@neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

From guidelines to careflows: modelling and supporting complex clinical processes.

Research on computer interpretable clinical guidelines has largely focused on individual points of care rather than processes of care. Whether we consider simple aids like clinical alerts and reminders or more sophisticated data interpretation and decision-making, guideline developers tend to focus on specific tasks rather than processes like care plans and pathways which are extended in time. In contrast, research on business process modelling has demonstrated notations and tools which deal directly with process modelling, but has not been concerned with problems like data interpretation and decision making. In this chapter we describe these two traditions, and compare some of their strengths and weaknesses. We also briefly discuss the distinct theoretical frameworks which have grown up around them, notably Petri nets for workflow modelling and mathematical logics for guidelines. We conclude that these offer complementary views of clinical processes and that a key research challenge is find a way of unifying them.

Promoting evidence-based management of anemia in cancer patients: background, development, and scientific validation of RESPOND, a web-based clinical guidance system based on the EORTC guidelines.

The 2006 EORTC guidelines for erythropoietic proteins in cancer-related anemia provide the most up-to-date assessment of the evidence base. Considering general concerns in medicine about clinicians' adoption of evidence-based guidelines, it is critical to find ways of bringing guidelines to the point of care. We describe the rationale behind RESPOND, a web-based clinical guidance system based on the EORTC guidelines, and the methodologies of two studies conducted to validate the system. In a first descriptive study, experts are asked to rate the accuracy of every algorithm derived from the guidelines. In a second step and using a hybrid matched pre-post design, separate retrospective and prospective patient cohorts matched by type of cancer and similarity of chemotherapy regimen (33 pairs) are used to examine the extent to which clinicians' practice patterns converge with the EORTC guidelines when they use or not use the RESPOND system. It is hypothesized that these studies will provide the necessary validation for RESPOND as an evidence-based clinical support tool.

International dispersial of Bourgelat's veterinary vision.

Reviewing the history , one is impressed by the remarkable speed with which the grand and powerful idea of creating a new profession of veterinary medicine spread throughout the world (even long before the emergence of electronic transmission). Four factors stand out as key components to this successful dissemination. First, there was the magnificent idea of veterinary education coupled to the powerful motivation of Bourgelat. Second, there existed at the time a tremendous perceived social need for improved animal health, initially for military purposes, the later for issues of food and fiber production. This factor continues to evolve today, with the increasing focus on animal welfare adn companion animal care. Third, support of political leaders with the power to launch the vision was generated. Fourth, of crucial importance was the sustaining of the meme by highly talented and dedicated individuals who modified and improved the original idea to allow for continuing renewal and growth. These four factors seem to have been the most salient features for the achievement of the initiation and the dynamic progression of the new profession.