Interoperable EHR Systems – Challenges, Standards and Solutions

Background: Electronic Health Record Systems (EHRS) and Personal Health Record Systems (PHRS) are core components of infrastructure needed to run any health system. Objectives: As health systems undergo paradigm changes, EHRS and PHRS have to advance as well to meet the related interoperability challenges. Methods: The paper discusses EHR types, implementations and standards, starting with different requirements specifications, systems and systems architectures, standards and solutions. Results: Existing standards and specifications are compared with changing requirements, presenting weaknesses and defining the advancement of EHRS, architectures and related services, embedded in advanced infrastructure systems. Conclusion: Future EHR systems are components in a layered architecture with open interfaces. The need of verifying data models at business domains level is specifically highlighted. Such approach is enabled by the ISO Interoperability Reference Architecture of a systemoriented, architecture-centric, ontology-based, policy- driven approach, meeting good modeling best practices

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

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

DETAILED CLINICAL MODELS AND THEIR RELATION WITH ELECTRONIC HEALTH RECORDS

Tesis por compendio[EN] Healthcare domain produces and consumes big quantities of people's health data. Although data exchange is the norm rather than the exception, being able to access to all patient data is still far from achieved. Current developments such as personal health records will introduce even more data and complexity to the Electronic Health Records (EHR). Achieving semantic interoperability is one of the biggest challenges to overcome in order to benefit from all the information contained in the distributed EHR. This requires that the semantics of the information can be understood by all involved parties. It has been stablished that three layers are needed to achieve semantic interoperability: Reference models, clinical models (archetypes), and clinical terminologies. As seen in the literature, information models (reference models and clinical models) are lacking methodologies and tools to improve EHR systems and to develop new systems that can be semantically interoperable. The purpose of this thesis is to provide methodologies and tools for advancing the use of archetypes in three different scenarios: - Archetype definition over specifications with no dual model architecture native support. Any EHR architecture that directly or indirectly has the notion of detailed clinical models (such as HL7 CDA templates) can be potentially used as a reference model for archetype definition. This allows transforming single-model architectures (which contain only a reference model) into dual-model architectures (reference model with archetypes). A set of methodologies and tools has been developed to support the definition of archetypes from multiple reference models. - Data transformation. A complete methodology and tools are proposed to deal with the transformation of legacy data into XML documents compliant with the archetype and the underlying reference model. If the reference model is a standard then the transformation is a standardization process. The methodologies and tools allow both the transformation of legacy data and the transformation of data between different EHR standards. - Automatic generation of implementation guides and reference materials from archetypes. A methodology for the automatic generation of a set of reference materials is provided. These materials are useful for the development and use of EHR systems. These reference materials include data validators, example instances, implementation guides, human-readable formal rules, sample forms, mindmaps, etc. These reference materials can be combined and organized in different ways to adapt to different types of users (clinical or information technology staff). This way, users can include the detailed clinical model in their organization workflow and cooperate in the model definition. These methodologies and tools put clinical models as a key part of the system. The set of presented methodologies and tools ease the achievement of semantic interoperability by providing means for the semantic description, normalization, and validation of existing and new systems.[ES] El sector sanitario produce y consume una gran cantidad de datos sobre la salud de las personas. La necesidad de intercambiar esta información es una norma más que una excepción, aunque este objetivo está lejos de ser alcanzado. Actualmente estamos viviendo avances como la medicina personalizada que incrementarán aún más el tamaño y complejidad de la Historia Clínica Electrónica (HCE). La consecución de altos grados de interoperabilidad semántica es uno de los principales retos para aprovechar al máximo toda la información contenida en las HCEs. Esto a su vez requiere una representación fiel de la información de tal forma que asegure la consistencia de su significado entre todos los agentes involucrados. Actualmente está reconocido que para la representación del significado clínico necesitamos tres tipos de artefactos: modelos de referencia, modelos clínicos (arquetipos) y terminologías. En el caso concreto de los modelos de información (modelos de referencia y modelos clínicos) se observa en la literatura una falta de metodologías y herramientas que faciliten su uso tanto para la mejora de sistemas de HCE ya existentes como en el desarrollo de nuevos sistemas con altos niveles de interoperabilidad semántica. Esta tesis tiene como propósito proporcionar metodologías y herramientas para el uso avanzado de arquetipos en tres escenarios diferentes: - Definición de arquetipos sobre especificaciones sin soporte nativo al modelo dual. Cualquier arquitectura de HCE que posea directa o indirectamente la noción de modelos clínicos detallados (por ejemplo, las plantillas en HL7 CDA) puede ser potencialmente usada como modelo de referencia para la definición de arquetipos. Con esto se consigue transformar arquitecturas de HCE de modelo único (solo con modelo de referencia) en arquitecturas de doble modelo (modelo de referencia + arquetipos). Se han desarrollado metodologías y herramientas que faciliten a los editores de arquetipos el soporte a múltiples modelos de referencia. - Transformación de datos. Se propone una metodología y herramientas para la transformación de datos ya existentes a documentos XML conformes con los arquetipos y el modelo de referencia subyacente. Si el modelo de referencia es un estándar entonces la transformación será un proceso de estandarización de datos. La metodología y herramientas permiten tanto la transformación de datos no estandarizados como la transformación de datos entre diferentes estándares. - Generación automática de guías de implementación y artefactos procesables a partir de arquetipos. Se aporta una metodología para la generación automática de un conjunto de materiales de referencia de utilidad en el desarrollo y uso de sistemas de HCE, concretamente validadores de datos, instancias de ejemplo, guías de implementación , reglas formales legibles por humanos, formularios de ejemplo, mindmaps, etc. Estos materiales pueden ser combinados y organizados de diferentes modos para facilitar que los diferentes tipos de usuarios (clínicos, técnicos) puedan incluir los modelos clínicos detallados en el flujo de trabajo de su sistema y colaborar en su definición. Estas metodologías y herramientas ponen los modelos clínicos como una parte clave en el sistema. El conjunto de las metodologías y herramientas presentadas facilitan la consecución de la interoperabilidad semántica al proveer medios para la descripción semántica, normalización y validación tanto de sistemas nuevos como ya existentes.[CA] El sector sanitari produeix i consumeix una gran quantitat de dades sobre la salut de les persones. La necessitat d'intercanviar aquesta informació és una norma més que una excepció, encara que aquest objectiu està lluny de ser aconseguit. Actualment estem vivint avanços com la medicina personalitzada que incrementaran encara més la grandària i complexitat de la Història Clínica Electrònica (HCE). La consecució d'alts graus d'interoperabilitat semàntica és un dels principals reptes per a aprofitar al màxim tota la informació continguda en les HCEs. Açò, per la seua banda, requereix una representació fidel de la informació de tal forma que assegure la consistència del seu significat entre tots els agents involucrats. Actualment està reconegut que per a la representació del significat clínic necessitem tres tipus d'artefactes: models de referència, models clínics (arquetips) i terminologies. En el cas concret dels models d'informació (models de referència i models clínics) s'observa en la literatura una mancança de metodologies i eines que en faciliten l'ús tant per a la millora de sistemes de HCE ja existents com per al desenvolupament de nous sistemes amb alts nivells d'interoperabilitat semàntica. Aquesta tesi té com a propòsit proporcionar metodologies i eines per a l'ús avançat d'arquetips en tres escenaris diferents: - Definició d'arquetips sobre especificacions sense suport natiu al model dual. Qualsevol arquitectura de HCE que posseïsca directa o indirectament la noció de models clínics detallats (per exemple, les plantilles en HL7 CDA) pot ser potencialment usada com a model de referència per a la definició d'arquetips. Amb açò s'aconsegueix transformar arquitectures de HCE de model únic (solament amb model de referència) en arquitectures de doble model (model de referència + arquetips). S'han desenvolupat metodologies i eines que faciliten als editors d'arquetips el suport a múltiples models de referència. - Transformació de dades. Es proposa una metodologia i eines per a la transformació de dades ja existents a documents XML conformes amb els arquetips i el model de referència subjacent. Si el model de referència és un estàndard llavors la transformació serà un procés d'estandardització de dades. La metodologia i eines permeten tant la transformació de dades no estandarditzades com la transformació de dades entre diferents estàndards. - Generació automàtica de guies d'implementació i artefactes processables a partir d'arquetips. S'hi inclou una metodologia per a la generació automàtica d'un conjunt de materials de referència d'utilitat en el desenvolupament i ús de sistemes de HCE, concretament validadors de dades, instàncies d'exemple, guies d'implementació, regles formals llegibles per humans, formularis d'exemple, mapes mentals, etc. Aquests materials poden ser combinats i organitzats de diferents maneres per a facilitar que els diferents tipus d'usuaris (clínics, tècnics) puguen incloure els models clínics detallats en el flux de treball del seu sistema i col·laborar en la seua definició. Aquestes metodologies i eines posen els models clínics com una part clau del sistemes. El conjunt de les metodologies i eines presentades faciliten la consecució de la interoperabilitat semàntica en proveir mitjans per a la seua descripció semàntica, normalització i validació tant de sistemes nous com ja existents.Boscá Tomás, D. (2016). DETAILED CLINICAL MODELS AND THEIR RELATION WITH ELECTRONIC HEALTH RECORDS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/62174TESISCompendi

The adoption of ICT in Malaysian public hospitals: the interoperability of electronic health records and health information systems

There have been a number of researches that investigated ICT adoption in Malaysian healthcare. With the small number of hospitals that adopt ICT in their daily clinical and administrative operations, the possibility to enable data exchange across 131 public hospitals in Malaysia is still a long journey. In addition to those studies, this research was framed under six objectives, which aim to critically review existing literature on the subject matter, identify barriers of ICT adoption in Malaysia, understand the administrative context during the pre and post-ICT adoption, and recommend possible solutions to the Ministry of Health of Malaysia (MoHM) in its efforts to implement interoperable electronic health records (EHR) and health information systems (HTIS). Specifically, this research aimed to identify the factors that had significant impacts to the processes of implementing interoperable EHR and HTIS by the MoHM. Furthermore, it also aimed to propose relevant actors who should involve in the implementation phases. These factors and actors were used to develop a model for implementing interoperable EHR and HTIS in Malaysia. To gather the needed data, series of interviews were conducted with three groups of participants. They were ICT administrators of MoHM, ICT and medical record administrators of three hospitals, and physicians of three hospitals. To ensure the interview feedback was representing the context of EHR and HTIS implementation in Malaysia, two hospital categories were selected, which included the hospitals with HTIS and non-HTIS hospitals. The government documents were then used to triangulate the feedback to ensure dependability, credibility, transferability and conformity of the findings. Two techniques were used to analyse the data, which were thematic analysis and theme matching. These two techniques were modified from its original method, known as pattern matching. The originality of this research was presented in the findings and methods to transform them into solutions and provide recommendation to the MoHM. In general, the results showed that the technological factors contributed less to the success of the implementation of interoperable EHR and HTIS compared to the managerial and administrative factors. Four main practical and social contributions were identified from this research, which included synchronisation of managerial elements, political determination and change management transformation, optimisation of use of existing legacy system (Patient Management System) and finally the roles of actors. Nevertheless, the findings of this research would be more dependable and transferable if more participants had been willing to participate especially among the physicians and those who managed the ICT adoptions under the MoHM

Data quality issues in electronic health records for large-scale databases

Data Quality (DQ) in Electronic Health Records (EHRs) is one of the core functions that play a decisive role to improve the healthcare service quality. The DQ issues in EHRs are a noticeable trend to improve the introduction of an adaptive framework for interoperability and standards in Large-Scale Databases (LSDB) management systems. Therefore, large data communications are challenging in the traditional approaches to satisfy the needs of the consumers, as data is often not capture directly into the Database Management Systems (DBMS) in a seasonably enough fashion to enable their subsequent uses. In addition, large data plays a vital role in containing plenty of treasures for all the fields in the DBMS. EHRs technology provides portfolio management systems that allow HealthCare Organisations (HCOs) to deliver a higher quality of care to their patients than that which is possible with paper-based records. EHRs are in high demand for HCOs to run their daily services as increasing numbers of huge datasets occur every day. Efficient EHR systems reduce the data redundancy as well as the system application failure and increase the possibility to draw all necessary reports. However, one of the main challenges in developing efficient EHR systems is the inherent difficulty to coherently manage data from diverse heterogeneous sources. It is practically challenging to integrate diverse data into a global schema, which satisfies the need of users. The efficient management of EHR systems using an existing DBMS present challenges because of incompatibility and sometimes inconsistency of data structures. As a result, no common methodological approach is currently in existence to effectively solve every data integration problem. The challenges of the DQ issue raised the need to find an efficient way to integrate large EHRs from diverse heterogeneous sources. To handle and align a large dataset efficiently, the hybrid algorithm method with the logical combination of Fuzzy-Ontology along with a large-scale EHRs analysis platform has shown the results in term of improved accuracy. This study investigated and addressed the raised DQ issues to interventions to overcome these barriers and challenges, including the provision of EHRs as they pertain to DQ and has combined features to search, extract, filter, clean and integrate data to ensure that users can coherently create new consistent data sets. The study researched the design of a hybrid method based on Fuzzy-Ontology with performed mathematical simulations based on the Markov Chain Probability Model. The similarity measurement based on dynamic Hungarian algorithm was followed by the Design Science Research (DSR) methodology, which will increase the quality of service over HCOs in adaptive frameworks

Uma rede telemática para a prestação regional de cuidados de saúde

Doutoramento em Engenharia InformáticaAs tecnologias de informação e comunicação na área da saúde não são só um instrumento para a boa gestão de informação, mas antes um fator estratégico para uma prestação de cuidados mais eficiente e segura. As tecnologias de informação são um pilar para que os sistemas de saúde evoluam em direção a um modelo centrado no cidadão, no qual um conjunto abrangente de informação do doente deve estar automaticamente disponível para as equipas que lhe prestam cuidados, independentemente de onde foi gerada (local geográfico ou sistema). Este tipo de utilização segura e agregada da informação clínica é posta em causa pela fragmentação generalizada das implementações de sistemas de informação em saúde. Várias aproximações têm sido propostas para colmatar as limitações decorrentes das chamadas “ilhas de informação” na saúde, desde a centralização total (um sistema único), à utilização de redes descentralizadas de troca de mensagens clínicas. Neste trabalho, propomos a utilização de uma camada de unificação baseada em serviços, através da federação de fontes de informação heterogéneas. Este agregador de informação clínica fornece a base necessária para desenvolver aplicações com uma lógica regional, que demostrámos com a implementação de um sistema de registo de saúde eletrónico virtual. Ao contrário dos métodos baseados em mensagens clínicas ponto-a-ponto, populares na integração de sistemas em saúde, desenvolvemos um middleware segundo os padrões de arquitetura J2EE, no qual a informação federada é expressa como um modelo de objetos, acessível através de interfaces de programação. A arquitetura proposta foi instanciada na Rede Telemática de Saúde, uma plataforma instalada na região de Aveiro que liga oito instituições parceiras (dois hospitais e seis centros de saúde), cobrindo ~350.000 cidadãos, utilizada por ~350 profissionais registados e que permite acesso a mais de 19.000.000 de episódios. Para além da plataforma colaborativa regional para a saúde (RTSys), introduzimos uma segunda linha de investigação, procurando fazer a ponte entre as redes para a prestação de cuidados e as redes para a computação científica. Neste segundo cenário, propomos a utilização dos modelos de computação Grid para viabilizar a utilização e integração massiva de informação biomédica. A arquitetura proposta (não implementada) permite o acesso a infraestruturas de e-Ciência existentes para criar repositórios de informação clínica para aplicações em saúde.Modern health information technology is not just a supporting instrument to good information management but a strategic requirement to provide more efficient and safer health care. Health information technology is a cornerstone to build the future patient-centric health care systems in which a comprehensive set of patient data will be available to the relevant care teams, in spite of where (system or service point) it was generated. Such secure and efficient use of clinical data is challenged by the existing fragmentation of health information systems implementation. Several approaches have been proposed to address the limitations of the so called “information silos” in healthcare, ranging from full centralization (a single system) to full-decentralized clinical message exchange networks. In this work we advocate the use of a service-based unification layer, by federating distributed heterogeneous information sources. This clinical information hub provides the basis to build regional-level applications, which we have demonstrated by implementing a virtual Electronic Health Record system. Unlike the message-driven, point-to-point approaches popular in health care systems integration, we developed a middleware layer, using J2EE architectural patterns, in which the common information is represented as an object model, accessible through programming interfaces. The proposed architecture was instantiated in the Rede Telemática da Saúde network, a platform deployed in the region of Aveiro connecting eight partner institutions (two hospitals and six primary care units), covering ~ 350,000 citizens, indexing information on more than 19,000,000 episodes of care and used by ~350 registered professionals. In addition to the regional health information collaborative platform (RTSys), we introduce a second line of research towards bridging the care networks and the science networks. In the later scenario, we propose the use of Grid computing to enable the massive use and integration of biomedical information. The proposed architecture (not implemented) enables to access existing e-Science infrastructures to create clinical information repositories for health applications

Quality framework for semantic interoperability in health informatics: definition and implementation

Aligned with the increased adoption of Electronic Health Record (EHR) systems, it is recognized that semantic interoperability provides benefits for promoting patient safety and continuity of care. This thesis proposes a framework of quality metrics and recommendations for developing semantic interoperability resources specially focused on clinical information models, which are defined as formal specifications of structure and semantics for representing EHR information for a specific domain or use case. This research started with an exploratory stage that performed a systematic literature review with an international survey about the clinical information modelling best practice and barriers. The results obtained were used to define a set of quality models that were validated through Delphi study methodologies and end user survey, and also compared with related quality standards in those areas that standardization bodies had a related work programme. According to the obtained research results, the defined framework is based in the following models: Development process quality model: evaluates the alignment with the best practice in clinical information modelling and defines metrics for evaluating the tools applied as part of this process. Product quality model: evaluates the semantic interoperability capabilities of clinical information models based on the defined meta-data, data elements and terminology bindings. Quality in use model: evaluates the suitability of adopting semantic interoperability resources by end users in their local projects and organisations. Finally, the quality in use model was implemented within the European Interoperability Asset register developed by the EXPAND project with the aim of applying this quality model in a broader scope to contain any relevant material for guiding the definition, development and implementation of interoperable eHealth systems in our continent. Several European projects already expressed interest in using the register, which will now be sustained by the European Institute for Innovation through Health Data