基于贝叶斯网络的临床信息模型检索方法研究:以HL7 V3为例  

A Method Based on Bayesian Network to Retrieve Clinical Information Models:A Case Study of HL7 V3

作　　者：黄晓硕 杨林[1] 李姣[1] Huang Xiaoshuo;Yang Lin;Li Jiao(Institute of Medical Information/Medical Library,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100020,China)

机构地区：[1]中国医学科学院/北京协和医学院医学信息研究所/图书馆,北京100020

出　　处：《中国生物医学工程学报》2020年第4期440-448,共9页Chinese Journal of Biomedical Engineering

基　　金：国家重点研发计划(2016YFC0901901);中国医学科学院医学与健康科技创新工程(2018-I2M-AI-016)。

摘　　要：临床信息模型的可复用性是实现健康医疗信息互联互通和共享的重要基础,检索并识别出临床信息模型中可复用的对象是提高复用性的一种有效途径。以HL7.org发布的HL7 V32017标准版本为研究对象,应用扩展的4层贝叶斯网络表征该临床信息模型,在简单贝叶斯网络的基础上增加分层消息描述(HMD)之间语义相似性的扩展层,通过网络的逐层概率推演识别出可复用的临床信息模型。实验设计"就诊预约"、"实验室结果"和"病人实体"等3个检索任务,并应用平均精度均值MAP、平均精度AP和截止点准确率等3个指标以评价检索方法的性能。最终构建含有3428个节点和22646条边的4层贝叶斯网络,自上而下依次为数据元素层、HMD层、重复的HMD层和消息类型层,各层节点数量分别为2177、422、422和407。检索结果显示,MAP值达到了0.382,在第3、第5和第10截止点的平均准确率分别达到77.8%、60.0%和46.7%;该方法不仅可以检索出通用型和领域型两类可复用模型,还能够发现临床语义切实相关的对象(例如检索"就诊预约"时返回的"预约更新通知"对象)。所提出的方法将有助于提高HL7 V3信息模型的复用性,并促进临床信息标准的国际化建设,同时对其他临床信息模型检索方法的优化和改进存在一定的借鉴意义。Reuse of clinical information models(CIMs)is important for the interoperability of electronic health records.Retrieving and identifying reusable CIMs is an efficient way.In this study,we used the HL7 V32017 normative edition released by HL7.org as an example and applied an extended four-layer Bayesian network to represent this CIM.We enriched the hierarchical message description(HMD)layer based on the simple Bayesian network,and calculated the semantic similarity between them.Thereafter,the reusable CIMs were identified through probability inferencing in the network.In the evaluation,we designed three retrieval tasks(“encounter appointment”,“laboratory result“and“patient entity”),and used MAP(mean average precision),AP(average precision),accuracy at cut-off point as evaluation metrics.Finally,we constructed a four-layer Bayesian network with 3428 nodes and 22646 edges,from top to bottom,the number of nodes was 2177,422,422,407 for data element layer,HMD layer,duplicate HMD layer and message type layer respectively.Results showed that the value of MAP was 0.382,and the average accuracy at 3rd,5th and 10th cut-off points was 77.8%,60.0%and 46.7%respectively.Our method was capable to retrieve general models and domain reusable models,as well as semantic related objects(such as“reschedule appointment notification“object in“encounter appointment”retrieval task).In summary,our method could help improve reusability of HL7 V3 CIMs as well as international standardization of clinical information,meanwhile,it could be useful for the optimization of other CIMs retrieval.

关 键 词：HL7 V3 贝叶斯网络 临床信息模型 信息检索 

分 类 号：R318[医药卫生—生物医学工程]