Ubiquitous-Severance Hospital Project: Implementation and Results

OBJECTIVES: The purpose of this study was to review an implementation of u-Severance information system with focus on electronic hospital records (EHR) and to suggest future improvements. METHODS: Clinical Data Repository (CDR) of u-Severance involved implementing electronic medical records (EMR) as the basis of EHR and the management of individual health records. EHR were implemented with service enhancements extending to the clinical decision support system (CDSS) and expanding the knowledge base for research with a repository for clinical data and medical care information. RESULTS: The EMR system of Yonsei University Health Systems (YUHS) consists of HP integrity superdome servers using MS SQL as a database management system and MS Windows as its operating system. CONCLUSIONS: YUHS is a high-performing medical institution with regards to efficient management and customer satisfaction; however, after 5 years of implementation of u-Severance system, several limitations with regards to expandability and security have been identifiedope

A national registry for juvenile dermatomyositis and other paediatric idiopathic inflammatory myopathies: 10 years' experience; the Juvenile Dermatomyositis National (UK and Ireland) Cohort Biomarker Study and Repository for Idiopathic Inflammatory Myopathies

Objectives: The paediatric idiopathic inflammatory myopathies (IIMs) are a group of rare chronic inflammatory disorders of childhood, affecting muscle, skin and other organs. There is a severe lack of evidence base for current treatment protocols in juvenile myositis. The rarity of these conditions means that multicentre collaboration is vital to facilitate studies of pathogenesis, treatment and disease outcomes. We have established a national registry and repository for childhood IIM, which aims to improve knowledge, facilitate research and clinical trials, and ultimately to improve outcomes for these patients. Methods: A UK-wide network of centres and research group was established to contribute to the study. Standardized patient assessment, data collection forms and sample protocols were agreed. The Biobank includes collection of peripheral blood mononuclear cells, serum, genomic DNA and biopsy material. An independent steering committee was established to oversee the use of data/samples. Centre training was provided for patient assessment, data collection and entry. Results: Ten years after inception, the study has recruited 285 children, of which 258 have JDM or juvenile PM; 86% of the cases have contributed the biological samples. Serial sampling linked directly to the clinical database makes this a highly valuable resource. The study has been a platform for 20 sub-studies and attracted considerable funding support. Assessment of children with myositis in contributing centres has changed through participation in this study. Conclusions: This establishment of a multicentre registry and Biobank has facilitated research and contributed to progress in the management of a complex group of rare muscloskeletal conditions

Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework--a dynamic knowledge repository--wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline

On-Demand Big Data Integration: A Hybrid ETL Approach for Reproducible Scientific Research

Scientific research requires access, analysis, and sharing of data that is distributed across various heterogeneous data sources at the scale of the Internet. An eager ETL process constructs an integrated data repository as its first step, integrating and loading data in its entirety from the data sources. The bootstrapping of this process is not efficient for scientific research that requires access to data from very large and typically numerous distributed data sources. a lazy ETL process loads only the metadata, but still eagerly. Lazy ETL is faster in bootstrapping. However, queries on the integrated data repository of eager ETL perform faster, due to the availability of the entire data beforehand. In this paper, we propose a novel ETL approach for scientific data integration, as a hybrid of eager and lazy ETL approaches, and applied both to data as well as metadata. This way, Hybrid ETL supports incremental integration and loading of metadata and data from the data sources. We incorporate a human-in-the-loop approach, to enhance the hybrid ETL, with selective data integration driven by the user queries and sharing of integrated data between users. We implement our hybrid ETL approach in a prototype platform, Obidos, and evaluate it in the context of data sharing for medical research. Obidos outperforms both the eager ETL and lazy ETL approaches, for scientific research data integration and sharing, through its selective loading of data and metadata, while storing the integrated data in a scalable integrated data repository.Comment: Pre-print Submitted to the DMAH Special Issue of the Springer DAPD Journa

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. Computer technology can be employed to provide clinical decision support and treatment recommendations. The problem of natural language applications is that they lack formality and the interpretation is not consistent. Conversely, ontologies can capture the intended meaning and specify modeling primitives. Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS). The proposed DSS uses Case-Based Reasoning (CBR) to consider disease manifestations and provides physicians with treatment solutions from similar previous cases for reference. The proposed DSS supports natural language processing (NLP) queries. The DSS obtained 84.63% accuracy in disease classification with the help of the ontology

Design and implementation of a federated health record server

This paper describes the practical implementation of a federated health record serverbased on a generic and comprehensive public domain architecture and deployed in alive clinical setting.The authors, working at the Centre for Health Informatics and MultiprofessionalEducation (University College London), have built up over a decade of experiencewithin Europe on the requirements and information models that are needed to underpincomprehensive multi-professional electronic health records. This work has involvedcollaboration with a wide range of healthcare and informatics organisations and partnersin the healthcare computing industry across Europe though the EU Health Telematicsprojects GEHR, Synapses, EHCR-SupA, SynEx and Medicate. The resultingarchitecture models have influenced recent European standards in this area, such asCEN TC/251 ENV 13606. UCL has now designed and built a federated health recordserver based on these models which is now running in the Department ofCardiovascular Medicine at the Whittington Hospital in north London. A new EC FifthFramework project, 6WINIT, is enabling new and innovative IPv6 and wirelesstechnology solutions to be added to this work.The north London clinical demonstrator site has provided the solid basis from which toestablish "proof of concept" verification of the design approach, and a valuableopportunity to install, test and evaluate the results of the component engineeringundertaken during the EC funded projects

Ethical issues of electronic patient data and informatics in clinical trial settings

The field of cancer bio-informatics unites the disciplines of scientific and clinical research withclinical practice and the treatment of individual patients. There is a need to study patients andsometimes their families, over many decades, to follow disease progress and long-term outcomes.This may require research teams to access the routinely-collected health data from generalpractice and hospital health records, prior to and after the cancer diagnosis is made. This clinicalinformation will increasingly include data provided by patients or acquired from them throughwearable devices that can monitor or deliver treatment, and data acquired from genetic relativesof the patient.All of these data, whether explicitly collected for the purpose of a clinical study, or routinelycollected as part of a patient?s life-time healthcare journey, are personal health data. There areethical and legal requirements to manage these data with care. This chapter explores the ethicalrequirements for collecting, holding, analysing and sharing personal health data, and thelegislation covering such activities

What are the quality indicators in wound care?

This paper discusses quality indicators that relate to wound care. As clinicians will be assessed against national quality indicators from April 2010, it is important for carers working in tissue viability to gain an understanding of what they are. The Darzi report (Department of Health, 2008) identified that high quality care for patients is an aspiration that is only possible with high quality education and training for all staff involved in NHS services. Continued education and promotion of quality in the field of tissue viability will be more attainable if the NHS, higher education institutions and industry strengthen their partnerships

Semantic Integration of Cervical Cancer Data Repositories to Facilitate Multicenter Association Studies: The ASSIST Approach

The current work addresses the unifi cation of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifi es multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing fl exibility by allowing the formation of study groups “on demand” and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profi le) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the defi nition and representation of the disease’s medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains

RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction

Robots have potential to revolutionize the way we interact with the world around us. One of their largest potentials is in the domain of mobile health where they can be used to facilitate clinical interventions. However, to accomplish this, robots need to have access to our private data in order to learn from these data and improve their interaction capabilities. Furthermore, to enhance this learning process, the knowledge sharing among multiple robot units is the natural step forward. However, to date, there is no well-established framework which allows for such data sharing while preserving the privacy of the users (e.g., the hospital patients). To this end, we introduce RoboChain - the first learning framework for secure, decentralized and computationally efficient data and model sharing among multiple robot units installed at multiple sites (e.g., hospitals). RoboChain builds upon and combines the latest advances in open data access and blockchain technologies, as well as machine learning. We illustrate this framework using the example of a clinical intervention conducted in a private network of hospitals. Specifically, we lay down the system architecture that allows multiple robot units, conducting the interventions at different hospitals, to perform efficient learning without compromising the data privacy.Comment: 7 pages, 6 figure