Journal of the American Medical Informatics Association : JAMIA
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To evaluate the data quality of ventilator settings recorded by respiratory therapists using a computer charting application and assess the impact of incorrect data on computerized ventilator management protocols. DESIGN An analysis of 29,054 charting events gathered over 12 months from 678 ventilated patients (1,736 ventilator days) in four intensive care units at a tertiary care hospital. ⋯ Even at institutions where manual charting of ventilator settings is performed well, automatic data collection can eliminate delays, improve charting efficiency, and reduce errors caused by incorrect data.
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J Am Med Inform Assoc · May 2007
Reevaluating recovery: perceived violations and preemptive interventions on emergency psychiatry rounds.
Contemporary error research suggests that the quest to eradicate error is misguided. Error commission, detection, and recovery are an integral part of cognitive work, even at the expert level. In collaborative workspaces, the perception of potential error is directly observable: workers discuss and respond to perceived violations of accepted practice norms. As perceived violations are captured and corrected preemptively, they do not fit Reason's widely accepted definition of error as "failure to achieve an intended outcome." However, perceived violations suggest the aversion of potential error, and consequently have implications for error prevention. This research aims to identify and describe perceived violations of the boundaries of accepted procedure in a psychiatric emergency department (PED), and how they are resolved in practice. ⋯ The analysis of perceived violations expands the data available for error analysis beyond occasional reported adverse events. These data are prospective: responses are captured in real time. This analysis supports a set of recommendations to improve the quality of care in the PED and other critical care contexts.
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J Am Med Inform Assoc · Mar 2007
Linking surveillance to action: incorporation of real-time regional data into a medical decision rule.
Broadly, to create a bidirectional communication link between public health surveillance and clinical practice. Specifically, to measure the impact of integrating public health surveillance data into an existing clinical prediction rule. We incorporate data about recent local trends in meningitis epidemiology into a prediction model differentiating aseptic from bacterial meningitis. ⋯ Epidemiological contextual information can improve the performance of a clinical prediction rule. We provide a methodological framework for leveraging regional surveillance data to improve medical decision-making.
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Our goal is to assess how clinical information from previous visits is used in the emergency department. We used detailed user audit logs to measure access to different data types. ⋯ Data were accessed less than half the time (up to 20% to 50%) even when the user was alerted to the presence of data. Our access rate indicates that health information exchange projects should be conservative in estimating how often shared data will be used and the wide breadth of data accessed indicates that although a clinical summary is likely to be useful, an ideal solution will supply a broad variety of data.
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J Am Med Inform Assoc · Jan 2007
ReviewMedication-related clinical decision support in computerized provider order entry systems: a review.
While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. ⋯ Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.