• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

使用FHIR映射语言实现健康数据的互操作性：通过可重复使用的可视化组件将HL7 CDA转换为FHIR

Interoperability of health data using FHIR Mapping Language: transforming HL7 CDA to FHIR with reusable visual components.

作者信息

Bossenko Igor, Randmaa Rainer, Piho Gunnar, Ross Peeter

机构信息

Department of Software Science, Tallinn University of Technology (TalTech), Tallinn, Estonia.

Department of Health Technologies, TalTech, Tallinn, Estonia.

出版信息

Front Digit Health. 2024 Dec 19;6:1480600. doi: 10.3389/fdgth.2024.1480600. eCollection 2024.

DOI:10.3389/fdgth.2024.1480600
PMID:39749099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11693713/
Abstract

INTRODUCTION

Ecosystem-centered healthcare innovations, such as digital health platforms, patient-centric records, and mobile health applications, depend on the semantic interoperability of health data. This ensures efficient, patient-focused healthcare delivery in a mobile world where citizens frequently travel for work and leisure. Beyond healthcare delivery, semantic interoperability is crucial for secondary health data use. This paper introduces a tool and techniques for achieving health data semantic interoperability, using reusable visual transformation components to create and validate transformation rules and maps, making them usable for domain experts with minimal technical skills.

METHODS

The tool and techniques for health data semantic interoperability have been developed and validated using Design Science, a common methodology for developing software artifacts, including tools and techniques.

RESULTS

Our tool and techniques are designed to facilitate the interoperability of Electronic Health Records (EHRs) by enabling the seamless unification of various health data formats in real time, without the need for extensive physical data migrations. These tools simplify complex health data transformations, allowing domain experts to specify and validate intricate data transformation rules and maps. The need for such a solution arises from the ongoing transition of the Estonian National Health Information System (ENHIS) from Clinical Document Architecture (CDA) to Fast Healthcare Interoperability Resources (FHIR), but it is general enough to be used for other data transformation needs, including the European Health Data Space (EHDS) ecosystem.

CONCLUSION

The proposed tool and techniques simplify health data transformation by allowing domain experts to specify and validate the necessary data transformation rules and maps. Evaluation by ENHIS domain experts demonstrated the usability, effectiveness, and business value of the tool and techniques.

摘要

引言

以生态系统为中心的医疗保健创新，如数字健康平台、以患者为中心的记录和移动健康应用程序，依赖于健康数据的语义互操作性。这确保了在一个公民经常因工作和休闲而出行的移动世界中，能够高效地提供以患者为中心的医疗保健服务。除了医疗保健服务，语义互操作性对于二次健康数据的使用也至关重要。本文介绍了一种实现健康数据语义互操作性的工具和技术，使用可重复使用的可视化转换组件来创建和验证转换规则及映射，使技术技能有限的领域专家也能使用。

方法

健康数据语义互操作性的工具和技术是使用设计科学开发和验证的，设计科学是一种开发软件工件（包括工具和技术）的常用方法。

结果

我们的工具和技术旨在通过实时无缝统一各种健康数据格式来促进电子健康记录（EHR）的互操作性，而无需进行大量的物理数据迁移。这些工具简化了复杂的健康数据转换，使领域专家能够指定和验证复杂的数据转换规则及映射。对这种解决方案的需求源于爱沙尼亚国家健康信息系统（ENHIS）正在从临床文档架构（CDA）向快速医疗保健互操作性资源（FHIR）的转变，但它具有足够的通用性，可用于其他数据转换需求，包括欧洲健康数据空间（EHDS）生态系统。

结论

所提出的工具和技术通过允许领域专家指定和验证必要的数据转换规则及映射，简化了健康数据转换。ENHIS领域专家的评估证明了该工具和技术的可用性、有效性和商业价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/90e26938ad1c/fdgth-06-1480600-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/00181404bd3b/fdgth-06-1480600-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/37231bee280c/fdgth-06-1480600-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/1f4d2607262e/fdgth-06-1480600-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/336a17b1a9bc/fdgth-06-1480600-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/535fa96e0646/fdgth-06-1480600-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/dd67d8397c6c/fdgth-06-1480600-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/d9263b760b1b/fdgth-06-1480600-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/d78bc300c091/fdgth-06-1480600-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/fcf52cd7482f/fdgth-06-1480600-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/e2fb5167b6ab/fdgth-06-1480600-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/9ec0e319b905/fdgth-06-1480600-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/4506b010b567/fdgth-06-1480600-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/90e26938ad1c/fdgth-06-1480600-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/00181404bd3b/fdgth-06-1480600-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/37231bee280c/fdgth-06-1480600-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/1f4d2607262e/fdgth-06-1480600-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/336a17b1a9bc/fdgth-06-1480600-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/535fa96e0646/fdgth-06-1480600-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/dd67d8397c6c/fdgth-06-1480600-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/d9263b760b1b/fdgth-06-1480600-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/d78bc300c091/fdgth-06-1480600-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/fcf52cd7482f/fdgth-06-1480600-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/e2fb5167b6ab/fdgth-06-1480600-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/9ec0e319b905/fdgth-06-1480600-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/4506b010b567/fdgth-06-1480600-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e2c/11693713/90e26938ad1c/fdgth-06-1480600-g013.jpg

相似文献

1
Interoperability of health data using FHIR Mapping Language: transforming HL7 CDA to FHIR with reusable visual components.使用FHIR映射语言实现健康数据的互操作性：通过可重复使用的可视化组件将HL7 CDA转换为FHIR
Front Digit Health. 2024 Dec 19;6:1480600. doi: 10.3389/fdgth.2024.1480600. eCollection 2024.
2
Electronic Health Record and Semantic Issues Using Fast Healthcare Interoperability Resources: Systematic Mapping Review.电子健康记录与 Fast Healthcare Interoperability Resources 的语义问题：系统映射综述。
J Med Internet Res. 2024 Jan 30;26:e45209. doi: 10.2196/45209.
3
Aggregating the syntactic and semantic similarity of healthcare data towards their transformation to HL7 FHIR through ontology matching.通过本体匹配，聚合医疗保健数据的语法和语义相似性，以将其转换为 HL7 FHIR。
Int J Med Inform. 2019 Dec;132:104002. doi: 10.1016/j.ijmedinf.2019.104002. Epub 2019 Oct 5.
4
A Data Transformation Methodology to Create Findable, Accessible, Interoperable, and Reusable Health Data: Software Design, Development, and Evaluation Study.一种创建可发现、可访问、可互操作和可重用健康数据的数据转换方法：软件设计、开发和评估研究。
J Med Internet Res. 2023 Mar 8;25:e42822. doi: 10.2196/42822.
5
A Generic Transformation Approach for Complex Laboratory Data Using the Fast Healthcare Interoperability Resources Mapping Language: Method Development and Implementation.使用快速医疗互操作性资源映射语言对复杂实验室数据进行通用转换方法：方法开发与实施。
JMIR Med Inform. 2024 Oct 18;12:e57569. doi: 10.2196/57569.
6
An HL7 FHIR and GraphQL approach for interoperability between heterogeneous Electronic Health Record systems.HL7 FHIR 和 GraphQL 方法在异构电子健康记录系统之间的互操作性。
Health Informatics J. 2021 Jul-Sep;27(3):14604582211043920. doi: 10.1177/14604582211043920.
7
Bridging the Gap between HL7 CDA and HL7 FHIR: A JSON Based Mapping.弥合HL7 CDA与HL7 FHIR之间的差距：基于JSON的映射
Stud Health Technol Inform. 2016;223:100-6.
8
PCEtoFHIR: Decomposition of Postcoordinated SNOMED CT Expressions for Storage as HL7 FHIR Resources.PCEtoFHIR：用于存储为 HL7 FHIR 资源的后协调 SNOMED CT 表达式的分解。
JMIR Med Inform. 2024 Sep 17;12:e57853. doi: 10.2196/57853.
9
HL7 Fast Healthcare Interoperability Resources (HL7 FHIR) in digital healthcare ecosystems for chronic disease management: Scoping review.HL7 快速医疗互操作性资源 (HL7 FHIR) 在慢性病管理的数字医疗生态系统中的应用：范围综述。
Int J Med Inform. 2024 Sep;189:105507. doi: 10.1016/j.ijmedinf.2024.105507. Epub 2024 Jun 4.
10
Designing Interoperable Health Care Services Based on Fast Healthcare Interoperability Resources: Literature Review.基于快速医疗互操作性资源设计可互操作的医疗服务：文献综述
JMIR Med Inform. 2023 Aug 21;11:e44842. doi: 10.2196/44842.

引用本文的文献

1
SQL on FHIR - Tabular views of FHIR data using FHIRPath.基于FHIR的SQL——使用FHIRPath的FHIR数据表格视图。
NPJ Digit Med. 2025 Jun 9;8(1):342. doi: 10.1038/s41746-025-01708-w.

本文引用的文献

1
TermX: A Game Changer in the Healthcare Interoperability.TermX：医疗互操作性的游戏规则改变者。
Stud Health Technol Inform. 2024 Aug 22;316:88-89. doi: 10.3233/SHTI240352.
2
A reference architecture for personal health data spaces using decentralized content-addressable storage networks.一种使用去中心化内容可寻址存储网络的个人健康数据空间参考架构。
Front Med (Lausanne). 2024 Jul 16;11:1411013. doi: 10.3389/fmed.2024.1411013. eCollection 2024.
3
Artificial intelligence based data curation: enabling a patient-centric European health data space.
基于人工智能的数据整理：构建以患者为中心的欧洲健康数据空间。
Front Med (Lausanne). 2024 May 15;11:1365501. doi: 10.3389/fmed.2024.1365501. eCollection 2024.
4
The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.设计和管理 5P 医学生态系统的代表性挑战。
Stud Health Technol Inform. 2024 May 23;314:3-13. doi: 10.3233/SHTI240047.
5
Dual Implementation Guides in FHIR and CDA.FHIR 和 CDA 中的双重实现指南。
Stud Health Technol Inform. 2024 Apr 26;313:49-54. doi: 10.3233/SHTI240011.
6
Now Is the Time to Strengthen Government-Academic Data Infrastructures to Jump-Start Future Public Health Crisis Response.现在是加强政府-学术数据基础设施以启动未来公共卫生危机应对的时候了。
JMIR Public Health Surveill. 2024 Apr 24;10:e51880. doi: 10.2196/51880.
7
EHDS and Free Movement of Patients: What EU Intervention is Needed?EHDS 与患者自由流动：欧盟需要何种干预？
Eur J Health Law. 2024 Apr 12;31(3):249-284. doi: 10.1163/15718093-bja10125.
8
A Semantic Approach to Describe Social and Economic Characteristics That Impact Health Outcomes (Social Determinants of Health): Ontology Development Study.一种描述影响健康结果的社会和经济特征（健康的社会决定因素）的语义方法：本体开发研究。
Online J Public Health Inform. 2024 Mar 13;16:e52845. doi: 10.2196/52845.
9
Patients' knowledge, preferences, and perspectives about data protection and data control: an exploratory survey.患者对数据保护和数据控制的认知、偏好及观点：一项探索性调查。
Front Pharmacol. 2024 Feb 20;14:1280173. doi: 10.3389/fphar.2023.1280173. eCollection 2023.
10
Principles and Standards for Designing and Managing Integrable and Interoperable Transformed Health Ecosystems.设计和管理可整合、互操作的转型健康生态系统的原则与标准。
J Pers Med. 2023 Nov 4;13(11):1579. doi: 10.3390/jpm13111579.