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To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs.

HIV-1-infected individuals with higher viral set points progress to AIDS more rapidly than those with lower set points. Predicting viral set point early following infection can contribute to our understanding of early control of HIV-1 replication, to predicting long-term clinical outcomes, and to the choice of optimal therapeutic regimens.

To identify predictors of nurses' acceptance of bar coded medication administration (BCMA).

The demographic and practice-related characteristics of physicians who use social networking websites, portable devices to access the internet, email to communicate with patients, podcasts, widgets, RSS feeds, and blogging were investigated. Logistic regression was used to analyze a survey of US primary care physicians, pediatricians, obstetrician/gynecologists, and dermatologists (N=1750). Reported technology use during the last 6 months ranged from 80.6% using a portable device to access the internet to 12.9% [...]

Many public health agencies monitor population health using syndromic surveillance, generally employing information from emergency department (ED) visit records. When combined with other information, objective evidence of fever may enhance the accuracy with which surveillance systems detect syndromes of interest, such as influenza-like illness. This study found that patient chief complaint of self-reported fever was more readily available in ED records than measured temperature and that the majority of patients [...]

Postoperative nausea and vomiting (PONV) is a frequent complication in patients undergoing ambulatory surgery, with an incidence of 20%-65%. A predictive model can be utilized for decision support and feedback for practitioner practice improvement. The goal of this study was to develop a better model to predict the patient's risk for PONV by incorporating both non-modifiable patient characteristics and modifiable practitioner-specific anesthetic practices.

To determine the effects of a personal health record (PHR)-linked medications module on medication accuracy and safety.

To develop a computerized clinical decision support system (CDSS) for cervical cancer screening that can interpret free-text Papanicolaou (Pap) reports.

This paper describes a natural language processing system for the task of pneumonia identification. Based on the information extracted from the narrative reports associated with a patient, the task is to identify whether or not the patient is positive for pneumonia.

Today's clinical research institutions provide tools for researchers to query their data warehouses for counts of patients. To protect patient privacy, counts are perturbed before reporting; this compromises their utility for increased privacy. The goal of this study is to extend current query answer systems to guarantee a quantifiable level of privacy and allow users to tailor perturbations to maximize the usefulness according to their needs.