|
|
Exchanging Chinese Medical Information Based on HL7 FHIR |
Sheng Shu1,Huang Qi1,2(),Yang Yang1,Xie Qiwen1,Qin Xinguo1,3 |
1School of Information Management, Nanjing University, Nanjing 210046, China 2Nanjing Research Based of National Information Management, Nanjing University, Nanjing 210093, China 3Information Office, Nanjing Audit University, Nanjing 211815, China |
|
|
Abstract [Objective] This paper explores the core framework of message exchange standard——Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR), aiming to standardize medical data formats and disease terms in Chinese. [Methods] We proposed a healthcare data interoperability method based on the FHIR framework. Then, we combined the ontology standardization conceptual model and the Disease Ontology to regulate the expression of disease terms, with ontology construction, mapping and migration techniques. [Results] We retrieved 176 pieces electronic medical records from the YiXiang platform with a Python crawler. After ontology mapping and migration, we fully standardized the medical records and disease term coding using the expression of FHIR data format. [Limitations] We did not standardize the semantics of heterogeneous medical data of multiple types. [Conclusions] This study provides a new perspective for constructing standard medical records system and related technology in China.
|
Received: 01 April 2021
Published: 26 August 2021
|
|
Corresponding Authors:
Huang Qi,ORCID:0000-0002-2806-3447
E-mail: huangqi@nju.edu.cn
|
[1] |
Topol E J. The Big Medical Data Miss: Challenges in Establishing an Open Medical Resource[J]. Nature Reviews Genetics, 2015, 16(5):253-254.
pmid: 26065035
|
[2] |
Pinto V B, de Oliveira R C R, Girão A I P T. SNOMED-CT as Standard Language for Organization and Representation of the Information in Patient Records[J]. Knowledge Organization, 2014, 41(4):311-318.
doi: 10.5771/0943-7444-2014-4
|
[3] |
Woods J W, Sneiderman C A, Hameed K, et al. Using UMLS Metathesaurus Concepts to Describe Medical Images: Dermatology Vocabulary[J]. Computers in Biology and Medicine, 2006, 36(1):89-100.
doi: 10.1016/j.compbiomed.2004.08.003
|
[4] |
Oemig F. HL7 Version 2.x Goes FHIR[J]. Studies in Health Technology and Informatics, 2019, 267:93-98.
|
[5] |
Catley C, Frize M. Design of a Health Care Architecture for Medical Data Interoperability and Application Integration[C]// Proceedings of the 2nd Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society IEEE, 2002: 1952-1953.
|
[6] |
Hussain M A, Langer S G, Kohli M. Learning HL7 FHIR Using the HAPI FHIR Server and Its Use in Medical Imaging with the SIIM Dataset[J]. Journal of Digital Imaging, 2018, 31(3):334-340.
doi: 10.1007/s10278-018-0090-y
|
[7] |
Maxhelaku S, Kika A. Improving Interoperability in Healthcare Using HL7 FHIR[C]// Proceedings of the 47th International Academic Conference. 2019: 9211566.
|
[8] |
Semenov I, Osenev R, Gerasimov S, et al. Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support[J]. International Journal of Environmental Research and Public Health, 2019, 17(1):E73.
|
[9] |
Kiourtis A, Mavrogiorgou A, Menychtas A, et al. Structurally Mapping Healthcare Data to HL7 FHIR Through Ontology Alignment[J]. Journal of Medical Systems, 2019, 43(3):43-62.
doi: 10.1007/s10916-019-1164-1
|
[10] |
Saripalle R, Runyan C, Russell M. Using HL7 FHIR to Achieve Interoperability in Patient Health Record[J]. Journal of Biomedical Informatics, 2019, 94:103188.
doi: S1532-0464(19)30106-6
pmid: 31063828
|
[11] |
Hong N, Wen A, Shen F C, et al. Developing a Scalable FHIR-Based Clinical Data Normalization Pipeline for Standardizing and Integrating Unstructured and Structured Electronic Health Record Data[J]. JAMIA Open, 2019, 2(4):570-579.
doi: 10.1093/jamiaopen/ooz056
pmid: 32025655
|
[12] |
Yan H C, Xiao L, Tian J B. Clinical Decision Support Based on FHIR Data Exchange Standard[C]// Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology. 2017: 424-430.
|
[13] |
Mukhiya S K, Rabbi F, Pun V K I, et al. A GraphQL Approach to Healthcare Information Exchange with HL7 FHIR[J]. Procedia Computer Science, 2019, 160:338-345.
doi: 10.1016/j.procs.2019.11.082
|
[14] |
Ullah F, Habib M A, Farhan M, et al. Semantic Interoperability for Big-Data in Heterogeneous IoT Infrastructure for Healthcare[J]. Sustainable Cities and Society, 2017, 34:90-96.
doi: 10.1016/j.scs.2017.06.010
|
[15] |
Katehakis D G, Kondylakis H, Koumakis L, et al. Integrated Care Solutions for the Citizen: Personal Health Record Functional Models to Support Interoperability[J]. European Journal for Biomedical Informatics, 2017, 13(1):48-56.
|
[16] |
Rivera S Y K, Demurjian S A, Baihan M S, et al. A Service-Based RBAC & MAC Approach Incorporated into the FHIR Standard[J]. Digital Communications and Networks, 2019, 5(4):214-225.
doi: 10.1016/j.dcan.2019.10.004
|
[17] |
Rajkomar A, Oren E, Chen K, et al. Scalable and Accurate Deep Learning with Electronic Health Records[J]. NPJ Digital Medicine, 2018, 1: Article No.18.
|
[18] |
何雨生, 王力华, 闫华. 国内首例HL7在医院信息系统集成中的应用[J]. 当代医学, 2002, 8(10):42-44.
|
[18] |
(He Yusheng, Wang Lihua, Yan Hua. The First Domestic Case of HL7 in the Integration of Hospital Information System[J]. China Contemporary Medicine, 2002, 8(10):42-44.)
|
[19] |
吴志禄, 李小坚. HL7标准的医保信息交换探究[C]// 全国冶金自动化信息网2011年年会论文集. 2011.
|
[19] |
(Wu Zhilu, Li Xiaojian. Research on HL7 Standard Medical Insurance Information Exchange[C]// Proceedings of the 2011 Annual Conference of National Metallurgical Automation Information Network. 2011.)
|
[20] |
唐春波, 郭文明, 严静东, 等. FHIR数据集成平台研究及其在连续医疗中的应用[J]. 生物医学工程研究, 2017, 36(2):178-182.
|
[20] |
(Tang Chunbo, Guo Wenming, Yan Jingdong, et al. The Research of Fast Healthcare Interoperability Resources Data Integration Platform and Its Application in Continuous Healthcare[J]. Journal of Biomedical Engineering Research, 2017, 36(2):178-182.)
|
[21] |
Al-Aswadi F N, Chan H Y, Gan K H. Automatic Ontology Construction from Text: A Review from Shallow to Deep Learning Trend[J]. Artificial Intelligence Review, 2020, 53(6):3901-3928.
doi: 10.1007/s10462-019-09782-9
|
[22] |
Alani H. Kim S, Millard D E, et al. Automatic Ontology-Based Knowledge Extraction from Web Documents[J]. IEEE Intelligent Systems, 2003, 18(1):14-21.
doi: 10.1109/MIS.2003.1234764
|
[23] |
Liu G, Zhang H W. An Ontology Constructing Technology Oriented on Massive Social Security Policy Documents[J]. Cognitive Systems Research, 2020, 60(5):97-105.
doi: 10.1016/j.cogsys.2019.09.005
|
[24] |
Fawei B, Pan J Z, Kollingbaum M, et al. A Semi-Automated Ontology Construction for Legal Question Answering[J]. New Generation Computing, 2019, 37(4):453-478.
doi: 10.1007/s00354-019-00070-2
|
[25] |
Zhuang L S, Schouten K, Frasincar F. SOBA: Semi-Automated Ontology Builder for Aspect-Based Sentiment Analysis[J]. Journal of Web Semantics, 2020, 60:100544.
doi: 10.1016/j.websem.2019.100544
|
[26] |
王思丽, 祝忠明, 刘巍, 等. 基于深度学习的领域本体概念自动获取方法研究[J]. 情报理论与实践, 2020, 43(3):145-152, 144.
|
[26] |
(Wang Sili, Zhu Zhongming, Liu Wei, et al. Method of Domain Ontology Concept Automatic Extraction Based on Deep Learning[J]. Information Studies: Theory & Application, 2020, 43(3):145-152, 144.)
|
[27] |
石湘, 刘萍. 基于知识元语义描述模型的领域知识抽取与表示研究——以信息检索领域为例[J]. 数据分析与知识发现, 2021, 5(4):123-133.
|
[27] |
(Shi Xiang, Liu Ping. Extraction and Representation of Domain Knowledge with Semantic Description Model and Knowledge Elements——Case Study of Information Retrieval[J]. Data Analysis and Knowledge Discovery, 2021, 5(4):123-133.)
|
[28] |
McMurray J, Zhu L, McKillop I, et al. Ontological Modeling of Electronic Health Information Exchange[J]. Journal of Biomedical Informatics, 2015, 56:169-178.
doi: 10.1016/j.jbi.2015.05.020
pmid: 26065983
|
[29] |
Plastiras P, O’Sullivan D M. Combining Ontologies and Open Standards to Derive a Middle Layer Information Model for Interoperability of Personal and Electronic Health Records[J]. Journal of Medical Systems, 2017, 41(12):1-15.
doi: 10.1007/s10916-016-0650-y
|
[30] |
Harrow I, Balakrishnan R, Jimenez-Ruiz E, et al. Ontology Mapping for Semantically Enabled Applications[J]. Drug Discovery Today, 2019, 24(10):2068-2075.
doi: S1359-6446(18)30421-5
pmid: 31158512
|
[31] |
Annane A, Bellahsene Z, Azouaou F, et al. Building an Effective and Efficient Background Knowledge Resource to Enhance Ontology Matching[J]. Journal of Web Semantics, 2018, 51(8):51-68.
doi: 10.1016/j.websem.2018.04.001
|
[32] |
Nakhla Z, Nouira K. Automatic Approach to Enrich Databases Using Ontology: Application in Medical Domain[J]. Procedia Computer Science, 2017, 112:387-396.
doi: 10.1016/j.procs.2017.08.221
|
[33] |
楼雯, 王慧, 鞠源. 基于二值相似度计算的异构本体融合方法[J]. 情报学报, 2019, 38(6):622-631.
|
[33] |
(Lou Wen, Wang Hui, Ju Yuan. An Ontology Fusion Method Based on Binary Similarity Calculation[J]. Journal of the China Society for Scientific and Technical Information, 2019, 38(6):622-631.)
|
[34] |
陈东华, 张润彤, 付磊, 等. SNOMED CT体系下医疗健康大数据映射和迁移方法研究[J]. 情报学报, 2018, 37(5):524-532.
|
[34] |
(Chen Donghua, Zhang Runtong, Fu Lei, et al. Mapping and Migration of Medical and Health Big Data with SNOMED CT[J]. Journal of the China Society for Scientific and Technical Information, 2018, 37(5):524-532.)
|
[35] |
Kiourtis A, Nifakos S, Mavrogiorgou A, et al. Aggregating the Syntactic and Semantic Similarity of Healthcare Data Towards Their Transformation to HL7 FHIR Through Ontology Matching[J]. International Journal of Medical Informatics, 2019, 132:104002.
doi: 10.1016/j.ijmedinf.2019.104002
|
[36] |
Kilintzis V, Chouvarda I, Beredimas N, et al. Supporting Integrated Care with a Flexible Data Management Framework Built Upon Linked Data, HL7 FHIR and Ontologies[J]. Journal of Biomedical Informatics, 2019, 94:103179.
doi: S1532-0464(19)30097-8
pmid: 31026596
|
[37] |
王兰成. 知识集成方法与技术: 知识组织与知识检索[M]. 北京: 国防工业出版社, 2010.
|
[37] |
(Wang Lancheng. Knowledge Integration Methods and Technologies——Knowledge Organization and Knowledge Retrieval[M]. Beijing: National Defense Industry Press, 2010.)
|
[38] |
Faria D, Pesquita C, Santos E, et al. The AgreementMakerLight Ontology Matching System[C]// Proceedings of OTM Confederated International Conferences “On the Move to Meaningful Internet Systems”. 2013: 527-541.
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|