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

Doctor of Philosophy

dissertationGenetic testing is becoming increasingly important to medical practice since the completion of the Human Genome project. To realize the full promise of personalized medicine, we need to first integrate genetic and genomic information into Electronic Health Records (EHRs) as coded and structured data using standards. However, EHRs are not ready for genomic medicine; lack of standardized information models and termi-nologies for genetic and genomic data representation is recognized as one of the major barriers. In this study, we have focused on constitutional cytogenetic tests. We first evaluat-ed the Logical Observation Identifiers Names and Codes (LOINC), the de facto vocabu-lary standard for representing laboratory test names and results, and identified that a gap exists in LOINC to support the integration of cytogenetic test results into EHRs. We ana-lyzed sample clinical reports from several large cytogenetics laboratories, and developed LOINC panels and codes for representing constitutional cytogenetic test findings through the LOINC panel approach. The LOINC committee approved the cytogenetic LOINC panels and officially released them as part of the LOINC database in December 2010. We then followed the well vetted standard development process of Health Level Seven (HL7), developed and balloted a HL7 version 2 implementation guide that details how these LOINC panels are coupled with the messaging standard to transfer cytogenetic test iv results over the wire. We also described the advantages of coupling the LOINC panel content to HL7 version 2 messages, and why we think this approach could be a practical and efficient way for implementers to develop interfaces that utilize standard information models bound to standard terminologies. We have filled the gap that there were no standard information models and no standard terminologies for representing constitutional cytogenetic test results, and have developed the foundation to allow incremental enhancement in the future

Lessons Learned from Implementing Service-Oriented Clinical Decision Support at Four Sites: A Qualitative Study

Objective To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Methods Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. Results We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Discussion Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. Conclusion The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services

A collaborative platform for management of chronic diseases via guideline-driven individualized care plans

Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans. We also report the results of usability studies carried out in four pilot sites by patients and clinicians

A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases

PhDData stored in individual autonomous databases often needs to be combined and interrelated. For example, in the Inland Water (IW) environment monitoring domain, the spatial and temporal variation of measurements of different water quality indicators stored in different databases are of interest. Data from multiple data sources is more complex to combine when there is a lack of metadata in a computation forin and when the syntax and semantics of the stored data models are heterogeneous. The main types of information retrieval (IR) requirements are query transparency and data harmonisation for data interoperability and support for multiple user views. A combined Semantic Web based and Agent based distributed system framework has been developed to support the above IR requirements. It has been implemented using the Jena ontology and JADE agent toolkits. The semantic part supports the interoperability of autonomous data sources by merging their intensional data, using a Global-As-View or GAV approach, into a global semantic model, represented in DAML+OIL and in OWL. This is used to mediate between different local database views. The agent part provides the semantic services to import, align and parse semantic metadata instances, to support data mediation and to reason about data mappings during alignment. The framework has applied to support information retrieval, interoperability and multi-lateral viewpoints for four European environmental agency databases. An extended GAV approach has been developed and applied to handle queries that can be reformulated over multiple user views of the stored data. This allows users to retrieve data in a conceptualisation that is better suited to them rather than to have to understand the entire detailed global view conceptualisation. User viewpoints are derived from the global ontology or existing viewpoints of it. This has the advantage that it reduces the number of potential conceptualisations and their associated mappings to be more computationally manageable. Whereas an ad hoc framework based upon conventional distributed programming language and a rule framework could be used to support user views and adaptation to user views, a more formal framework has the benefit in that it can support reasoning about the consistency, equivalence, containment and conflict resolution when traversing data models. A preliminary formulation of the formal model has been undertaken and is based upon extending a Datalog type algebra with hierarchical, attribute and instance value operators. These operators can be applied to support compositional mapping and consistency checking of data views. The multiple viewpoint system was implemented as a Java-based application consisting of two sub-systems, one for viewpoint adaptation and management, the other for query processing and query result adjustment

A standards-based ICT framework to enable a service-oriented approach to clinical decision support

This research provides evidence that standards based Clinical Decision Support (CDS) at the point of care is an essential ingredient of electronic healthcare service delivery. A Service Oriented Architecture (SOA) based solution is explored, that serves as a task management system to coordinate complex distributed and disparate IT systems, processes and resources (human and computer) to provide standards based CDS. This research offers a solution to the challenges in implementing computerised CDS such as integration with heterogeneous legacy systems. Reuse of components and services to reduce costs and save time. The benefits of a sharable CDS service that can be reused by different healthcare practitioners to provide collaborative patient care is demonstrated. This solution provides orchestration among different services by extracting data from sources like patient databases, clinical knowledge bases and evidence-based clinical guidelines (CGs) in order to facilitate multiple CDS requests coming from different healthcare settings. This architecture aims to aid users at different levels of Healthcare Delivery Organizations (HCOs) to maintain a CDS repository, along with monitoring and managing services, thus enabling transparency. The research employs the Design Science research methodology (DSRM) combined with The Open Group Architecture Framework (TOGAF), an open source group initiative for Enterprise Architecture Framework (EAF). DSRM’s iterative capability addresses the rapidly evolving nature of workflows in healthcare. This SOA based solution uses standards-based open source technologies and platforms, the latest healthcare standards by HL7 and OMG, Decision Support Service (DSS) and Retrieve, Update Locate Service (RLUS) standard. Combining business process management (BPM) technologies, business rules with SOA ensures the HCO’s capability to manage its processes. This architectural solution is evaluated by successfully implementing evidence based CGs at the point of care in areas such as; a) Diagnostics (Chronic Obstructive Disease), b) Urgent Referral (Lung Cancer), c) Genome testing and integration with CDS in screening (Lynch’s syndrome). In addition to medical care, the CDS solution can benefit organizational processes for collaborative care delivery by connecting patients, physicians and other associated members. This framework facilitates integration of different types of CDS ideal for the different healthcare processes, enabling sharable CDS capabilities within and across organizations

Intégration de ressources en recherche translationnelle : une approche unificatrice en support des systèmes de santé "apprenants"

Learning health systems (LHS) are gradually emerging and propose a complimentary approach to translational research challenges by implementing close coupling of health care delivery, research and knowledge translation. To support coherent knowledge sharing, the system needs to rely on an integrated and efficient data integration platform. The framework and its theoretical foundations presented here aim at addressing this challenge. Data integration approaches are analysed in light of the requirements derived from LHS activities and data mediation emerges as the one most adapted for a LHS. The semantics of clinical data found in biomedical sources can only be fully derived by taking into account, not only information from the structural models (field X of table Y), but also terminological information (e.g. International Classification of Disease 10th revision) used to encode facts. The unified framework proposed here takes this into account. The platform has been implemented and tested in context of the TRANSFoRm endeavour, a European project funded by the European commission. It aims at developing a LHS including clinical activities in primary care. The mediation model developed for the TRANSFoRm project, the Clinical Data Integration Model, is presented and discussed. Results from TRANSFoRm use-cases are presented. They illustrate how a unified data sharing platform can support and enhance prospective research activities in context of a LHS. In the end, the unified mediation framework presented here allows sufficient expressiveness for the TRANSFoRm needs. It is flexible, modular and the CDIM mediation model supports the requirements of a primary care LHS.Les systèmes de santé "apprenants" (SSA) présentent une approche complémentaire et émergente aux problèmes de la recherche translationnelle en couplant de près les soins de santé, la recherche et le transfert de connaissances. Afin de permettre un flot d’informations cohérent et optimisé, le système doit se doter d’une plateforme intégrée de partage de données. Le travail présenté ici vise à proposer une approche de partage de données unifiée pour les SSA. Les grandes approches d’intégration de données sont analysées en fonction du SSA. La sémantique des informations cliniques disponibles dans les sources biomédicales est la résultante des connaissances des modèles structurelles des sources mais aussi des connaissances des modèles terminologiques utilisés pour coder l’information. Les mécanismes de la plateforme unifiée qui prennent en compte cette interdépendance sont décrits. La plateforme a été implémentée et testée dans le cadre du projet TRANSFoRm, un projet européen qui vise à développer un SSA. L’instanciation du modèle de médiation pour le projet TRANSFoRm, le Clinical Data Integration Model est analysée. Sont aussi présentés ici les résultats d’un des cas d’utilisation de TRANSFoRm pour supporter la recherche afin de donner un aperçu concret de l’impact de la plateforme sur le fonctionnement du SSA. Au final, la plateforme unifiée d’intégration proposée ici permet un niveau d’expressivité suffisant pour les besoins de TRANSFoRm. Le système est flexible et modulaire et le modèle de médiation CDIM couvre les besoins exprimés pour le support des activités d’un SSA comme TRANSFoRm

Master of Science

thesisLack of information is a serious concern for clinicians. Information resources can address this problem, leading to improvements in decision making and patient outcomes. Genomics is an information-rich domain where searching for information can be complex. For example, most physicians agree that pharmacogenomics can be used to improve the quality of care, and there is evidence that many patients harbor actionable pharmacogenomic variation. However, surveys have shown that physicians feel their knowledge of pharmacogenomics to be inadequate. This represents an information need. A natural approach to meet this need is to provide context-aware access to the precise information needed. The Health Level 7 Context-Aware Knowledge Retrieval Standard, a.k.a the Infobutton, offers a modality to deliver context-aware knowledge into electronic health record (EHR) systems. OpenInfobutton is a reference implementation of this standard that offers an open-source instantiation. In this thesis, we aimed to provide insight into pharmacogenomics information needs and an automated mechanism for addressing these needs. Such work can aid the design of tools that support clinical decisions in genomics