Possibilities and implications of using the ICF and other vocabulary standards in electronic health records

There is now widespread recognition of the powerful potential of electronic health record (EHR) systems to improve the health-care delivery system. The benefits of EHRs grow even larger when the health data within their purview are seamlessly shared, aggregated and processed across different providers, settings and institutions. Yet, the plethora of idiosyncratic conventions for identifying the same clinical content in different information systems is a fundamental barrier to fully leveraging the potential of EHRs. Only by adopting vocabulary standards that provide the lingua franca across these local dialects can computers efficiently move, aggregate and use health data for decision support, outcomes management, quality reporting, research and many other purposes. In this regard, the International Classification of Functioning, Disability, and Health (ICF) is an important standard for physiotherapists because it provides a framework and standard language for describing health and health-related states. However, physiotherapists and other health-care professionals capture a wide range of data such as patient histories, clinical findings, tests and measurements, procedures, and so on, for which other vocabulary standards such as Logical Observation Identifiers Names and Codes and Systematized Nomenclature Of Medicine Clinical Terms are crucial for interoperable communication between different electronic systems. In this paper, we describe how the ICF and other internationally accepted vocabulary standards could advance physiotherapy practise and research by enabling data sharing and reuse by EHRs. We highlight how these different vocabulary standards fit together within a comprehensive record system, and how EHRs can make use of them, with a particular focus on enhancing decision-making. By incorporating the ICF and other internationally accepted vocabulary standards into our clinical information systems, physiotherapists will be able to leverage the potent capabilities of EHRs and contribute our unique clinical perspective to other health-care providers within the emerging electronic health information infrastructure

Comparative study of healthcare messaging standards for interoperability in ehealth systems

Advances in the information and communication technology have created the field of "health informatics," which amalgamates healthcare, information technology and business. The use of information systems in healthcare organisations dates back to 1960s, however the use of technology for healthcare records, referred to as Electronic Medical Records (EMR), management has surged since 1990’s (Net-Health, 2017) due to advancements the internet and web technologies. Electronic Medical Records (EMR) and sometimes referred to as Personal Health Record (PHR) contains the patient’s medical history, allergy information, immunisation status, medication, radiology images and other medically related billing information that is relevant. There are a number of benefits for healthcare industry when sharing these data recorded in EMR and PHR systems between medical institutions (AbuKhousa et al., 2012). These benefits include convenience for patients and clinicians, cost-effective healthcare solutions, high quality of care, resolving the resource shortage and collecting a large volume of data for research and educational needs. My Health Record (MyHR) is a major project funded by the Australian government, which aims to have all data relating to health of the Australian population stored in digital format, allowing clinicians to have access to patient data at the point of care. Prior to 2015, MyHR was known as Personally Controlled Electronic Health Record (PCEHR). Though the Australian government took consistent initiatives there is a significant delay (Pearce and Haikerwal, 2010) in implementing eHealth projects and related services. While this delay is caused by many factors, interoperability is identified as the main problem (Benson and Grieve, 2016c) which is resisting this project delivery. To discover the current interoperability challenges in the Australian healthcare industry, this comparative study is conducted on Health Level 7 (HL7) messaging models such as HL7 V2, V3 and FHIR (Fast Healthcare Interoperability Resources). In this study, interoperability, security and privacy are main elements compared. In addition, a case study conducted in the NSW Hospitals to understand the popularity in usage of health messaging standards was utilised to understand the extent of use of messaging standards in healthcare sector. Predominantly, the project used the comparative study method on different HL7 (Health Level Seven) messages and derived the right messaging standard which is suitable to cover the interoperability, security and privacy requirements of electronic health record. The issues related to practical implementations, change over and training requirements for healthcare professionals are also discussed

Clinical coverage of an archetype repository over SNOMED-CT

AbstractClinical archetypes provide a means for health professionals to design what should be communicated as part of an Electronic Health Record (EHR). An ever-growing number of archetype definitions follow this health information modelling approach, and this international archetype resource will eventually cover a large number of clinical concepts. On the other hand, clinical terminology systems that can be referenced by archetypes also have a wide coverage over many types of health-care information.No existing work measures the clinical content coverage of archetypes using terminology systems as a metric. Archetype authors require guidance to identify under-covered clinical areas that may need to be the focus of further modelling effort according to this paradigm.This paper develops a first map of SNOMED-CT concepts covered by archetypes in a repository by creating a so-called terminological Shadow. This is achieved by mapping appropriate SNOMED-CT concepts from all nodes that contain archetype terms, finding the top two category levels of the mapped concepts in the SNOMED-CT hierarchy, and calculating the coverage of each category. A quantitative study of the results compares the coverage of different categories to identify relatively under-covered as well as well-covered areas. The results show that the coverage of the well-known National Health Service (NHS) Connecting for Health (CfH) archetype repository on all categories of SNOMED-CT is not equally balanced. Categories worth investigating emerged at different points on the coverage spectrum, including well-covered categories such as Attributes, Qualifier value, under-covered categories such as Microorganism, Kingdom animalia, and categories that are not covered at all such as Cardiovascular drug (product)

Content diffusion in ALERT clinical applications

Estágio realizado na ALERT e orientado pelo Eng.º Tiago SilvaTese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Terminology Services: Standard Terminologies to Control Medical Vocabulary. “Words are Not What they Say but What they Mean”

Data entry is an obstacle for the usability of electronic health records (EHR) applications and the acceptance of physicians, who prefer to document using “free text”. Natural language is huge and very rich in details but at the same time is ambiguous; it has great dependence on context and uses jargon and acronyms. Healthcare Information Systems should capture clinical data in a structured and preferably coded format. This is crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions, etc. In order to address this point, numerous terminological systems for the systematic recording of clinical data have been developed. These systems interrelate concepts of a particular domain and provide reference to related terms and possible definitions and codes. The purpose of terminology services consists of representing facts that happen in the real world through database management. This process is named Semantic Interoperability. It implies that different systems understand the information they are processing through the use of codes of clinical terminologies. Standard terminologies allow controlling medical vocabulary. But how do we do this? What do we need? Terminology services are a fundamental piece for health data management in health environment

Decision support system for in-flight emergency events

Medical problems during flight have become an important issue as the number of passengers and miles flown continues to increase. The case of an incident in the plane falls within the scope of the healthcare management in the context of scarce resources associated with isolation of medical actors working in very complex conditions, both in terms of human and material resources. Telemedicine uses information and communication technologies to provide remote and flexible medical services, especially for geographically isolated people. Therefore, telemedicine can generate interesting solutions to the medical problems during flight. Our aim is to build a knowledge-based system able to help health professionals or staff members addressing an urgent situation by given them relevant information, some knowledge, and some judicious advice. In this context, knowledge representation and reasoning can be correctly realized using an ontology that is a representation of concepts, their attributes, and the relationships between them in a particular domain. Particularly, a medical ontology is a formal representation of a vocabulary related to a specific health domain. We propose a new approach to explain the arrangement of different ontological models (task ontology, inference ontology, and domain ontology), which are useful for monitoring remote medical activities and generating required information. These layers of ontologies facilitate the semantic modeling and structuring of health information. The incorporation of existing ontologies [for instance, Systematic Nomenclature Medical Clinical Terms (SNOMED CT)] guarantees improved health concept coverage with experienced knowledge. The proposal comprises conceptual means to generate substantial reasoning and relevant knowledge supporting telemedicine activities during the management of a medical incident and its characterization in the context of air travel. The considered modeling framework is sufficiently generic to cover complex medical situations for isolated and vulnerable populations needing some care and support services

Combining ontologies and rules with clinical archetypes

Al igual que otros campos que dependen en gran medida de las funcionalidades ofrecidas por las tecnologías de la información y las comunicaciones (IT), la biomedicina y la salud necesitan cada vez más la implantación de normas y mecanismos ampliamente aceptados para el intercambio de datos, información y conocimiento. Dicha necesidad de compatibilidad e interoperabilidad va más allá de las cuestiones sintácticas y estructurales, pues la interoperabilidad semántica es también requerida. La interoperabilidad a nivel semántico es esencial para el soporte computarizado de alertas, flujos de trabajo y de la medicina basada en evidencia cuando contamos con la presencia de sistemas heterogéneos de Historia Clínica Electrónica (EHR). El modelo de arquetipos clínicos respaldado por el estándar CEN/ISO EN13606 y la fundación openEHR ofrece un mecanismo para expresar las estructuras de datos clínicos de manera compartida e interoperable. El modelo ha ido ganando aceptación en los últimos años por su capacidad para definir conceptos clínicos basados en un Modelo de Referencia común. Dicha separación a dos capas permite conservar la heterogeneidad de las implementaciones de almacenamiento a bajo nivel, presentes en los diferentes sistemas de EHR. Sin embargo, los lenguajes de arquetipos no soportan la representación de reglas clínicas ni el mapeo a ontologías formales, ambos elementos fundamentales para alcanzar la interoperabilidad semántica completa pues permiten llevar a cabo el razonamiento y la inferencia a partir del conocimiento clínico existente. Paralelamente, es reconocido el hecho de que la World Wide Web presenta requisitos análogos a los descritos anteriormente, lo cual ha fomentado el desarrollo de la Web Semántica. El progreso alcanzado en este terreno, con respecto a la representación del conocimiento y al razonamiento sobre el mismo, es combinado en esta tesis con los modelos de EHR con el objetivo de mejorar el enfoque de los arquetipos clínicos y ofrecer funcionalidades que se corresponden con nivel más alto de interoperabilidad semántica. Concretamente, la investigación que se describe a continuación presenta y evalúa un enfoque para traducir automáticamente las definiciones expresadas en el lenguaje de definición de arquetipos de openEHR (ADL) a una representación formal basada en lenguajes de ontologías. El método se implementa en la plataforma ArchOnt, que también es descrita. A continuación se estudia la integración de dichas representaciones formales con reglas clínicas, ofreciéndose un enfoque para reutilizar el razonamiento con instancias concretas de datos clínicos. Es importante ver como el acto de compartir el conocimiento clínico expresado a través de reglas es coherente con la filosofía de intercambio abierto fomentada por los arquetipos, a la vez que se extiende la reutilización a proposiciones de conocimiento declarativo como las utilizadas en las guías de práctica clínica. De esta manera, la tesis describe una técnica de mapeo de arquetipos a ontologías, para luego asociar reglas clínicas a la representación resultante. La traducción automática también permite la conexión formal de los elementos especificados en los arquetipos con conceptos clínicos equivalentes provenientes de otras fuentes como son las terminologías clínicas. Dichos enlaces fomentan la reutilización del conocimiento clínico ya representado, así como el razonamiento y la navegación a través de distintas ontologías clínicas. Otra contribución significativa de la tesis es la aplicación del enfoque mencionado en dos proyectos de investigación y desarrollo clínico, llevados a cabo en combinación con hospitales universitarios de Madrid. En la explicación se incluyen ejemplos de las aplicaciones más representativas del enfoque como es el caso del desarrollo de sistemas de alertas orientados a mejorar la seguridad del paciente. No obstante, la traducción automática de arquetipos clínicos a lenguajes de ontologías constituye una base común para la implementación de una amplia gama de actividades semánticas, razonamiento y validación, evitándose así la necesidad de aplicar distintos enfoques ad-hoc directamente sobre los arquetipos para poder satisfacer las condiciones de cada contexto