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Health information exchange (HIE) systems are being developed across the nation. Understanding approaches taken by existing successful exchanges can help new exchange efforts determine goals and plan implementations. The goal of this study was to explore characteristics of use and users of a successful regional HIE.

Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems.

To present a partnership-based and community-oriented approach designed to ease provider anxiety and facilitate the implementation of electronic health records (EHR) in resource-limited primary care settings.

To compare the use of structured reporting software and the standard electronic medical records (EMR) in the management of patients with bladder cancer. The use of a human factors laboratory to study management of disease using simulated clinical scenarios was also assessed.

A supervised machine learning approach to discover relations between medical problems, treatments, and tests mentioned in electronic medical records.

Implementing health information technology (IT) at the community level is a national priority to help improve healthcare quality, safety, and efficiency. However, community-based organizations implementing health IT may not have expertise in evaluation. This study describes lessons learned from experience as a multi-institutional academic collaborative established to provide independent evaluation of community-based health IT initiatives. The authors' experience derived from adapting the principles of community-based participatory research to the field [...]

To evaluate the incidence of duplicate medication orders before and after computerized provider order entry (CPOE) with clinical decision support (CDS) implementation and identify contributing factors.

This paper describes natural-language-processing techniques for two tasks: identification of medical concepts in clinical text, and classification of assertions, which indicate the existence, absence, or uncertainty of a medical problem. Because so many resources are available for processing clinical texts, there is interest in developing a framework in which features derived from these resources can be optimally selected for the two tasks of interest.