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会诊分析:自由文本与编码文本的使用

Consultation analysis: use of free text versus coded text.

作者信息

Millares Martin Pablo

机构信息

Whitehall Surgery, Wortley Beck Health Centre, Leeds, LS12 5SG UK.

出版信息

Health Technol (Berl). 2021;11(2):349-357. doi: 10.1007/s12553-020-00517-3. Epub 2021 Jan 24.

Abstract

General practice in the United Kingdom has been using electronic health records for over two decades, but coding clinical information remains poor. Lack of interest and training are considerable barriers preventing code use levels improvement. Tailored training could be the way forward, to break barriers in the uptake of coding; to do so it is paramount to understand coding use of the particular clinicians, to recognise their needs. It should be possible to easily assess text quantity and quality in medical consultations. A tool to measure these parameters, which could be used to tailor training needs and assess change, is demonstrated. The tool is presented and a preliminary study using a randomised sample of five recent consultations from thirteen different clinicians is used as an example. The tool, based on using a word processor and a spread-sheet, allowed quantitative analysis among clinicians while word clouds permitted a qualitative comparison between coded and free text. The average amount of free text per consultation was 68.2 words, (ranging from 25.4 and 130.2 among clinicians); an average of 6% of the text was coded (ranging from 0 to 13%). Patterns among clinicians could be identified. Using Word cloud, a different text use was demonstrated depending on its purpose. Some free text could be turned into code but nomenclature probably prevented some of the codings, like the expression of time. This proof of concept demonstrated that it is possible to calculate what percentage of consultations are coded and what codes are used. This allowed understanding clinicians' preferences; training needs and gaps in nomenclature.

摘要

英国的全科医疗使用电子健康记录已有二十多年,但临床信息编码情况仍然不佳。缺乏兴趣和培训是阻碍编码使用水平提高的重大障碍。量身定制的培训可能是解决之道,以打破编码应用中的障碍;要做到这一点,了解特定临床医生的编码使用情况、认识他们的需求至关重要。应该能够轻松评估医疗咨询中的文本数量和质量。展示了一种可用于确定培训需求和评估变化的测量这些参数的工具。介绍了该工具,并以从13位不同临床医生最近的会诊中随机抽取的5份会诊记录为例进行了初步研究。该工具基于文字处理器和电子表格,可对临床医生进行定量分析,而词云图则允许对编码文本和自由文本进行定性比较。每次会诊的自由文本平均数量为68.2个单词(临床医生之间的范围为25.4至130.2个单词);平均6%的文本被编码(范围为0至13%)。可以识别临床医生之间的模式。使用词云图可以看出,根据文本用途不同,文本使用情况也不同。一些自由文本可以转换为编码,但术语可能阻碍了一些编码,比如时间的表达。这一概念验证表明,可以计算出会诊被编码的百分比以及使用了哪些编码。这有助于了解临床医生的偏好、培训需求和术语方面的差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27b3/7829039/74a381a99c10/12553_2020_517_Fig1_HTML.jpg

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