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To determine the accuracy of self-reported information from patients and families for use in a disease surveillance system.

Electronic prescribing has improved the quality and safety of care. One barrier preventing widespread adoption is the potential detrimental impact on workflow. We used time-motion techniques to compare prescribing times at three ambulatory care sites that used paper-based prescribing, desktop, or laptop e-prescribing. An observer timed all prescriber (n = 27) and staff (n = 42) tasks performed during a 4-hour period. At the sites with optional e-prescribing >75% of [...]

This study sought to determine public opinion on alternatives to project-specific consent for use of their personal information for health research.

The purpose of this review is to organize various published conceptions of health numeracy and to discuss how health numeracy contributes to the productive use of quantitative information for health. We define health numeracy as the individual-level skills needed to understand and use quantitative health information, including basic computation skills, ability to use information in documents and non-text formats such as graphs, and ability to communicate orally. We also identify [...]

Inefficiencies in clinical trial data collection cause delays, increase costs, and may reduce clinician participation in medical research. In this proof-of-concept study, we examine the feasibility of using point-of-care data capture for both the medical record and clinical research in the setting of a working clinical trial. We hypothesized that by doing so, we could increase reuse of patient data, eliminate redundant data entry, and minimize disruption to clinic workflow.

To specify and identify disease and patient care processes represented by temporal patterns in clinical events and observations, and retrieve patient populations containing those patterns from clinical data repositories, in support of clinical research, outcomes studies, and quality assurance.

Part-of-speech tagging represents an important first step for most medical natural language processing (NLP) systems. The majority of current statistically-based POS taggers are trained using a general English corpus. Consequently, these systems perform poorly on medical text. Annotated medical corpora are difficult to develop because of the time and labor required. We investigated a heuristic-based sample selection method to minimize annotated corpus size for retraining a Maximum Entropy (ME) POS [...]

Parallel to the monumental problem of replacing paper-and-pen-based patient information management systems with electronic ones is the problem of evaluating the extent to which the change represents an improvement. All clinicians must grapple with this daunting challenge; those with little or no informatics expertise may be particularly surprised by the attendant difficulties. To do so successfully, they must be able to explicitly conceptualize the daily clinical work-a prerequisite for appreciating [...]