islEHR, a model for electronic health records interoperability

Author:

Najjar Arwa1,Amro Belal1,Macedo Mário2

Affiliation:

1. Information Technology College, Hebron University , Hebron , Palestine

2. Sciences and Technologies of Information and Communication College, Atlântica University , Lisbon , Portugal

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Health Informatics,Biochemistry, Genetics and Molecular Biology (miscellaneous),Medicine (miscellaneous),General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data Extraction and Integration from Unstructured Electronic Health Records;2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS);2023-11-01

2. HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study;Sensors;2022-05-15

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