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

Consultation analysis: use of free text versus coded text

Affiliations

Consultation analysis: use of free text versus coded text

Pablo Millares Martin. Health Technol (Berl). 2021.

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.

Keywords: Clinical coding; Electronic health record; Family practice; General practice; Records; Systematized Nomenclature of Medicine.

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Conflict of interest statement

Conflict of interestThe authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
GP consultation, as extracted, and with separated text and code for word counting
Fig. 2
Fig. 2
Average number of codes in the different sections of consultation
Fig. 3
Fig. 3
Word cloud of free text, with list of most common words encountered
Fig. 4
Fig. 4
Word cloud of coded text, with list of most common words encountered

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