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David S Thompson

Publications and source records attributed to David S Thompson.

3 recordsLinked to original sources

A guide to knowledge translation theory.

Despite calls over several decades for theory development, there remains no overarching knowledge-translation theory. However, a range of models and theoretical perspectives focused on narrower and related areas have been available for some time. We provide an overview of selected perspectives that we believe are particularly useful for developing testable and useful knowledge-translation interventions. In addition, we discuss adjuvant theories necessary to complement these perspectives. We draw from organizational innovation, health, and social sciences literature to illustrate the similarities and differences of various theoretical perspectives related to the knowledge-translation field.A variety of theoretical perspectives useful to knowledge translation exist. They are often spread across disciplinary boundaries, making them difficult to locate and use. Poor definitional clarity, discipline-specific terminology, and implicit assumptions often hinder the use of complementary perspectives. Health care environments are complex, and assessing the setting prior to selecting a theory should be the first step in knowledge-translation initiatives. Finding a fit between setting (context) and theory is important for knowledge-translation initiatives to succeed. Because one theory will not fit all contexts, it is helpful to understand and use several different theories. Although there are often barriers associated with combining theories from different disciplines, such obstacles can be overcome, and to do so will increase the likelihood that knowledge-translation initiatives will succeed.

Health Knowledge, Attitudes, Practice↗

Sepsis alert and diagnostic system: integrating clinical systems to enhance study coordinator efficiency.

Screening patients for clinical studies is time-consuming for researchers. Inefficiencies from human-based eligibility screening cause delay in scientific breakthroughs and are costly. We sought to determine the reliability of an automated computer-based real-time eligibility screening tool. A time-motion diary study was conducted in two university-based intensive care units using a cohort-controlled design. Time saved by automated eligibility screening and the positive and negative predictive values of the integrated eligibility screening system were compared with the gold standard of manual chart review. Sepsis Alert and Diagnostic System sensitivity and specificity were 82% and 95%, respectively. Positive and negative predictive values were 87.5% and 93%, respectively. During evaluation, Sepsis Alert and Diagnostic System saved a minimum of 137 minutes for the study coordinator. Sepsis Alert and Diagnostic System serves as a reliable tool for real-time eligibility screening in an intensive care unit setting. Time efficiencies through use of Sepsis Alert and Diagnostic System may translate into cost savings for funding agencies. The concept and methodology deployed in this study are applicable to any facility with electronic medical record capacity, as long as the data within that system are granular enough to support the specific query.

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