基于临床医疗科研信息共享系统，利用复杂网络开展河南中医学院第一附属医院慢阻肺基地慢性阻塞性肺疾病急性加重期（AECOPD）证候分布及中药组合研究，分析研究河南中医学院第一附属医院慢阻肺基地AECOPD诊疗常见证候分布规律及中药核心药组组合特点。方法是利用临床医疗科研信息共享系统，开展河南中医学院第一附属医院AECOPD数据研究（2012年8月-2015年1月3 000份格式化电子病历），通过ETL软件进行数据处理，构建数据库，运用复杂网络进行数据挖掘，获取河南中医学院第一附属医院AECOPD数据常见证候分布及中药药组组合研究资料。挖掘结果是常见证候分布为：痰热壅肺41.94%、痰浊阻肺22.97%、痰湿阻肺10.30%、气阴两虚6.31%、痰瘀阻肺5.72% 、肺肾气虚4.01%、肺脾气虚1.15%、痰蒙神窍1.15%。中药组合明显分2大组合，每一组合有核心中药组和关联中药组。基于以上结果分析，临床医疗科研信息共享系统，有很好的联想分析归类作用，不仅可以分析老中医专家个人的及单个医院单个病种的临床治疗用药规律，而且可用于大数据（全国性中医临床研究基地单病种及多病种的数据汇总）的分析研究，为中医的临床科研研究提供一个很好的平台。

Based on clinical research and information-sharing system, this article was aimed to study both the syndrome distribution and Chinese medicine composition of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the COPD base of our hospital using the complex networks. The analysis was made on the common rules of syndrome distribution and features of key Chinese medicine compositions in the diagnosis and treatment of AECOPD. The clinical research and information-sharing system was used on the AECOPD data study (3000 hospital electronic medical records from August 2012 to January 2015). Data was processed by ETL software. The database was constructed. And the complex networks were used in the data mining. The results showed that the distribution of AECOPD common syndromes was heat-phlegm obstructing lung of 41.94%, phlegm-turbid obstructing lung of 22.97%, phlegm-damp obstructing lung of 10.30%, qi-yin deficiency of 6.31%, phlegm-stasis obstructing lung of 5.72%, lung-kidney qi-deficiency of 4.01%, lung-spleen qi-deficiency of 1.15%, and phlegm obstructing orifices of 1.15%. Chinese medicine compositions were obviously divided into two large groups, which were the core Chinese medicine group and the associated Chinese medicine group. The research results illustrated that the clinical research and information-sharing system had good analysis and classification effects, which not only analyzing the medication laws of senior Chinese medicine experts and single disease treatment by a hospital, but also using in the large data analysis (data collection of single or multiple diseases on Chinese medicine clinical research nationally). It provided a good scientific research platform for Chinese medicine.

国家中医药管理局2012中医药行业科研专项（HY12079675）：全国中医医疗与临床科研信息共享推广与应用研究， 负责人：李真 。