Distributed Electronic Health Records Semantic Interoperability Based on a Fuzzy Ontology Architecture

Author(s):  
Ebtsam Adel ◽  
Sherif Barakat ◽  
Mohammed Elmogy
2007 ◽  
Vol 46 (03) ◽  
pp. 332-343 ◽  
Author(s):  
P. Knaup ◽  
E. J. S. Hovenga ◽  
S. Heard ◽  
S. Garde

Summary Objectives: In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability. Methods: Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees. Results: The openEHR archetypes approach enables syntactic interoperability and semantic interpretability – both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology. Conclusions: To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, ‘rank growth’ of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.


Author(s):  
Shivani Batra ◽  
Shelly Sachdeva

EHRs aid in maintaining longitudinal (lifelong) health records constituting a multitude of representations in order to make health related information accessible. However, storing EHRs data is non-trivial due to the issues of semantic interoperability, sparseness, and frequent evolution. Standard-based EHRs are recommended to attain semantic interoperability. However, standard-based EHRs possess challenges (in terms of sparseness and frequent evolution) that need to be handled through a suitable data model. The traditional RDBMS is not well-suited for standardized EHRs (due to sparseness and frequent evolution). Thus, modifications to the existing relational model is required. One such widely adopted data model for EHRs is entity attribute value (EAV) model. However, EAV representation is not compatible with mining tools available in the market. To style the representation of EAV, as per the requirement of mining tools, pivoting is required. The chapter explains the architecture to organize EAV for the purpose of preparing the dataset for use by existing mining tools.


2013 ◽  
Vol 58 (2) ◽  
pp. 81-89 ◽  
Author(s):  
Hua-Qiong Wang ◽  
Jing-Song Li ◽  
Yi-Fan Zhang ◽  
Muneou Suzuki ◽  
Kenji Araki

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Arjmand Naveed

The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique.  Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders.


2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Arjmand Naveed, T Sigwele, Yim Fun Hu, M Kamala, Misfa Susanto

The use of Electronic Health Records (EHR) in healthcare has the potential of reducing medical errors, minimizing healthcare cost and significantly improving the healthcare service quality. However, there is a barrier in healthcare data and information exchange between various healthcare systems due to the lack of interoperability. Also, with the implementation of EHR system, there are security and privacy concerns in the storage and transferring data entities.  The healthcare interoperability problem remains an issue of further research and this paper proposes a semantic interoperability framework for solving  this problem by allowing healthcare stakeholders and organizations (doctors, clinics, hospitals)using various healthcare standards to exchange data and its semantics, which can be understood by both machines and humans. Moreover, the proposed framework takes into consideration the security aspects in the semantic interoperability framework by utilizing data encryption and other technologies to secure the communication for the EHR information while ensuring real time data availability.                                                                                                  Keywords:. Semantic interoperability; Interoperability standards; Electronic Health records(EHR); Artifical Intelligence Techniques. Natural Language Processing (NLP), Word2Vec, skip gram, CBOW


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