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We seek to quantify the mortality risk associated with mentions of medical concepts in textual electronic health records (EHRs). Recognizing mentions of named entities of relevant types (eg, conditions, symptoms, laboratory tests or behaviors) in text is a well-researched task. However, determining the level of risk associated with them is partly dependent on the textual context in which they appear, which may describe severity, temporal aspects, quantity, etc.

Translational science aims at "translating" basic scientific discoveries into clinical applications. The identification of translational science has practicality such as evaluating the effectiveness of investments made into large programs like the Clinical and Translational Science Awards. Despite several proposed methods that group publications-the primary unit of research output-into some categories, we still lack a quantitative way to place articles onto the full, continuous spectrum from basic research to clinical medicine.

Systematic surveillance for venous thromboembolism (VTE) in the United States has been recommended by several organizations. Despite adoption of electronic medical records (EMRs) by most health care providers and facilities, however, systematic surveillance for VTE is not available.

Discrepancies in controlled substance documentation are common and can lead to legal and regulatory repercussions. We introduced a visual analytics dashboard to assist in a quality improvement project to reduce the discrepancies in controlled substance documentation in the operating room (OR) of our free-standing pediatric hospital.

Health care-associated infections, specifically catheter-associated urinary tract infections (CAUTIs), can cause significant mortality and morbidity. However, the process of collecting CAUTI surveillance data, storing it, and visualizing the data to inform health policy has been fraught with challenges.

The implementation of health information technology (HIT) is complex. A method for mitigating complexity is incrementalism. Incrementalism forms the foundation of both incremental software development models, like agile, and the Plan-Do-Study-Act cycles (PDSAs) of quality improvement (QI), yet we often fail to be incremental at the union of the disciplines. We propose a new model for HIT implementation that explicitly links incremental software development cycles with PDSAs, the QI-HIT Figure [...]

With the pervasive use of health information technology (HIT) there has been increased concern over the usability and safety of this technology. Identifying HIT usability and safety hazards, mitigating those hazards to prevent patient harm, and using this knowledge to improve future HIT systems are critical to advancing health care.

Clinical decision support systems (CDSSs) are a good strategy for preventing medication errors and reducing the incidence and severity of adverse drug events (ADEs). However, these systems are not very effective and are subject to multiple limitations that prevent their implementation in clinical practice.

Clinical decision support (CDS) and computerized provider order entry have been shown to improve health care quality and safety, but may also generate previously unanticipated errors. We identified multiple CDS tools for platelet transfusion orders. In this study, we sought to evaluate and improve the effectiveness of those CDS tools while creating and testing a framework for future evaluation of other CDS tools.