Abstract
Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution of this paper is to propose and implement a fuzzy ontology-based semantic interoperability framework for distributed EHR systems. First, a separate standard ontology is created for each input source. Second, a unified ontology is created that merges the previously created ontologies. However, this crisp ontology is not able to answer vague or uncertain queries. We thirdly extend the integrated crisp ontology into a fuzzy ontology by using a standard methodology and fuzzy logic to handle this limitation. The used dataset includes identified data of 100 patients. The resulting fuzzy ontology includes 27 class, 58 properties, 43 fuzzy data types, 451 instances, 8376 axioms, 5232 logical axioms, 1216 declarative axioms, 113 annotation axioms, and 3204 data property assertions. The resulting ontology is tested using real data from the MIMIC-III intensive care unit dataset and real archetypes from openEHR. This fuzzy ontology-based system helps physicians accurately query any required data about patients from distributed locations using near-natural language queries. Domain specialists validated the accuracy and correctness of the obtained results.
Highlights
With the increasing expansion of medical science, traditional handwriting health records have not been adequate for recording the massive quantity of information
We found that various techniques were proposed to solve the SI problem in distributed electronic health record (EHR) [37,40,50]
Concerning Data source #1, the main table was transformed to an OWL class “PatientTests”, all 8 columns were mapped into 8 Datatype Properties, and 100 records were successfully mapped to 100 individuals of the constructed ontology
Summary
With the increasing expansion of medical science, traditional handwriting health records have not been adequate for recording the massive quantity of information. Information technology (IT) has to play a prime role in the healthcare system redesigning to improve substantial quality [1]. In the 1960s and 70s, new computer technology was developed, leading to the development of the electronic health record (EHR). Early efforts for EHRs development began [2]. EHR is an electronic repository for all individual’s lifetime health information [3]. EHRs support efficient, quality, and persistent integrated healthcare, improving the medical domain [4]
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