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This paper presents a multiple perspectives model of clinical information system implementation, the CONTEXTual Implementation Model (CIM). Although other implementation models have been developed, few are grounded in data and others fail to take adequate account of the clinical environment and users' requirements.

The European INFOBIOMED Network of Excellence recognized that a successful education program in biomedical informatics should include not only traditional teaching activities in the basic sciences but also the development of skills for working in multidisciplinary teams.

Complete patient health information that is available where and when it is needed is essential to providers and patients and improves healthcare quality and patient safety. VA and DoD have built on their previous experience in patient data exchange to establish data standards and terminology services to enable real-time bi-directional computable (i.e., encoded) data exchange and achieve semantic interoperability in compliance with recommended national standards and the eGov initiative. The [...]

Unstructured electronic information sources, such as news reports, are proving to be valuable inputs for public health surveillance. However, staying abreast of current disease outbreaks requires scouring a continually growing number of disparate news sources and alert services, resulting in information overload. Our objective is to address this challenge through the HealthMap.org Web application, an automated system for querying, filtering, integrating and visualizing unstructured reports on disease outbreaks.

We conducted a prospective observational study to (1) determine usage and construct validity of a method to gauge the cognitive impact of information derived from daily e-mail, and (2) describe self-reported impacts of research-based synopses (InfoPOEMs) delivered as e-mail. Ratings of InfoPOEMs using an Impact assessment scale provided (a) data on usage of the impact assessment method, (b) reports of impact by InfoPOEM and by doctor and (c) data for [...]

We examine the feasibility of a machine learning approach to identification of foot examination (FE) findings from the unstructured text of clinical reports. A Support Vector Machine (SVM) based system was constructed to process the text of physical examination sections of in- and out-patient clinical notes to identify if the findings of structural, neurological, and vascular components of a FE revealed normal or abnormal findings or were not assessed. The [...]

To assess compliance with a clinical decision support system (CDSS) for diagnostic management of children with fever without apparent source and to study the effects of application of the CDSS on time spent in the emergency department (ED) and number of laboratory tests.

Explore the automated acquisition of knowledge in biomedical and clinical documents using text mining and statistical techniques to identify disease-drug associations.

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using [...]

We describe the architecture of LifeCode (A-Life Medical, Inc.), a natural language processing system for free-text clinical information extraction, our methodology in applying LifeCode to the i2b2 smoking challenge, and statistical measures for performance evaluation. Due to the limited test size and the coefficient of variation in the test standard, it is difficult to draw conclusions regarding the relative efficacy of approaches that were applied to this challenge.