AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
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Health messages are crucial to the field of public health in effecting behavior change, but little research is available to assist writers in composing the overall structure of a message. In order to develop software to assist non-expert message writers in constructing effective messages, the structure of existing health messages must be understood, and an appropriate method for analyzing health message structure developed. ⋯ A novel framework for characterizing health message structure and a method for analyzing messages appears to be reproducible.
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The aim of the present project was the development of a system supporting on-line Guideline-based training in Emergency Medicine. The developed Windows application is built on Visual C++ 6.0, in Greek language, and is based on widely accepted Emergency Medical Guidelines, employed to define the minimum standard of care provided to patients by the First Responders.
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AMIA Annu Symp Proc · Jan 2005
Web-based residency training program reviews influence applicants who use them.
Scutwork.com is an online, peer-based residency review system. We report preliminary results of an online survey designed to investigate the impact of Scutwork on the residency application process. Overall, 68% of respondents believe that the reviews influenced their decision-making and 91% would use Scutwork again. These results and others reported below suggest that Scutwork may play a significant role in the residency selection process.
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AMIA Annu Symp Proc · Jan 2005
Leveraging point-of-care clinician feedback to study barriers to guideline adherence.
Studies of barriers to guideline adherence have generally surveyed clinicians temporally remote from the clinical scenario in which recommendations were delivered, potentially adversely biasing clinician observations. The user interface of ATHENA DSS, a guideline-based decision support system for hypertension, includes a point-of-care feedback window that accepts clinician-user comments during the display of recommendations. Analysis of this feedback has revealed a number of intriguing patient, provider, and technical barriers to adherence collected during real-time system use.
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The intensive care unit (ICU) is an instance of a very dynamic health care setting where critically ill patients are being managed. It comprises of an extensive amount of communication amongst the role players, use of numerous information systems and operation of devices for monitoring and treatment purposes. ⋯ These pieces of the ICU workflow were used to develop a generalizable cognitive model to represent the intricate workflow in health care settings. The proposed model can be used to identify and characterize medical errors and also used for error prediction in practice.