1.中国中医科学院中医临床基础医学研究所,北京市东直门内南小街16号,100700
2.中国医学科学院北京协和医学院药用植物研究所
3.北京中医药大学东直门医院
4.北京科技大学
shanghongcai@126.com
收稿:2024-02-25,
修回:2024-03-01,
纸质出版:2024-04-17
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张晓雨,田思超,尤良震等.大数据时代中医症状疗效评价存在的问题与解决对策[J].中医杂志,2024,65(08):792-795.
ZHANG Xiaoyu,TIAN Sichao,YOU Liangzhen,et al.Issues and Solutions for Symptom Efficacy Evaluation in the Big Data Era of Traditional Chinese Medicine[J].Journal of Traditional Chinese Medicine,2024,65(08):792-795.
张晓雨,田思超,尤良震等.大数据时代中医症状疗效评价存在的问题与解决对策[J].中医杂志,2024,65(08):792-795. DOI: 10.13288/j.11-2166/r.2024.08.005.
ZHANG Xiaoyu,TIAN Sichao,YOU Liangzhen,et al.Issues and Solutions for Symptom Efficacy Evaluation in the Big Data Era of Traditional Chinese Medicine[J].Journal of Traditional Chinese Medicine,2024,65(08):792-795. DOI: 10.13288/j.11-2166/r.2024.08.005.
重视症状疗效是中医辨证论治个体化诊疗特色的重要体现。目前中医药临床实践中存在症状表述多样、规范难度大,症状疗效评价标准不一、缺少通用量化方法,症状信息复杂多变、难以完整准确采集的问题,使得症状信息不能得到充分、有效利用。针对症状术语规范、症状疗效量化分级、症状信息采集的研究现状及存在问题,围绕大数据时代有效记录、充分利用中医症状疗效信息的方法学难题,提出基于患者报告采集中医症状信息、从测量尺度和评价维度规范中医症状疗效评价、融入临床诊疗过程的中医症状疗效评价、利用人工智能技术获取并处理中医症状疗效信息。基于患者视角与人工智能技术的中医症状疗效评价策略将有助于充分发挥数据要素价值,助力中医药特色疗效的客观展示和有效规律的挖掘。
Emphasizing symptom efficacy is an important manifestation of the personalized diagnosis and treatment of traditional Chinese medicine (TCM). However, in current clinical practice of TCM, there are challenges such as diverse symptom expressions, difficulty in standardization, inconsistent evaluation standards for symptom efficacy, lack of universal quantitative methods, and complexity in collecting complete and accurate symptom information. These issues hinder the full and effective utilization of symptom information. Addressing the current research status and existing problems of symptom terminology standardization, quantification and grading of symptom efficacy, and collection of symptom information, this paper proposes methodological strategies for effectively recording and utilizing TCM symptom efficacy information in the era of big data. These strategies include collecting TCM symptom information based on patient reporting, standardizing the evaluation of TCM symptom efficacy from measurement scales and evaluation dimensions, integrating TCM symptom efficacy evaluation into clinical diagnosis and treatment processes, and utilizing artificial intelligence technology to acquire and process TCM symptom efficacy information. TCM symptom efficacy evaluation strategies based on patient perspectives and artificial intelligence technology will help fully explore the value of data elements, promote the objective demonstration of the specific efficacy of TCM, and facilitate the discovery of effective patterns.
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