中科院分区：
文献类型：
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作者：
Khoong,ElaineC;Rodriguez,JorgeA
提供语言上适当的护理仍然是实现健康公平的一个挑战。语言障碍影响着美国 2560 万英语水平有限 (LEP) 的人。 LEP 患者的医疗保健获取、质量和结果较差，部分原因是系统经常无法以患者喜欢的语言与患者互动。 1 尽管口译员对于语言不和谐的沟通至关重要，但他们的利用不足 2，并且在资源贫乏的地区或需求增加的时期（例如大流行期间）可能无法使用口译员。因此，临床医生可能会依赖临时口译员或推迟口译。临床医生之间有限的语言多样性加剧了口译员使用的障碍。最终，语言获取不足导致了不平等，需要紧急关注。机器翻译 (MT) 提供了一个诱人的解决方案。机器翻译是指将（文本）或解释（语音）从一种语言翻译成另一种语言的软件。这些工具可以通过网站和移动应用程序以低成本获得，使它们成为临床医生的实用资源，特别是在没有经过认证的（甚至临时）笔译员或口译员的情况下。尽管没有正式量化，但机器翻译工具在临床护理中的使用可能很频繁，反映了这种便利性，并引发了安全问题。 3 虽然机器翻译工具的可访问性表明它可以解决语言资源不足的挑战，但现实世界中对机器翻译的医疗保健评估有限，阻碍了更广泛的采用。虽然有初步证据支持 MT 在翻译公共卫生信息、出院说明和患者门户消息方面的准确性，4-6 但很少有证据表明 MT 用于解释。 7
P rovision of linguistically appropriate care remains a challenge to achieving health equity. Language barriers impact 25.6 million limited English proficient (LEP) individuals in the USA. LEP patients experience worse healthcare access, quality, and outcomes, partly because systems frequently fail to engage patients in their preferred language. 1 Though interpreters are essential for language-discordant communication, they are underused 2 and may be unavailable in underresourced settings or during times of increased demand, such as during a pandemic. Consequently, clinicians may rely on ad hoc interpreters or defer interpretation. Barriers to interpreter use are compounded by limited language diversity among clinicians. Ultimately, inadequate language access has led to inequities that require urgent attention. Machine translation (MT) presents a tempting solution. MT refers to software that translates (text) or interprets (speech) from one language to another. These tools are available at low cost through websites and mobile apps, making them pragmatic resources for clinicians, particularly when certified (or even ad hoc) translators or interpreters are not available. Though not formally quantified, the use of MT tools in clinical care is likely frequent, reflecting this convenience, and has prompted safety concerns. 3 While the accessibility of MT tools suggests it may solve the challenge of inadequate language resources, the limited real-world healthcare evaluation of MT has prevented broader uptake. While there is preliminary evidence supporting MT accuracy for translating public health information, discharge instructions, and patient portal messages, 4–6 there is scant evidence on MT use for interpretation. 7