Abstract：Reuse of clinical informationmodels (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 V3 2017 normative edition released by HL7.org as an example and applied an extended four-layer Bayesian network to represent this CIM. We enriched the hierarchicalmessage 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 3 428 nodes and 22 646 edges,from top to bottom,the number of nodes was 2 177,422,422,407 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.
黄晓硕, 杨林, 李姣. 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[J]. 中国生物医学工程学报, 2020, 39(4): 440-448.
Huang Xiaoshuo, Yang Lin, Li Jiao. A Method Based on Bayesian Network to Retrieve Clinical Information Models: A Case Study of HL7 V3. Chinese Journal of Biomedical Engineering, 2020, 39(4): 440-448.
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