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Individual users' attitudes and opinions help predict successful adoption of health information technology (HIT) into practice; however, little is known about pediatric users' acceptance of HIT for medical decision-making at the point of care.

Despite the potential for electronic health records to help providers coordinate care, the current marketplace has failed to provide adequate solutions. Using a simple framework, we describe a vision of information technology capabilities that could substantially improve four care coordination activities: identifying collaborators, contacting collaborators, collaborating, and monitoring. Collaborators can include any individual clinician, caregiver, or provider organization involved in care for a given patient. This vision can be used [...]

The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. Genetic data obtained for clinical purposes, as is true for all results of clinical tests, are expected to be included in patients' medical records. With this explosion of information, questions of what, when, where and how to incorporate genetic data into electronic health records (EHRs) have reached a [...]

To identify potential opportunities for drug repurposing by developing an automated approach to pre-screen the predicted proteomes of any organism against databases of known drug targets using only freely available resources.

Electronic health records (EHR) hold great promise for managing patient information in ways that improve healthcare delivery. Physicians differ, however, in their use of this health information technology (IT), and these differences are not well understood. The authors study the differences in individual physicians' EHR use patterns and identify perceptions of uncertainty as an important new variable in understanding EHR use.

To better understand the relationship between online health-seeking behaviors and in-world healthcare utilization (HU) by studies of online search and access activities before and after queries that pursue medical professionals and facilities.

To determine whether the knowledge contained in a rich corpus of local terms mapped to LOINC (Logical Observation Identifiers Names and Codes) could be leveraged to help map local terms from other institutions.

To assess the state of readiness for the adoption of paperless labeling among a nationally representative sample of pharmacies, including chain pharmacies, independent retail pharmacies, hospitals, and other rural or urban dispensing sites.

Natural language processing (NLP) applications typically use regular expressions that have been developed manually by human experts. Our goal is to automate both the creation and utilization of regular expressions in text classification.