Pathling: analytics on FHIR.

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
John Grimes, Piotr Szul, Alejandro Metke-Jimenez, Michael Lawley, Kylynn Loi
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引用次数: 3

Abstract

Background: Health data analytics is an area that is facing rapid change due to the acceleration of digitization of the health sector, and the changing landscape of health data and clinical terminology standards. Our research has identified a need for improved tooling to support analytics users in the task of analyzing Fast Healthcare Interoperability Resources (FHIR®) data and associated clinical terminology.

Results: A server implementation was developed, featuring a FHIR API with new operations designed to support exploratory data analysis (EDA), advanced patient cohort selection and data preparation tasks. Integration with a FHIR Terminology Service is also supported, allowing users to incorporate knowledge from rich terminologies such as SNOMED CT within their queries. A prototype user interface for EDA was developed, along with visualizations in support of a health data analysis project.

Conclusions: Experience with applying this technology within research projects and towards the development of analytics-enabled applications provides a preliminary indication that the FHIR Analytics API pattern implemented by Pathling is a valuable abstraction for data scientists and software developers within the health care domain. Pathling contributes towards the value proposition for the use of FHIR within health data analytics, and assists with the use of complex clinical terminologies in that context.

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路径:FHIR分析。
背景:由于卫生部门数字化的加速以及卫生数据和临床术语标准的变化,卫生数据分析是一个面临快速变化的领域。我们的研究发现需要改进工具来支持分析用户分析快速医疗保健互操作性资源(FHIR®)数据和相关临床术语的任务。结果:开发了一个服务器实现,具有FHIR API和新操作,旨在支持探索性数据分析(EDA),高级患者队列选择和数据准备任务。还支持与FHIR术语服务的集成,允许用户将来自丰富术语(如SNOMED CT)的知识合并到他们的查询中。开发了EDA的原型用户界面,以及支持健康数据分析项目的可视化。结论:在研究项目中应用该技术以及开发支持分析的应用程序的经验初步表明,Pathling实现的FHIR Analytics API模式对于医疗保健领域的数据科学家和软件开发人员来说是一个有价值的抽象。Pathling有助于在卫生数据分析中使用FHIR的价值主张,并协助在这方面使用复杂的临床术语。
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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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