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islEHR, a model for electronic health records interoperability

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dc.contributor.author Amro, Belal
dc.contributor.author Najjar, Arwa
dc.contributor.author Macido, Mario
dc.date.accessioned 2022-03-29T09:38:16Z
dc.date.available 2022-03-29T09:38:16Z
dc.date.issued 2022-03-17
dc.identifier.citation Najjar, A., Amro, B. & Macedo, M. (2022). islEHR, a model for electronic health records interoperability. Bio-Algorithms and Med-Systems, (). https://doi.org/10.1515/bams-2021-0117 en_US
dc.identifier.uri http://dspace.hebron.edu:80/xmlui/handle/123456789/1125
dc.description.abstract Objectives Due to the diversity, volume, and distribution of ingested data, the majority of current healthcare entities operate independently, increasing the problem of data processing and interchange. The goal of this research is to design, implement, and evaluate an electronic health record (EHR) interoperability solution – prototype – among healthcare organizations, whether these organizations do not have systems that are prepared for data sharing, or organizations that have such systems. Methods We established an EHR interoperability prototype model named interoperability smart lane for electronic health record (islEHR), which comprises of three modules: 1) a data fetching APIs for external sharing of patients’ information from participant hospitals; 2) a data integration service, which is the heart of the islEHR that is responsible for extracting, standardizing, and normalizing EHRs data leveraging the fast healthcare interoperability resources (FHIR) and artificial intelligence techniques; 3) a RESTful API that represents the gateway sits between clients and the data integration services. Results The prototype of the islEHR was evaluated on a set of unstructured discharge reports. The performance achieved a total time of execution ranging from 0.04 to 84.49 s. While the accuracy reached an F-Score ranging from 1.0 to 0.89. Conclusions According to the results achieved, the islEHR prototype can be implemented among different heterogeneous systems regardless of their ability to share data. The prototype was built based on international standards and machine learning techniques that are adopted worldwide. Performance and correctness results showed that islEHR outperforms existing models in its diversity as well as correctness and performance. en_US
dc.language.iso en en_US
dc.publisher De Gruyter en_US
dc.subject electronic health record en_US
dc.subject fast healthcare interoperability resources en_US
dc.subject interoperability en_US
dc.subject machine learning en_US
dc.subject natural language processing en_US
dc.title islEHR, a model for electronic health records interoperability en_US
dc.type Article en_US


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