Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jun 16, 2021
Open Peer Review Period: Jun 16, 2021 - Jun 24, 2021
Date Accepted: Aug 1, 2021
(closed for review but you can still tweet)
Verifying the feasibility of implementing semantic interoperability based on openEHR approach between different countries: A case study using Acute Coronary Syndrome Registry
ABSTRACT
Background:
The semantic interoperability of healthcare information has been a critical challenge of medical informatics, influencing the integration, sharing, analyzing, and utilizing medical big data. International standard organizations have developed standards, approaches, and models to improve and implement semantic interoperability. The openEHR approach, one of the standouts, has been implemented worldwide for improving semantic interoperability based on reused archetypes.
Objective:
This paper aims to verify the feasibility of semantic interoperability between different countries by comparing openEHR based information modelling of two acute coronary syndrome (ACS) registries in China and New Zealand.
Methods:
An archetype semantic comparison method is proposed to determine the reused archetypes' semantics reuse degree in two ACS-related clinical registries from two countries. It comprises: 1) determining the scope of reused archetypes; 2) determining corresponding data items within corresponding archetypes; 3) comparing the semantics of corresponding data items; 4) calculating the number of mappings in corresponding data items and analyzing results.
Results:
Among the related archetypes in two ACS-related clinical registries based on openEHR from China and New Zealand, there are eight pairs of reusable archetypes, including 89 pairs of corresponding data items and 120 non-corresponding data items. In these corresponding data item pairs, 87 pairs (97.75%) are mappable supporting semantic interoperability, and 71 pairs (79.78%) are direct mapping. Among the non-corresponding data items, 114 (95%) data items were generated by archetype evolution, and 6 (5%) data items were generated by archetype localization.
Conclusions:
The semantic comparison results between the two ACS-related clinical registries prove the feasibility of establishing semantic interoperability of healthcare data between different countries based on openEHR. Archetype reuse provides the degree to which semantic interoperability exists when using openEHR. Although the openEHR community has effectively promoted archetype reuse and semantic interoperability by providing archetype modeling methods, tools, models repository and archetype design patterns, uncontrolled evolution of archetypes and inconsistent localization create major challenges for achieving higher levels of semantic interoperability.
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