Using the ResearchEHR platform to facilitate the practical application of the EHR standards

Possibly the most important requirement to support co-operative work among health professionals and institutions is the ability of sharing EHRs in a meaningful way, and it is widely acknowledged that standardization of data and concepts is a prerequisite to achieve semantic interoperability in any domain. Different international organizations are working on the definition of EHR architectures but the lack of tools that implement them hinders their broad adoption. In this paper we present ResearchEHR, a software platform whose objective is to facilitate the practical application of EHR standards as a way of reaching the desired semantic interoperability. This platform is not only suitable for developing new systems but also for increasing the standardization of existing ones. The work reported here describes how the platform allows for the edition, validation, and search of archetypes, converts legacy data into normalized, archetypes extracts, is able to generate applications from archetypes and finally, transforms archetypes and data extracts into other EHR standards. We also include in this paper how ResearchEHR has made possible the application of the CEN/ISO 13606 standard in a real environment and the lessons learnt with this experience. © 2011 Elsevier Inc..This work has been partially supported by the Spanish Ministry of Science and Innovation under Grants TIN2010-21388-C02-01 and TIN2010-21388-C02-02, and by the Health Institute Carlos in through the RETICS Combiomed, RD07/0067/2001. Our most sincere thanks to the Hospital of Fuenlabrada in Madrid, including its Medical Director Pablo Serrano together with Marta Terron and Luis Lechuga for their support and work during the development of the medications reconciliation project.Maldonado Segura, JA.; Martínez Costa, C.; Moner Cano, D.; Menárguez-Tortosa, M.; Boscá Tomás, D.; Miñarro Giménez, JA.; Fernández-Breis, JT.... (2012). Using the ResearchEHR platform to facilitate the practical application of the EHR standards. Journal of Biomedical Informatics. 45(4):746-762. doi:10.1016/j.jbi.2011.11.004S74676245

Electronic Health Record Architecture: A Systematic Review

Numerous advantages are derived from the electronic health record (EHR).Though achieving such advantages depends on its architecture, at present no unique understanding of the architecture dimensions and specifications is available. Therefore, the aim of the present study is a systematic review of architecture perception of the electronic health record. The authors searched the literature in Science Direct, Scopus, PubMed and Proudest Databases (2000 to Jun 2015).  Data extraction was done by 2 reviewers on content, structure, content/structure relationship, confidentiality and security of the EHR. Subsequent to refining the 87 retrieved studies, 25 studies were finally included in the study. In the studies and paradigms so far proposed for the EHR, a unique comprehensive architecture model from the viewpoint of research criteria has not been investigated and it has been considered only from some dimensions. Hence, we provide a new definition of the EHR architecture

Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts

Introduction The secondary use of Electronic Healthcare Records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, Virtual Health Records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data. Our main objective is to develop methods allowing for a direct use of EHR data for the identification of patient cohorts leveraging current EHR standards and semantic web technologies. Materials and Methods We propose to take advantage of the best features of working with EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures. Our main principle is to perform each activity at the abstraction level with the most appropriate technology available. This means that part of the processing will be performed using archetypes (i.e., data level) and the rest using ontologies (i.e., knowledge level). Our approach will start working with EHR data in proprietary format, which will be first normalized and elaborated using EHR standards and then transformed into a semantic representation, which will be exploited by automated reasoning. Results We have applied our approach to protocols for colorectal cancer screening. The results comprise the archetypes, ontologies and datasets developed for the standardization and semantic analysis of EHR data. Anonymized real data has been used and the patients have been successfully classified by the risk of developing colorectal cancer. Conclusion This work provides new insights in how archetypes and ontologies can be effectively combined for EHR-driven phenotyping. The methodological approach can be applied to other problems provided that suitable archetypes, ontologies and classification rules can be designed.This work was supported by the Ministerio de Economia y Competitividad and the FEDER program through grants TIN2010-21388-C01 and TIN2010-21388-C02. MCLG was supported by the Fundacion Seneca through grant 15555/FPI/2010.Fernández-Breis, JT.; Maldonado Segura, JA.; Marcos, M.; Legaz-García, MDC.; Moner Cano, D.; Torres-Sospedra, J.; Esteban-Gil, A.... (2013). Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts. Journal of the American Medical Informatics Association. 20(E2):288-296. https://doi.org/10.1136/amiajnl-2013-001923S28829620E2Cuggia, M., Besana, P., & Glasspool, D. (2011). Comparing semi-automatic systems for recruitment of patients to clinical trials. International Journal of Medical Informatics, 80(6), 371-388. doi:10.1016/j.ijmedinf.2011.02.003Sujansky, W. 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Modelo de Objetos do openEHR: uma Revisão Sistemática da Literatura e sua relação com métricas de software

Dos principais padrões em sistemas de Registro Eletrônico de Saúde (RES), destaca-se a abordagem da Fundação openEHR. Este trabalho apresenta uma Revisão Sistemática da Literatura dos estudos que utilizam esta abordagem com ênfase na utilização do seu Modelo de Objetos. A pesquisa foi realizada nas bases de dados internacionais com base em quatro questões de pesquisa e critérios de inclusão e exclusão definidos. Entre os resultados obtidos, foi possível observar que o continente europeu é o maior centro dos estudos relacionados com a abordagem openEHR, com exceção da Austrália na Oceania. Pode-se concluir que uma versão estável da especificação openEHR contribuiu para o aumento de estudos a partir de 2008. Em relação às métricas de software aplicadas ao modelo do openEHR, até a realização deste trabalho, não se observaram estudos dessa natureza. Além disso, esta revisão possibilitou relacionar as ferramentas para coleta de métricas disponíveis na literatura

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

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

Enriquecimiento de la historia clínica electrónica con información de sistemas de ayuda a la decisión clínica y datos enlazados abiertos

[ES] La explotación de datos de salud ha demostrado ser de creciente interés en la comunidad científica, especialmente para la creación y uso de sistemas de ayuda a la decisión clínica (SADC). Para abordar este problema, tradicionalmente se ha investigado por separado en materia de modelos de información, modelos de dominio y SADC. En lo que se refiere a modelos de información, las propuestas presentan limitaciones semánticas y no tienen en cuenta la interacción con los modelos de dominio, que pretenden proporcionar una comprensión formal y compartida del conocimiento clínico, ni con los SADC, cuya finalidad es proporcionar apoyo a la toma de decisión clínica a partir de la historia clínica electrónica (HCE). La finalidad de esta tesis se enmarca dentro del objetivo general de enriquecer sistemas de HCE con resultados de SADC y modelos de dominio representados mediante datos enlazados abiertos. Para ello, se investiga la combinación y explotación conjunta de las tecnologías más avanzadas para modelos de información, modelos de dominio y SADC. La principal contribución de esta tesis es el desarrollo de metodologías y herramientas para enriquecer la HCE con resultados de SADC y datos enlazados abiertos. Las contribuciones específicas son las siguientes: * Definición conceptual y metodológica de la HCE aumentada con información potencialmente relevante de la web semántica. * Definición conceptual y metodológica del informe radiológico estructurado (IRE), enriquecido con resultados de SADC basados en reglas, visión por computación y modelos de aprendizaje automático. * Caso de uso de HCE aumentada, consistente en enriquecer la HCE resumida del Sistema Nacional de Salud de España con datos enlazados abiertos sobre interacciones farmacológicas y tratamientos recomendados para los episodios activos del paciente. * Sistema de IRE enriquecido con resultados de SADC. Incluye el desarrollo de plantillas de IRE y mecanismos para el enriquecimiento de las mismas con resultados de SADC basados en reglas, cuantificación de imagen médica y redes neuronales. Nuestro objetivo es mejorar el grado de interoperabilidad en las integraciones de sistemas de HCE con SADC y datos enlazados abiertos, mediante estrategias basadas en los tres pilares de la interoperabilidad semántica: modelos de información, de arquetipos y de dominio. Esto tiene el potencial de repercutir positivamente sobre la salud y el cuidado del paciente, especialmente en el paradigma de la medicina personalizada.[CA] L'explotació de dades de salut ha demostrat ser de creixent interés en la comunitat científica, especialment per a la creació i ús de sistemes d'ajuda a la decisió clínica (SADC). Per a abordar aquest problema, tradicionalment s'ha investigat per separat en matèria de models d'informació, models de domini i SADC. Pel que fa a models d'informació, les propostes presenten limitacions semàntiques i no tenen en compte la interacció amb els models de domini, que pretenen proporcionar una comprensió formal i compartida del coneixement clínic, ni amb els SADC, la finalitat dels quals és proporcionar suport a la presa de decisió clínica partint de la història clínica electrònica (HCE). La finalitat d'aquesta tesi s'emmarca dins de l'objectiu general d'enriquir sistemes de HCE amb resultats de SADC i models de domini representats mitjançant dades enllaçades obertes. Per a això, s'investiga la combinació i explotació conjunta de les tecnologies més avançades per a models d'informació, models de domini i SADC. La principal contribució d'aquesta tesi és el desenvolupament de metodologies i eines per a enriquir la HCE amb resultats de SADC i dades enllaçades obertes. Les contribucions específiques són les següents: * Definició conceptual i metodològica de la HCE augmentada amb informació potencialment rellevant de la web semàntica. * Definició conceptual i metodològica de l'informe radiològic estructurat (IRE), enriquit amb resultats de SADC basats en regles, visió per computació i models d'aprenentatge automàtic. * Cas d'ús de HCE augmentada, consistent a enriquir la HCE resumida del Sistema Nacional de Salut d'Espanya amb dades enllaçades obertes sobre interaccions farmacològiques i tractaments recomanats per als episodis actius del pacient. * Sistema de IRE enriquit amb resultats de SADC. Inclou el desenvolupament de plantilles de IRE i mecanismes per a l'enriquiment de les mateixes amb resultats de SADC basats en regles, quantificació d'imatge mèdica i xarxes neuronals. El nostre objectiu és millorar el grau d'interoperabilitat en les integracions de sistemes de HCE amb SADC i dades enllaçades obertes, mitjançant estratègies basades en els tres pilars de la interoperabilitat semàntica: models d'informació, d'arquetips i de domini. Això té el potencial de repercutir positivament sobre la salut i la cura del pacient, especialment en el paradigma de la medicina personalitzada.[EN] The exploitation of health data has proven to be of increasing interest in the scientific community, especially for the creation and use of clinical decision support systems (CDSS). To address this problem, separate research has traditionally been done on information models, domain models and CDSS. Regarding information models, the proposals present semantic limitations and do not consider the interaction with domain models, which aim to provide a formal and shared understanding of clinical knowledge, nor with CDSS, whose purpose is to provide clinical decision support from the electronic health record (EHR). The aim of this thesis is framed within the general goal of enriching EHR systems with SADC results and domain models represented by open linked data. For this purpose, the combination and joint exploitation of state-of-the-art technologies for information models, domain models and SADC is investigated. The main contribution of this thesis is the development of methodologies and tools to enrich EHR with SADC results and open linked data. Specific contributions are: * Conceptual and methodological definition of EHR augmented with potentially relevant information from the semantic web. * Conceptual and methodological definition of the structured radiology report (SRR), enriched with CDSS results based on logical rules, computer vision and machine learning models. * Augmented EHR use case, consisting of enriching the summarized EHR of the Spanish National Health System with linked open data on pharmacological interactions and recommended treatments for active patient episodes. * SRR system enriched with CDSS results. Includes the development of SRR templates and mechanisms for enriching them with SADC results based on logical rules, medical image quantification and neural networks. Our goal is to improve the degree of interoperability in EHR system integrations with CDSS results and linked open data, through strategies based on the three pillars of semantic interoperability: information, archetype and domain models. This has the potential to positively impact health and patient care, especially in the personalized medicine paradigm.Mañas García, A. (2022). Enriquecimiento de la historia clínica electrónica con información de sistemas de ayuda a la decisión clínica y datos enlazados abiertos [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/18773

Arquiteturas federadas para integração de dados biomédicos

Doutoramento Ciências da ComputaçãoThe last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.A adoção sucessiva das tecnologias de comunicação e de informação na área da saúde tem permitido um aumento na diversidade e na qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado uma enorme quantidade de dados, cujo valor científico está ainda por explorar. A partilha e o acesso integrado a esta informação poderá permitir a identificação de novas descobertas que possam conduzir a melhores diagnósticos e a melhores tratamentos clínicos. Esta tese propõe novos modelos de integração e de exploração de dados com vista à extração de conhecimento biomédico a partir de múltiplas fontes de dados. A primeira contribuição é uma arquitetura baseada em nuvem para partilha de serviços de imagem médica. Esta solução oferece um mecanismo de registo simplificado para fornecedores e serviços, permitindo o acesso remoto e facilitando a integração de diferentes fontes de dados. A segunda proposta é uma arquitetura baseada em sensores para integração de registos electrónicos de pacientes. Esta estratégia segue um modelo de integração federado e tem como objetivo fornecer uma solução escalável que permita a pesquisa em múltiplos sistemas de informação. Finalmente, o terceiro contributo é um sistema aberto para disponibilizar dados de pacientes num contexto europeu. Todas as soluções foram implementadas e validadas em cenários reais