Semantic Interoperability and Data Mapping in EHR Systems
Open accessAbstract
We present our preliminary research work intended to lay the foundation for providing a cost effective, secure and reliable system for real time clinical data acquisition required for analysis. We identify a specific problem, namely the need to achieve interoperability by applying a standards based data modeling approach to achieve a common platform that serves to improve the health data mapping of unstructured data and addresses ambiguity issues when dealing with health data from heterogeneous systems. We propose an original algorithm directed at mapping unstructured data and performing semantic integration to form a uniform interoperable system. In order to achieve this, efficient data modeling techniques are introduced for improving data storage and extraction, as demonstrated by our preliminary results.
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In the reviewed literature, interoperability was more at the semantic level.
“Based on results, Interoperability was more at the semantic level.”
From Interoperability of heterogeneous health information systems: a systematic literature review (2023) · cites this paper as [25]
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Interoperability of heterogeneous health information systems: a systematic literature review
Torab-Miandoab, A., Samad-Soltani, T., Jodati, A., & Rezaei-Hachesu, P. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02115-5 · Cited by 393 · see citing works
- Authors
- Janaswamy, S., & Kent, R. D.
- Affiliations
- University of Windsor (CA)
- Venue
- 2016 IEEE 6th International Conference on Advanced Computing (IACC)
- Publisher
- IEEE
- Published
- 2016-02
- Pages
- 117-122
- OpenAlex
- W2511207473
- Cited by
- 11
- References
- 36
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 2 · 2019: 2
- FWCI
- 0.93
- Type
- conference paper
- Language
- en
- Open access
- green
- scholar.uwindsor.ca
- Licence
- cc-by-nc-nd
- Locations
- IEEE International Conference on Advanced Computing (IACC) (publishedVersion)
- Scholarship at UWindsor (University of Windsor) (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Keywords
- semantic interoperability, electronic health records, data mapping, unstructured clinical data, semantic integration, data modeling
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