AIDBMay 10, 2023

Building Interoperable Electronic Health Records as Purpose-Driven Knowledge Graphs

arXiv:2305.06088v1
Originality Incremental advance
AI Analysis

This addresses interoperability issues in eHealth for healthcare providers and developers, but it appears incremental as it builds on existing standards like FHIR.

The paper tackles the challenge of reusing and integrating existing knowledge in electronic health records by proposing iTelos, a methodology that independently develops data and schema levels guided by purpose-driven competence queries, validated through a large-scale case study.

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.

Code Implementations1 repo
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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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