十多年来电子健康记录中精神病临床记录的词汇稳定性

IF 3.8 4区 医学 Q1 Medicine
Lasse Hansen, Kenneth Enevoldsen, Martin Bernstorff, Erik Perfalk, Andreas A Danielsen, Kristoffer L Nielbo, Søren D Østergaard
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引用次数: 0

摘要

目的:自然语言处理(NLP)方法有望通过利用电子健康记录临床记录中隐藏的信息来改进临床预测。然而,临床实践——以及记录和存储临床记录的系统和数据库——随着时间的推移而变化。因此,临床记录的内容也可能随着时间的推移而改变,这可能会降低预测模型的性能。尽管它很重要,但临床记录随时间的稳定性很少得到测试。方法:对2011年1月1日至2021年11月22日期间(共14811551份临床记录,共129570例患者)的临床记录,通过量化句子长度、可读性、句法复杂性和临床内容,对临床记录的词汇稳定性进行评估。变更点检测模型用于估计这些度量中的潜在变更。结果:我们发现临床笔记的词汇稳定性随时间而变化,在COVID-19大流行期间有轻微的偏差。在2988个数据点中,检测到17个可能的变化点(对应0.6%)。其中大多数与某种特定类型的纸币的停止使用有关。结论:我们发现精神病服务的临床笔记的词汇和句法随时间的变化具有稳定性,这预示着在临床精神病学中使用NLP进行预测建模是一个好兆头。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lexical stability of psychiatric clinical notes from electronic health records over a decade.

Objective: Natural language processing (NLP) methods hold promise for improving clinical prediction by utilising information otherwise hidden in the clinical notes of electronic health records. However, clinical practice - as well as the systems and databases in which clinical notes are recorded and stored - change over time. As a consequence, the content of clinical notes may also change over time, which could degrade the performance of prediction models. Despite its importance, the stability of clinical notes over time has rarely been tested.

Methods: The lexical stability of clinical notes from the Psychiatric Services of the Central Denmark Region in the period from January 1, 2011, to November 22, 2021 (a total of 14,811,551 clinical notes describing 129,570 patients) was assessed by quantifying sentence length, readability, syntactic complexity and clinical content. Changepoint detection models were used to estimate potential changes in these metrics.

Results: We find lexical stability of the clinical notes over time, with minor deviations during the COVID-19 pandemic. Out of 2988 data points, 17 possible changepoints (corresponding to 0.6%) were detected. The majority of these were related to the discontinuation of a specific note type.

Conclusion: We find lexical and syntactic stability of clinical notes from psychiatric services over time, which bodes well for the use of NLP for predictive modelling in clinical psychiatry.

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来源期刊
Acta Neuropsychiatrica
Acta Neuropsychiatrica 医学-精神病学
CiteScore
8.50
自引率
5.30%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. It publishes high-quality original research papers and reviews. The Journal''s scope specifically highlights the pathway from discovery to clinical applications, healthcare and global health that can be viewed broadly as the spectrum of work that marks the pathway from discovery to global health.
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