医疗保健研究中分布式IT开发的开放、模块化和参与式工具链的开发和实现——经验教训。

Daniel Neumann, Richard Gebler, Jana Kiederle, Jördis Beck, Fabio Aubele, Alexander Struebing, Florian Schmidt, Matthias Reusche, Helene Koester, Markus Loeffler, Sebastian Staeubert
{"title":"医疗保健研究中分布式IT开发的开放、模块化和参与式工具链的开发和实现——经验教训。","authors":"Daniel Neumann, Richard Gebler, Jana Kiederle, Jördis Beck, Fabio Aubele, Alexander Struebing, Florian Schmidt, Matthias Reusche, Helene Koester, Markus Loeffler, Sebastian Staeubert","doi":"10.3233/SHTI251418","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Distributed healthcare research infrastructures face significant challenges when translating routine clinical data into harmonized, research-ready formats using HL7 FHIR standards.</p><p><strong>State of the art: </strong>Existing FHIR-based pipelines such as the SMART/HL7 FHIR Bulk Data Access API, FHIR-to-OMOP mappings, and analytical services like Pathling demonstrate technical feasibility. However, most assume semantically valid FHIR data, operate within single-institution settings, and lack practical guidance for deployment across heterogeneous, regulated environments. Technical Framework and Deployment: Within the German Medical Informatics Initiative (MII) and the INTERPOLAR project, we developed an open, modular, and participatory toolchain for decentralized FHIR-based data transformation and export across multiple Data Integration Centers (DICs). The toolchain supports FHIR extraction, profile-based transformation, REDCap integration, and OMOP-compatible export. Deployment required adapting to local infrastructures, regulatory boundaries (e.g., de-identified FHIR stores, restricted network access), and clinical domain needs. Configurable modules, proxy support, and site-specific adaptations were essential for integration into operational hospital workflows.</p><p><strong>Lessons learned: </strong>Key lessons include the necessity of early access to real data, the limitations of synthetic test data, the value of joint workshops for profile interpretation, and the need for adaptable validation tooling. Organizational knowledge gaps, inconsistent FHIR implementations, and performance issues in resource flattening were addressed through co-design and iterative rollout strategies. Validator modules are essential across technical, content, and cross-site consistency levels.</p><p><strong>Conclusion: </strong>Centralized development paired with decentralized, participatory deployment enables scalable, GDPR-compliant infrastructures for embedded clinical research. This approach offers a replicable framework for future multi-site initiatives aiming to leverage real-world data across diverse environments.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"331 ","pages":"378-385"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and Implementation of an Open, Modular, and Participatory Toolchain for Distributed IT Development in Healthcare Research - Lessons Learned.\",\"authors\":\"Daniel Neumann, Richard Gebler, Jana Kiederle, Jördis Beck, Fabio Aubele, Alexander Struebing, Florian Schmidt, Matthias Reusche, Helene Koester, Markus Loeffler, Sebastian Staeubert\",\"doi\":\"10.3233/SHTI251418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Distributed healthcare research infrastructures face significant challenges when translating routine clinical data into harmonized, research-ready formats using HL7 FHIR standards.</p><p><strong>State of the art: </strong>Existing FHIR-based pipelines such as the SMART/HL7 FHIR Bulk Data Access API, FHIR-to-OMOP mappings, and analytical services like Pathling demonstrate technical feasibility. However, most assume semantically valid FHIR data, operate within single-institution settings, and lack practical guidance for deployment across heterogeneous, regulated environments. Technical Framework and Deployment: Within the German Medical Informatics Initiative (MII) and the INTERPOLAR project, we developed an open, modular, and participatory toolchain for decentralized FHIR-based data transformation and export across multiple Data Integration Centers (DICs). The toolchain supports FHIR extraction, profile-based transformation, REDCap integration, and OMOP-compatible export. Deployment required adapting to local infrastructures, regulatory boundaries (e.g., de-identified FHIR stores, restricted network access), and clinical domain needs. Configurable modules, proxy support, and site-specific adaptations were essential for integration into operational hospital workflows.</p><p><strong>Lessons learned: </strong>Key lessons include the necessity of early access to real data, the limitations of synthetic test data, the value of joint workshops for profile interpretation, and the need for adaptable validation tooling. Organizational knowledge gaps, inconsistent FHIR implementations, and performance issues in resource flattening were addressed through co-design and iterative rollout strategies. Validator modules are essential across technical, content, and cross-site consistency levels.</p><p><strong>Conclusion: </strong>Centralized development paired with decentralized, participatory deployment enables scalable, GDPR-compliant infrastructures for embedded clinical research. This approach offers a replicable framework for future multi-site initiatives aiming to leverage real-world data across diverse environments.</p>\",\"PeriodicalId\":94357,\"journal\":{\"name\":\"Studies in health technology and informatics\",\"volume\":\"331 \",\"pages\":\"378-385\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies in health technology and informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/SHTI251418\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in health technology and informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI251418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

简介:分布式医疗保健研究基础设施在使用HL7 FHIR标准将常规临床数据转换为统一的研究就绪格式时面临重大挑战。现状:现有的基于FHIR的管道,如SMART/HL7 FHIR批量数据访问API, FHIR到omop映射,以及Pathling等分析服务,都证明了技术可行性。然而,大多数假设语义上有效的FHIR数据,在单一机构设置中运行,并且缺乏跨异构、受监管环境部署的实际指导。技术框架和部署:在德国医学信息学倡议(MII)和INTERPOLAR项目中,我们开发了一个开放、模块化和参与式的工具链,用于跨多个数据集成中心(dic)进行分散的基于fhr的数据转换和导出。工具链支持FHIR提取、基于概要文件的转换、REDCap集成和omop兼容的导出。部署需要适应本地基础设施、监管边界(例如,去识别的FHIR商店、受限制的网络访问)和临床领域需求。可配置模块、代理支持和特定于站点的调整对于集成到可操作的医院工作流程中至关重要。吸取的经验教训:主要的经验教训包括早期访问真实数据的必要性、综合测试数据的局限性、对剖面解释的联合研讨会的价值,以及对适应性验证工具的需求。通过协同设计和迭代推出策略,解决了组织知识差距、不一致的FHIR实现以及资源扁平化中的性能问题。验证器模块是跨技术、内容和跨站点一致性级别必不可少的。结论:集中式开发与分散的参与式部署相结合,可以为嵌入式临床研究提供可扩展的、符合gdpr的基础设施。这种方法为未来的多站点计划提供了一个可复制的框架,旨在利用不同环境中的真实数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and Implementation of an Open, Modular, and Participatory Toolchain for Distributed IT Development in Healthcare Research - Lessons Learned.

Introduction: Distributed healthcare research infrastructures face significant challenges when translating routine clinical data into harmonized, research-ready formats using HL7 FHIR standards.

State of the art: Existing FHIR-based pipelines such as the SMART/HL7 FHIR Bulk Data Access API, FHIR-to-OMOP mappings, and analytical services like Pathling demonstrate technical feasibility. However, most assume semantically valid FHIR data, operate within single-institution settings, and lack practical guidance for deployment across heterogeneous, regulated environments. Technical Framework and Deployment: Within the German Medical Informatics Initiative (MII) and the INTERPOLAR project, we developed an open, modular, and participatory toolchain for decentralized FHIR-based data transformation and export across multiple Data Integration Centers (DICs). The toolchain supports FHIR extraction, profile-based transformation, REDCap integration, and OMOP-compatible export. Deployment required adapting to local infrastructures, regulatory boundaries (e.g., de-identified FHIR stores, restricted network access), and clinical domain needs. Configurable modules, proxy support, and site-specific adaptations were essential for integration into operational hospital workflows.

Lessons learned: Key lessons include the necessity of early access to real data, the limitations of synthetic test data, the value of joint workshops for profile interpretation, and the need for adaptable validation tooling. Organizational knowledge gaps, inconsistent FHIR implementations, and performance issues in resource flattening were addressed through co-design and iterative rollout strategies. Validator modules are essential across technical, content, and cross-site consistency levels.

Conclusion: Centralized development paired with decentralized, participatory deployment enables scalable, GDPR-compliant infrastructures for embedded clinical research. This approach offers a replicable framework for future multi-site initiatives aiming to leverage real-world data across diverse environments.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信