A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

A Repository of Semantic Open EHR Archetypes

This paper describes a repository of openEHR archetypes that have been translated to OWL. In the work presented here, five different CKMs (Clinical Knowledge Managers) have been downloaded and the archetypes have been translated to OWL. This translation is based on an existing translator that has been improved to solve programming problems with certain structures. As part of the repository a tool has been developed to keep it always up-to-date. So, any change in one of the CKMs (addition, elimination or even change of an archetype) will involve translating the changed archetypes once more. The repository is accessible through a Web interface (http://www.openehr.es/)

Developing the first generally-available openEHR archetypes and templates for physiotherapy: an example of building clinical models and modelling capacity via student-led academic–industrial collaboration

Given the clear assertions in published literature that physiotherapy needs, and will benefit from, electronic health records, it was surprising that the international repository for clinical models for the openEHR record architecture (the Clinical Knowledge Manager or CKM at openehr.org/ckm ) made no reference to physiotherapy, and that other published modelling work had not used formalisms that provided for easy re-use. We set out to explore what would be involved in changing this

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

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research

Background Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. Results The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. Conclusions The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu

The Morningside Initiative: Collaborative Development of a Knowledge Repository to Accelerate Adoption of Clinical Decision Support

The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It is based on the belief that sharing of knowledge can be highly effective as is the case in other competitive domains such as genomics. Participants in the Morningside Initiative believe that a coordinated effort between the private and public sectors is needed to accomplish this goal and that a small number of highly visible and respected health care organizations in the public and private sector can lead by example. Ultimately, a future collaborative knowledge sharing organization must have a sustainable long-term business model for financial support

Information Systems and Healthcare XXI: A Dynamic, Client-Centric, Point-Of-Care System for the Novice Nurse

Nurse clinicians need to make complex decisions on a continual basis, while delivering cost-effective treatments. The rapid proliferation of medical and nursing knowledge complicates the decision-making process, particularly for novice nurses. We describe a Clinical Decision Support System (CDSS) for the novice nurse that combines evidence-based nursing knowledge with specific patient information to create a real-time guide through the nursing diagnostic care process. The goal of the paper is to describe how an appropriately designed and evidence-based CDSS can aid the nursing practice. An off-the-shelf handheld computer is utilized to deliver clinical knowledge to the nurse, via wireless link to a central server and a data repository. In describing the software architecture of the system, particular emphasis is paid to the issue of appropriate design by discussing the steps taken to address system extensibility, performance, reliability, and security, which are important factors in the design of a CDSS

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