在丹麦医院,通过自然语言处理模型协助验证厌食症和 Bulimia nervosa 诊断编码
Jeanie Meincke Egedal1, Rene Klinkby Støving1, Rasmus Bank Lynggaard2
1Center for Eating Disorders, Odense University Hospital, Odense, Denmark; Research Unit for Medical Endocrinology, Odense University Hospital, Odense, Denmark; Mental Health Services in the Region of Southern Denmark, Denmark; Open Patient data Explorative Network (OPEN), Denmark; Clinical Institute, University of Southern Denmark, Denmark.
Journal of psychiatric research
|September 26, 2024
概括
丹麦医疗保健注册表显示,饮食障碍诊断的准确性很高,包括神经性厌食症 (AN) 和神经性 Bulimia (BN). 自然语言处理 (NLP) 辅助手动图表审查以验证这些ICD-10代码.
科学领域:
- 医疗信息学 医疗信息学
- 精神病学是一个精神病学.
- 流行病学 流行病学
背景情况:
- 丹麦医疗保健注册使用ICD分类来进行流行病学研究.
- 饮食障碍,包括神经性厌食症 (AN) 和神经性嗜食症 (BN),需要准确的诊断验证.
- 手动图表审查是验证的标准,但自然语言处理 (NLP) 可能会提高效率.
研究的目的:
- 评估丹麦医疗保健登记册中饮食障碍的ICD-10诊断代码 (F50.0,F50.1,F50.2,F50.3) 的准确性.
- 评估NLP在协助手册图表审查中对诊断代码验证的有用性.
主要方法:
- 提取了来自丹麦南部地区的每位诊断码的100人电子健康日记数据.
- 采用NLP模型与正则表达式来识别相关的文本段落用于手册审查.
- 进行手动图表审查,以验证已注册的ICD-10饮食障碍代码的准确性.
主要成果:
- 经过验证的ICD-10代码的整体准确率为93% (372分之400).
- 具体代码的准确性: 厌食症神经 (90%), 异常AN (96%), 神经过敏 (96%), 异常BN (90%).
- 在验证过程中,NLP有效地支持手动图表审查.
结论:
- 在丹麦医疗保健登记册中,ICD-10代码F50.0,F50.1,F50.2和F50.3对于饮食障碍的准确性很高.
- 这些发现支持丹麦卫生登记册对于有关饮食障碍的流行病学研究的总体有效性.
- 在提高诊断代码验证流程的效率方面,NLP显示出前景.
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