Journal of biomedical informatics
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Randomized Controlled Trial
Showing Your Work: Impact of annotating electronic prescriptions with decision support results.
e-Prescribing systems with decision support do not routinely communicate an adequate amount of information regarding the prescribers' decision to pharmacists. To address this communication gap in the e-prescribing process, we implemented a system called Show Your Work (SYW) that appends alerts and override comments to e-prescriptions generated by an e-prescribing system. To assess the quantitative impact of this system, we conducted a randomized, double-blinded, controlled study to assess pharmacy callback rates and types, and to uncover any unintended consequences of the annotations. ⋯ Most respondents agreed (69%) that SYW favorably impacted callbacks--especially with pediatric prescriptions (82%). Comments suggested that SYW increased callbacks where necessary and decreased them in other situations, but did not contribute to unnecessary callbacks. These findings support the continued and potentially expanded use of SYW by e-prescribing systems to enhance communication with pharmacists.
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Simulators for honing procedural skills (such as surgical skills and central venous catheter placement) have proven to be valuable tools for medical educators and students. While such simulations represent an effective paradigm in surgical education, there is an opportunity to add a layer of cognitive exercises to these basic simulations that can facilitate robust skill learning in residents. This paper describes a controlled methodology, inspired by neuropsychological assessment tasks and embodied cognition, to develop cognitive simulators for laparoscopic surgery. ⋯ It is independent of the types of sensors, simulation environment and feedback mechanisms that the simulators use. A proof of concept of the framework is provided through developing a simulator that includes cognitive variations to a basic psychomotor task. The results of two pilot studies are presented that show the validity of the methodology in providing an effective evaluation and learning environments for surgeons.
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Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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Decision-support systems, and specifically rule-based clinical reminders, are becoming common in medical practice. Despite their potential to improve clinical outcomes, physicians do not always use information from these systems. Concepts from the cognitive engineering literature on users' responses to warning systems may help to define physicians' responses to reminders. ⋯ We suggest statistical measures to estimate these responses and empirically demonstrate them on data from a large-scale clinical reminder system for secondary prevention of cardiovascular diseases. There was evidence for Compliance, probably since the physicians found the reminders informative, but not for Reliance, in line with the notion that Compliance and Reliance are two distinct types of trust in information from decision-support systems. Our research supports the notion that CDSS can promote closing the treatment gap and improve physicians' adherence to guidelines.
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Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. ⋯ The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.