全科医生上门问诊时会观察到哪些体格检查?使用基于文本的方法自动提取

IF 3.7 2区 医学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Moomna Waheed, Hao Xiong, Kate Tong, Annie.Y. Lau
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引用次数: 0

摘要

目标预计远程会诊将在初级医疗中长期发挥作用。然而,进行虚拟体检是一个众所周知的限制因素。为了预测全科医生(GP)和患者在远程会诊过程中可能遇到的未满足需求,本研究旨在自动识别全科医生面对面会诊过程中通常会进行的身体检查。我们提出了一种基于文本的自动方法,利用全科医生与患者问诊对话中的关键词(如 "卷起袖子")的正则表达式来识别身体检查(如血压测量)。这种方法包括构建概念图以直观地检查关键词与体检之间的关系,进行语法分析以识别关键词之间的模式并生成正则表达式,以及在问诊记录中使用这些正则表达式来检测体检的潜在实例,随后检索匹配的视频帧。两名独立研究人员使用 5 倍交叉验证(精确度、召回率和 F1 分数)将我们基于文本的自动化方法的性能与人工分类进行了比较。在这 133 次问诊中,共观察到 283 次体格检查,其中 21 次是在幕后进行的。我们从这 283 次体格检查中确定了 42 种不同类型的体格检查,并根据身体部位和体征将其分为 10 个体格检查类别。最常见的体检类别是生命体征 26.80%(76/283)。总体而言,血压测量(也属于生命体征类别)是最常见的体格检查,占 59.2%(45/76)。人工分类与正则表达式模型之间的比较显示,5 倍交叉验证的平均精确度为 88.3%,召回率为 78.9%,F1 分数为 83.3%,为了解全科医生当面问诊时进行身体检查的频率和类型提供了重要依据。这项研究的结果,即全科医生面对面咨询中的身体检查,为全科医生和患者在远程咨询中可能需要支持的领域提供了启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What physical examinations are observed during an in-person GP consultation? Automatic extraction using a text-based approach

Objectives

Teleconsultation is anticipated to have a long-term role in primary care. However, conducting virtual physical examinations is a well-known limitation. To anticipate unmet needs general practitioners (GPs) and patients may experience during teleconsultation, this study aims to automatically identify physical examinations typically conducted during in-person GP consultation.

Material and Methods

This study utilizes 281 GP in-person consultations (de-identified transcripts & video recordings) within UK general practices, where 169 eligible ones were included in this study. We propose an automated text-based approach using regular expressions on keywords in GP-patient consultation dialogue (e.g., “roll up your sleeves”) to identify physical examinations (e.g. blood pressure measurement). This approach involves the construction of conceptual diagrams to visually inspect the relationship between keywords and physical examinations, syntax analysis to identify patterns between keywords and generate regular expressions, and the use of these regular expressions in consultation transcripts to detect potential instances of physical examinations, where matching video frames were subsequently retrieved. The performance of our automated text-based approach is compared to manual classification by 2 independent researchers using 5-fold cross-validation (precision, recall, and F1-score).

Results

Among the 169 eligible GP in-person consultations, 133 (79%) required a physical examination, while the other 33 visits were for psychological reasons. Out of these 133 consultations, a total of 283 physical examinations were observed, with 21 instances conducted behind a curtain. We identified 42 distinct types of physical examinations from these 283 instances, grouped into 10 physical examination categories based on body areas and physical artefacts. The most frequent category of physical examinations is Vital Signs 26.80% (76/283). Overall, blood pressure measurement (also belonging to the Vital Signs category) is the most frequent physical examination at 59.2% (45/76). The comparison between manual classification and the regular expression model demonstrates an average precision of 88.3%, recall of 78.9%, and an F1-score of 83.3% from 5-fold cross-validation, providing significant insights into the frequency and types of physical examinations conducted during in-person GP consultations.

Conclusion

By using regular expressions in consultation dialogues between GPs and patients, we can automatically identify physical examinations in GP consultations with a precision of 88.3%. Findings from this study, i.e. physical examinations during in-person GP consultations, provide insights into areas where GPs and patients may need support during teleconsultation.

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来源期刊
International Journal of Medical Informatics
International Journal of Medical Informatics 医学-计算机:信息系统
CiteScore
8.90
自引率
4.10%
发文量
217
审稿时长
42 days
期刊介绍: International Journal of Medical Informatics provides an international medium for dissemination of original results and interpretative reviews concerning the field of medical informatics. The Journal emphasizes the evaluation of systems in healthcare settings. The scope of journal covers: Information systems, including national or international registration systems, hospital information systems, departmental and/or physician''s office systems, document handling systems, electronic medical record systems, standardization, systems integration etc.; Computer-aided medical decision support systems using heuristic, algorithmic and/or statistical methods as exemplified in decision theory, protocol development, artificial intelligence, etc. Educational computer based programs pertaining to medical informatics or medicine in general; Organizational, economic, social, clinical impact, ethical and cost-benefit aspects of IT applications in health care.
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