A Methodology for Defining Working Healthcare Ontologies

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.

Computers in Biology and Medicine, 2006

Ontology is no longer a mere research topic, but its relevance has been recognized in several practical fields. Current applications areas include natural language translation, e-commerce, geographic information systems, legal information systems and biology and medicine. It is the backbone of solid and effective applications in health care and can help to build more powerful and more interoperable medical information systems. The design and implementation of ontologies in medicine is mainly focused on the re-organization of medical terminologies. This is obviously a difficult task and requires a deep analysis of the structure and the concepts of such terminologies, in order to define domain ontologies able to provide both flexibility and consistency to medical information systems. The aim of this special issue of Computers in Biology and Medicine is to report the current evolution of research in biomedical ontologies, presenting both papers devoted to methodological issues and works with a more applicative emphasys.

Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences., 2009

There are several medical statistics databases in Latvia covering the main pathologies endangering the quality of life by spread of risk factors to residents of Latvia. Our task has been to merge these legacy relational databases into a single unified Medical Data Warehouse accessible for medical researchers. Additionally, medical researchers require easyto-understand ontologies describing the structure of available data and a flexible query mechanism for data retrieval.

Studies in health technology and informatics, 2012

This paper describes an approach to build a Data Definition Ontology (DDO) in the context of full domain ontology integration with datasets in order to share and query clinical heterogeneous data repositories. We have adapted an existing semantic web tool (D2RQ) to implement a process that automatically generates the DDO from a database information model, thanks to reverse engineering and schema mapping approaches. This study has been performed in the context of the DebugIT European project (Detecting and Eliminating Bacteria UsinG Information Technology) that aims to control and monitor the bacterial growth via a semantic interoperability platform (IP). The evaluation of the process is based, first, on the accuracy of the produced DDO for different samples of database storage and second, by checking the congruency between the DDO and the D2RQ database mapping file.

Studies in health technology and informatics, 2007

In this paper we describe a model of clinical information designed to make health information systems properly interoperable and safely computable. The model is a response to a number of categories of requirements, ranging from the semantic to the performance of software at runtime. We argue that the starting point of a successful model must be an ontological analysis of the process of clinical care delivery, seen as a scientific problem-solving process. From this approach we develop a classification of types of clinical information called the Clinical Investigator Record (CIR) ontology.

Reciis, 2009

2014 IEEE International Conference on Bioinformatics and Bioengineering, 2014

Semantic interoperability is essential to facilitate efficient collaboration in heterogeneous multi-site healthcare environments. The deployment of a semantic interoperability solution has the potential to enable a wide range of informaticssupported applications in clinical care and research both within a single healthcare organization and in a network of organizations. At the same time, building and deploying a semantic interoperability solution may require significant effort to carry out data transformation and to harmonize the semantics of the information in the different systems. Our approach to semantic interoperability leverages existing healthcare standards and ontologies, focusing first on specific clinical domains and key applications, and gradually expanding the solution when needed. An important objective of this work is to create a semantic link between clinical research and care environments to enable applications such as streamlining the execution of multi-centric clinical trials, including the identification of eligible patients for the trials. This paper presents an analysis of the suitability of several widely-used medical ontologies in the clinical domain: SNOMED-CT, LOINC, MedDRA, to capture the semantics of the clinical trial eligibility criteria, of the clinical trial data (e.g., Clinical Report Forms), and of the corresponding patient record data that would enable the automatic identification of eligible patients. Next to the coverage provided by the ontologies we evaluate and compare the sizes of the sets of relevant concepts and their relative frequency to estimate the cost of data transformation, of building the necessary semantic mappings, and of extending the solution to new domains. This analysis shows that our approach is both feasible and scalable. I.

2008

The meeting focused on uses of ontologies, with a special focus on spatial ontologies, in addressing the ever increasing needs faced by biology and medicine to cope with ever expanding quantities of data. To provide effective solutions computers need to integrate data deriving from myriad heterogeneous sources by bringing the data together within a single framework. The meeting brought together leaders in the field of what are called 'top-level ontologies' to address this issue, and to establish strategies among leaders in the field of biomedical ontology for the creation of interoperable biomedical ontologies which will serve the goal of useful data integration.

Procedia - Social and Behavioral Sciences, 2015

The ultimate goal to improve healthcare practices and the development of better biomedical products largely depends on the ability to share and link the wealth of collected medical data. The key challenge to pursue this ambitious objective is not only enabling the integration of the data spanning heterogeneous data sources and formats, but in the development of tools and standards for flexible search, data analytics and user friendly interfaces. In this paper we conduct an extensive survey on how Semantic Web is used to answer these challenges. First, we review ontology management and semantic data repositories for healthcare. Second, we conduct a survey on most representative applications and user-friendly viewers for semantic healthcare data. Third, we analyze the data mining and data analytics approaches used to find useful patterns and knowledge in these data. Finally, we discuss the positive effects of this synergy between Semantic Web and healthcare processes, and we identify some of the major remaining obstacles and research challenges in this area.

One of the challenges faced nowadays by the healthcare industry is semantic interoperability. It is the ability of a healthcare system to share information and have that information properly interpreted by the receiving system in the same sense as intended by the transmitting system. Semantic Web (aka Web 3.0) provides the enabling technologies to achieve semantic interoperability. Web Services, as a catalyst in this process, provide seamless communication of information between healthcare systems thus providing better access to patient information and improved healthcare. Semantic technologies are emerging and several applications ranging from business process management to information security have demonstrated encouraging prospects of its benefits. Role of semantics is also very vital for achieving interoperability in sharing of health records. The aim of this chapter is to establish research and development in the domain of Health Level 7 (HL7) as an application to provide e-health services for the diverse communities. Through this research process, we intend to develop HL7 interface software for healthcare information systems that will provide semantic interoperability between the communicating medical systems. The objective is to facilitate e-health services that are interoperable among a number of domains in this field such as laboratory, patient administration and pharmacy. After its development and testing in the end-user environment, this software solution will be made publicly available under an open-source license. Due to its cutting-edge nature, this software solution has the potential of establishing an international repute for Pakistan in the highly profitable and potent healthcare industry. Since healthcare is a sensitive and critical area as it involves life of human beings, this project will be conducted in a manner to ensure that the resulting software is secure, reliable and maintainable. This mostly involves research and implementation challenges. Some initiatives are already underway such as Health Services Specification Project (HSSP). It is a joint-venture of HL7 and Object Management Group (OMG), providing standardized service interface specifications. Following the traces of HSSP, our proposal is aimed to design and implement concrete SOA model. The ultimate goal is to define the HL7 Web services as Semantic Web