Electronical Health Record's Systems. Interoperability

Understanding the importance that the electronic medical health records system has, with its various structural types and grades, has led to the elaboration of a series of standards and quality control methods, meant to control its functioning. In time, the electronic health records system has evolved along with the medical data's change of structure. Romania has not yet managed to fully clarify this concept, various definitions still being encountered, such as "Patient's electronic chart", "Electronic health file". A slow change from functional interoperability (OSI level 6) to semantic interoperability (level 7) is being aimed at the moment. This current article will try to present the main electronic files models, from a functional interoperability system's possibility to be created perspective. \ud \u

Representación del conocimiento en historia clínica electrónica interoperable: el caso de la Historia Clínica Digital del Sistema Nacional de Salud de España

The Electronic Health Records of the National Health System (HCDSNS) of Spain is one of the fundamental pillars for achieving the effective interoperability of digital medical records within the National Health System. This article analyses the process of standardization and the semantic standards of reference that are allowing this ten-year old system to represent knowledge in electronic medical records. Firstly, the theoretical and legal basis that support the system development is exposed. Below are identified and analysed the reference standards proposed to achieve semantic interoperability, and finally the most significant resources that have been developed for this purpose are reviewed

Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI)

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 stakeholder

The European Institute for Innovation through Health Data

The European Institute for Innovation through Health Data (i~HD, www.i-hd.eu) has been formed as one of the key sustainable entities arising from the Electronic Health Records for Clinical Research (IMI-JU-115189) and SemanticHealthNet (FP7-288408) projects, in collaboration with several other European projects and initiatives supported by the European Commission. i~HD is a European not-for-profit body, registered in Belgium through Royal Assent. i~HD has been established to tackle areas of challenge in the successful scaling up of innovations that critically rely on high-quality and interoperable health data. It will specifically address obstacles and opportunities to using health data by collating, developing, and promoting best practices in information governance and in semantic interoperability. It will help to sustain and propagate the results of health information and communication technology (ICT) research that enables better use of health data, assessing and optimizing their novel value wherever possible. i~HD has been formed after wide consultation and engagement of many stakeholders to develop methods, solutions, and services that can help to maximize the value obtained by all stakeholders from health data. It will support innovations in health maintenance, health care delivery, and knowledge discovery while ensuring compliance with all legal prerequisites, especially regarding the insurance of patient's privacy protection. It is bringing multiple stakeholder groups together so as to ensure that future solutions serve their collective needs and can be readily adopted affordably and at scale

Addressing Semantic Interoperability, Privacy and Security Concerns in Electronic Health Records

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, CBO

Semantic processing of EHR data for clinical research

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.Comment: Accepted for publication in Journal of Biomedical Informatics, 2015, preprint versio

ARGOS policy brief on semantic interoperability

Semantic interoperability requires the use of standards, not only for Electronic Health Record (EHR) data to be transferred and structurally mapped into a receiving repository, but also for the clinical content of the EHR to be interpreted in conformity with the original meanings intended by its authors. Accurate and complete clinical documentation, faithful to the patient’s situation, and interoperability between systems, require widespread and dependable access to published and maintained collections of coherent and quality-assured semantic resources, including models such as archetypes and templates that would (1) provide clinical context, (2) be mapped to interoperability standards for EHR data, (3) be linked to well specified, multi-lingual terminology value sets, and (4) be derived from high quality ontologies. Wide-scale engagement with professional bodies, globally, is needed to develop these clinical information standards