Falcetta Frederico Soares, de Almeida Fernando Kude, Lemos Janaína Conceição Sutil, Goldim José Roberto, da Costa Cristiano André
Software Innovation Laboratory - Softwarelab, Universidade do Vale do Rio dos Sinos - Unisinos, Av. Unisinos 950, São Leopoldo, 93022-750, RS, Brazil; Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos 2350, Porto Alegre, 90035-903, RS, Brazil.
Hospital Fêmina, Rua Mostardeiro 17, Porto Alegre, 90430-001, RS, Brazil.
Artif Intell Med. 2023 Mar;137:102487. doi: 10.1016/j.artmed.2023.102487. Epub 2023 Jan 19.
Electronic systems are increasingly present in the healthcare system and are often related to improved medical care. However, the widespread use of these technologies ended up building a relationship of dependence that can disrupt the doctor-patient relationship. In this context, digital scribes are automated clinical documentation systems that capture the physician-patient conversation and then generate the documentation for the appointment, enabling the physician to engage with the patient entirely. We have performed a systematic literature review on intelligent solutions for automatic speech recognition (ASR) with automatic documentation during a medical interview. The scope included only original research on systems that could detect speech and transcribe it in a natural and structured fashion simultaneously with the doctor-patient interaction, excluding speech-to-text-only technologies. The search resulted in a total of 1995 titles, with eight articles remaining after filtering for the inclusion and exclusion criteria. The intelligent models mainly consisted of an ASR system with natural language processing capability, a medical lexicon, and structured text output. None of the articles had a commercially available product at the time of the publication and reported limited real-life experience. So far, none of the applications has been prospectively validated and tested in large-scale clinical studies. Nonetheless, these first reports suggest that automatic speech recognition may be a valuable tool in the future to facilitate medical registration in a faster and more reliable manner. Improving transparency, accuracy, and empathy could drastically change how patients and doctors experience a medical visit. Unfortunately, clinical data on the usability and benefits of such applications is almost non-existent. We believe that future work in this area is necessary and needed.
电子系统在医疗保健系统中越来越普遍，并且常常与改善医疗护理相关。然而，这些技术的广泛使用最终建立了一种依赖关系，这种关系可能会破坏医患关系。在这种背景下，数字抄写员是一种自动化临床文档系统，它能够捕捉医患对话，然后生成预约文档，使医生能够全心与患者交流。我们对医疗问诊期间用于自动语音识别（ASR）和自动文档记录的智能解决方案进行了系统的文献综述。范围仅包括对能够在医患互动的同时以自然且结构化的方式检测语音并进行转录的系统的原始研究，不包括仅语音转文本的技术。搜索总共得到1995个标题，在根据纳入和排除标准进行筛选后，剩下八篇文章。智能模型主要由具有自然语言处理能力的ASR系统、医学词汇表和结构化文本输出组成。在发表时，没有一篇文章有商业可用产品，并且所报告的实际应用经验有限。到目前为止，没有任何应用程序在大规模临床研究中得到前瞻性验证和测试。尽管如此，这些初步报告表明，自动语音识别未来可能成为一种有价值的工具，以更快、更可靠的方式促进医疗记录。提高透明度、准确性和同理心可能会极大地改变患者和医生体验医疗问诊的方式。不幸的是，关于此类应用程序的可用性和益处的临床数据几乎不存在。我们认为该领域未来的工作是必要且急需的。
