Toward semantic interoperability of electronic health records

Proceedings of the …, 2010

The use of Electronic Health Records (EHRs) has brought multiple benefits to the healthcare domain. However, those advantages would be greater if seamless interoperability of EHRs between heterogeneous Health Information Systems were achieved. Our proposal allows one system to interpret on the fly data about medical observations–present in EHRs–from another one even when they use different data representations. We propose a framework where the central element is an ontology that ...

2020

A CORE REFERENCE HIERARCHICAL PRIMITIVE ONTOLOGY FOR ELECTRONIC MEDICAL RECORDS SEMANTICS INTEROPERABILITY Ziniya Zahedi Old Dominion University, 2020 Director: Dr. T. Steven Cotter Currently, electronic medical records (EMR) cannot be exchanged among hospitals, clinics, laboratories, pharmacies, and insurance providers or made available to patients outside of local networks. Hospital, laboratory, pharmacy, and insurance provider legacy databases can share medical data within a respective network and limited data with patients. The lack of interoperability has its roots in the historical development of electronic medical records. Two issues contribute to interoperability failure. The first is that legacy medical record databases and expert systems were designed with semantics that support only internal information exchange. The second is ontological commitment to the semantics of a particular knowledge representation language formalism. This research seeks to address these interoper...

International Journal of Medical Informatics, 1998

We apply the principles included in two CEN standards (ENV 12265, ENV 12264) to the analysis of the semantic structure of health record systems, to support their semantic interoperability. This result was made possible by dramatic methodological progress in the field of terminological systems-due to a worldwide evolution towards a new generation-and by the experience we acquired in the GALEN-IN-USE (formerly GALEN) project. The meaning behind names, content and context of record items and record item complexes can be considered as a 'semantic continuum'. This continuum is made explicit, by building a suitable paraphrase in a controlled language. We can then apply the principles we previously elaborated for the second generation of terminological system. Methodology and tools for generating a controlled language and a second-generation terminological system were developed and successfully used in the GALEN-IN-USE project and promising experiments were performed on elements of record structure listed in LOINC and SDM. In this way, the semantic structures of different record systems can be expressed by the resulting common formalism and thus, information units can be faithfully exchanged among different structures.

The amount of medical information has generated challenges for interoperability between health information systems (HIS). In the enterprise engineering context, is desirable the enterprise integration through interoperability of its systems. The semantic interoperability SI in HIS is the ability of such systems for exchanging data between themselves despite the different terminologies adopted. In seeking for ways to cope with issues of SI, one can find much research initiatives on subjects like vocabularies, thesauri, terminology, information models and ontologies. This paper describes the research carried out within a thesis in the construction phase, which general objective is to determine a top-level ontology based solution to provide semantic interoperability in HISs. This thesis is classified as a qualitative applied research. We hope to formulate a top-level ontology based solution to provide the semantic interoperability between the ontologies and terminologies which the healthcare information systems use.

Lecture Notes in Computer Science, 2012

The adoption of Electronic Healthcare Records (EHRs) holds the key for the success of next generation intelligent healthcare systems to improve the quality of healthcare and patient safety by facilitating the exchange of critical patient's episodic information among different stakeholders. The primary and secondary care healthcare systems store the episodic information for future reuse and for auditing purposes. The conventional healthcare information management systems for primary and secondary care are expected to be able to communicate and exchange complex medical knowledge (often expressed in numerous languages in different parts of the world) in an efficient and unequivocal way. For the purpose of this research, we present a novel technique to transform conventional patients' data into OWL-based Electronic Healthcare Records (EHRs) which addresses the issues of interoperability, flexibility, and scalability through the utilization of ontology inspired framework. Using ontologies is a cost effective and pragmatic solution to implementing a shift from simple patient interviewing systems to more intelligent systems in the primary and secondary care. The Patient Semantic Profile specifically developed for generating EHRs has been validated using a sample of real patients' data acquired from the Raigmore Hospital's RACPC (Rapid Access Chest Pain Clinic).

Studies in health technology and informatics, 2016

The main purpose of this paper is to design a data model for Electronic Health Records which main goal is to enable cooperation of various heterogeneous health information systems. We investigate the interest of the meta-ontologies proposed in [1] by instantiating it with real data. We tested the feasibility of our model on real anonymous medical data provided by the Médibase Systèmes company.

International Journal of Computer Applications, 2012

The healthcare domain is a complex domain which lacks a unified terminological set, most especially in clinical cases. As a result of this, the messaging standards employed in the healthcare domain use different terms for the same concept which often results in clinical misinterpretation, knowledge mismanagement, misdiagnosis of the patient's illness or even death. Consequently, the healthcare system is characterized by high error rate and semantic heterogeneity. A lot of efforts have been made to resolve this problem through the use of standards, clinical terminologies, web services as well as the use of achetype. However, these solutions have proved unsuccessful in resolving semantic heterogeneity in healthcare. Ontologies have also been developed to resolve this problem by making explicit the meaning of terms used in healthcare. Ontologies provide a source of shared and precisely defined terms, resulting in interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that the healthcare domain is conceptualized results in the creation of different ontologies with contradicting or overlapping parts. Thus, the available ontologies also introduce semantic heterogeneity to this domain. An effective solution to this problem is the introduction of methods for finding matches among the various components of ontologies in healthcare in order to facilitate semantic interoperability. Therefore, this paper aims at examining the various attempts for achieving semantic interoperability in healthcare and also motivates the critical needs for ontology matching in healthcare systems.

2009

The interoperability problem in eHealth can only be addressed by means of combining standards and technology. However, these alone do not suffice. An appropriate framework that articulates such combination is required. In this paper, we adopt a three-dimensional (information, concept, and inference) approach for such framework, based on OWL as formal language for terminological and ontological health resources, SNOMED CT as lexical backbone for all such resources, and the standard CEN 13606 for representing EHRs. Based on such framework, we propose a novel form for creating and supporting networks of clinical terminologies. Additionally, we propose a number of software modules to semantically process and exploit EHRs, including NLP-based search and inference, which can support medical applications in heterogeneous and distributed eHealth systems. 1 ec.europa.eu/information_society/activities/health/policy sector. One of the most challenging issues identified addresses the interoperability problem between different e-health systems. Such problem is partially due to the exponential increase of the number of medical terminologies (SNOMED CT 2 , MedDra 3 , etc.), ontologies (GALEN 4 , FMA 5 , etc), and classifications of diseases and related medical events and concepts (ICD 6 , CPT 7 , etc.) that eventually need 2

2012

Resolving heterogeneities between data and processes paves the way for interoperability between different heterogeneous systems. Healthcare standards provide the base for interoperability between different Electronic Health Record (EHR) system. The problems related to data interoperability arise when two EHR system's are complaint to heterogeneous healthcare standards and want to communicate with each other. To achieve semantic data interoperability, there is need to resolve data level heterogeneity. In this paper, we propose system that enable high level of accuracy of mapping between heterogeneous healthcare standards model. The broader goal of data interoperability is achieved when these heterogeneities are resolved through ontology matching and generation of accurate mapping file, that helps in clinical message conversion from one standard to another. To justify claim we investigate HL7 and openEHR standards ontological mappings. We will discuss transformation of HL7 and openEHR models at high level and instance transformation at the realization level. The proposed approach provides accurate mappings that enables timely health information sharing among different healthcare systems to provide better healthcare to patients.

2005

1 Abstract In the last two decades we have witnessed considerable efforts directed towards making electronic healthcare records comparable and interoperable through advances in record architectures and (bio) medical terminologies and coding systems. Deep semantic issues in general, and ontology in particular, have received some interest from the research communities. However, with the exception of work on so-called 'controlled vocabularies', ontology has thus far played little role in work on standardization.