Building Interoperable Electronic Health Records as Purpose-Driven Knowledge Graphs

CoRR(2023)

引用 0|浏览21
暂无评分
摘要
When building a new application we are increasingly confronted with the need of reusing and integrating pre-existing knowledge. Nevertheless, it is a fact that this prior knowledge is virtually impossible to reuse as-is. This is true also in domains, e.g., eHealth, where a lot of effort has been put into developing high-quality standards and reference ontologies, e.g. FHIR1. In this paper, we propose an integrated methodology, called iTelos, which enables data and knowledge reuse towards the construction of Interoperable Electronic Health Records (iEHR). The key intuition is that the data level and the schema level of an application should be developed independently, thus allowing for maximum flexibility in the reuse of the prior knowledge, but under the overall guidance of the needs to be satisfied, formalized as competence queries. This intuition is implemented by codifying all the requirements, including those concerning reuse, as part of a purpose defined a priori, which is then used to drive a middle-out development process where the application schema and data are continuously aligned. The proposed methodology is validated through its application to a large-scale case study.
更多
查看译文
关键词
interoperable electronic health records,knowledge graphs,purpose-driven
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要