An ontology-based approach for data integration in regionally interoperable healthcare systems

In order to best utilize the limited resource of medical resources, and to reduce the cost and improve the quality of medical treatment, we propose to build an interoperable regional healthcare systems among several levels of medical treatment organizations. In this paper, our approaches are as follows:(1) the ontology based approach is introduced as the methodology and technological solution for information integration; (2) the integration framework of data sharing among different organizations are proposed(3)the virtual database to realize data integration of hospital information system is established. Our methods realize the effective management and integration of the medical workflow and the mass information in the interoperable regional healthcare system. Furthermore, this research provides the interoperable regional healthcare system with characteristic of modularization, expansibility and the stability of the system is enhanced by hierarchy structure

Semantic technologies: from niche to the mainstream of Web 3? A comprehensive framework for web Information modelling and semantic annotation

Context: Web information technologies developed and applied in the last decade have considerably changed the way web applications operate and have revolutionised information management and knowledge discovery. Social technologies, user-generated classification schemes and formal semantics have a far-reaching sphere of influence. They promote collective intelligence, support interoperability, enhance sustainability and instigate innovation. Contribution: The research carried out and consequent publications follow the various paradigms of semantic technologies, assess each approach, evaluate its efficiency, identify the challenges involved and propose a comprehensive framework for web information modelling and semantic annotation, which is the thesis’ original contribution to knowledge. The proposed framework assists web information modelling, facilitates semantic annotation and information retrieval, enables system interoperability and enhances information quality. Implications: Semantic technologies coupled with social media and end-user involvement can instigate innovative influence with wide organisational implications that can benefit a considerable range of industries. The scalable and sustainable business models of social computing and the collective intelligence of organisational social media can be resourcefully paired with internal research and knowledge from interoperable information repositories, back-end databases and legacy systems. Semantified information assets can free human resources so that they can be used to better serve business development, support innovation and increase productivity

A Two-Level Information Modelling Translation Methodology and Framework to Achieve Semantic Interoperability in Constrained GeoObservational Sensor Systems

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation. Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data models underpinning these information systems are typically too rigid in their data representation to allow for the ever-changing and evolving nature of geo-spatial domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in an interoperable and computable way. The health domain experiences similar challenges with representing complex and evolving domain information concepts. Within any complex domain (such as Earth system science or health) two categories or levels of domain concepts exist. Those concepts that remain stable over a long period of time, and those concepts that are prone to change, as the domain knowledge evolves, and new discoveries are made. Health informaticians have developed a sophisticated two-level modelling systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how data, information, and knowledge interoperability among heterogenous systems can be achieved. This research investigates whether two-level modelling can be translated from the health domain to the geo-spatial domain and applied to observing scenarios to achieve semantic interoperability within and between spatial data infrastructures, beyond what is possible with current state-of-the-art approaches. A detailed review of state-of-the-art SDIs, geo-spatial standards and the two-level modelling methodology was performed. A cross-domain translation methodology was developed, and a proof-of-concept geo-spatial two-level modelling framework was defined and implemented. The Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard was re-profiled to aid investigation of the two-level information modelling approach. An evaluation of the method was undertaken using II specific use-case scenarios. Information modelling was performed using the two-level modelling method to show how existing historical ocean observing datasets can be expressed semantically and harmonized using two-level modelling. Also, the flexibility of the approach was investigated by applying the method to an air quality monitoring scenario using a technologically constrained monitoring sensor system. This work has demonstrated that two-level modelling can be translated to the geospatial domain and then further developed to be used within a constrained technological sensor system; using traditional wireless sensor networks, semantic web technologies and Internet of Things based technologies. Domain specific evaluation results show that twolevel modelling presents a viable approach to achieve semantic interoperability between constrained geo-observational sensor systems and spatial data infrastructures for ocean observing and city based air quality observing scenarios. This has been demonstrated through the re-purposing of selected, existing geospatial data models and standards. However, it was found that re-using existing standards requires careful ontological analysis per domain concept and so caution is recommended in assuming the wider applicability of the approach. While the benefits of adopting a two-level information modelling approach to geospatial information modelling are potentially great, it was found that translation to a new domain is complex. The complexity of the approach was found to be a barrier to adoption, especially in commercial based projects where standards implementation is low on implementation road maps and the perceived benefits of standards adherence are low. Arising from this work, a novel set of base software components, methods and fundamental geo-archetypes have been developed. However, during this work it was not possible to form the required rich community of supporters to fully validate geoarchetypes. Therefore, the findings of this work are not exhaustive, and the archetype models produced are only indicative. The findings of this work can be used as the basis to encourage further investigation and uptake of two-level modelling within the Earth system science and geo-spatial domain. Ultimately, the outcomes of this work are to recommend further development and evaluation of the approach, building on the positive results thus far, and the base software artefacts developed to support the approach

Transparent ICD and DRG Coding Using Information Technology: Linking and Associating Information Sources with the eXtensible Markup Language

With the introduction of ICD-10 as the standard for diagnostics, it becomes necessary to develop an electronic representation of its complete content, inherent semantics, and coding rules. The authors' design relates to the current efforts by the CEN/TC 251 to establish a European standard for hierarchical classification systems in health care. The authors have developed an electronic representation of ICD-10 with the eXtensible Markup Language (XML) that facilitates integration into current information systems and coding software, taking different languages and versions into account. In this context, XML provides a complete processing framework of related technologies and standard tools that helps develop interoperable applications. XML provides semantic markup. It allows domain-specific definition of tags and hierarchical document structure. The idea of linking and thus combining information from different sources is a valuable feature of XML. In addition, XML topic maps are used to describe relationships between different sources, or "semantically associated” parts of these sources. The issue of achieving a standardized medical vocabulary becomes more and more important with the stepwise implementation of diagnostically related groups, for example. The aim of the authors' work is to provide a transparent and open infrastructure that can be used to support clinical coding and to develop further software applications. The authors are assuming that a comprehensive representation of the content, structure, inherent semantics, and layout of medical classification systems can be achieved through a document-oriented approac

An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems

The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus.We thank Fagor Electrodomesticos S.Coop for their support and funding in the development of this work, specially to Juan Ramon Inurria and Jorge de Antonio Prieto. We also thank the colaboration from Universidad de Mondragon in the design of the general architecture of the telemedicine system, specially, Felix Larrinaga. This work has been partially supported by the Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001.Sáez Silvestre, C.; Bresó Guardado, A.; Vicente Robledo, J.; Robles Viejo, M.; García Gómez, JM. (2013). An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems. Computer Methods and Programs in Biomedicine. 109(3):239-249. doi:10.1016/j.cmpb.2012.10.003S239249109