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There is increasing pressure to share health information and even make it publicly available. However, such disclosures of personal health information raise serious privacy concerns. To alleviate such concerns, it is possible to anonymize the data before disclosure. One popular anonymization approach is k-anonymity. There have been no evaluations of the actual re-identification probability of k-anonymized data sets.

Chronic disease prevalence and burden is growing, as is the need for applicable large community-based clinical trials of potential interventions. To support the development of clinical trial management systems for such trials, a community-based primary care research information model is needed. We analyzed the requirements of trials in this environment, and constructed an information model to drive development of systems supporting trial design, execution, and analysis. We anticipate that this [...]

To test whether the use of an evidence retrieval system that uses clinically targeted meta-search filters can enhance the rate at which clinicians make correct decisions, reduce the effort involved in locating evidence, and provide an intuitive match between clinical tasks and search filters.

The use of doctor-computer interaction devices in the operation room (OR) requires new modalities that support medical imaging manipulation while allowing doctors' hands to remain sterile, supporting their focus of attention, and providing fast response times. This paper presents "Gestix," a vision-based hand gesture capture and recognition system that interprets in real-time the user's gestures for navigation and manipulation of images in an electronic medical record (EMR) database. Navigation and [...]

This study sought to identify opportunities to safely turn off frequently overridden drug-drug interaction alerts (DDIs) in computerized physician order entry (CPOE).

This study sought to design and validate a reliable instrument to assess the quality of physician documentation.

The aim of this study was to improve naïve Bayes prediction of Medical Subject Headings (MeSH) assignment to documents using optimal training sets found by an active learning inspired method.

Despite the proliferation of consumer health sites, lay individuals often experience difficulty finding health information online. The present study attempts to understand users' information seeking difficulties by drawing on a hypothesis testing explanatory framework. It also addresses the role of user competencies and their interaction with internet resources.

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance [...]

All methods of identifying medication prescribing errors are fraught with inaccuracies and systematic bias. A systematic, efficient, and inexpensive way of measuring and quantifying prescribing errors would be a useful step for reducing them. We ask if rapid discontinuations of prescription-orders--where physicians stop their orders within 2 hours--would be an expedient proxy for prescribing errors? To study this we analyzed CPOE-system medication orders entered and then discontinued within 2 hours [...]