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Catalog
Guidelines Development Workshop
Session 1: Overview of Clinical Practice Guideline ...
Session 1: Overview of Clinical Practice Guidelines including scope, developing key questions, and inclusion/exclusion criteria for systematic literature searches
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Video Transcription
Video Summary
In this video, Jonathan Treadwell and Stacey Ewell from ECRI present an evidence workshop for the American Association of Clinical Endocrinology. They provide an overview of evidence assessment in clinical practice guidelines. Jonathan Treadwell introduces ECRI as a non-profit organization focused on patient safety, evidence-based medicine, and technology decision support. He explains that clinical practice guidelines are statements that include recommendations based on a systematic review of evidence and an assessment of the benefits and harms of alternative care options. Treadwell discusses the continuum of evidence quality and the challenges of setting the bar for inclusion in guideline development. He emphasizes the importance of structured processes and transparency in decision-making to minimize bias. Stacey Ewell then discusses the scoping of systematic reviews, the development of key questions, and the planning and conducting of systematic reviews. She provides examples of how key questions can be refined using frameworks like PCOTS (population, interventions, comparison, outcomes, timing, and setting) . Ewell highlights the importance of clear and focused key questions to guide literature searches, study selection, data abstraction, and evidence synthesis. The video concludes with an overview of the inclusion and exclusion criteria, and the potential challenges of conducting systematic reviews. Overall, the video provides a comprehensive introduction to evidence assessment in clinical practice guidelines, with a focus on scoping, key question development, and systematic review processes.
Keywords
evidence workshop
clinical practice guidelines
patient safety
evidence-based medicine
systematic reviews
key questions
PCOTS framework
literature searches
data abstraction
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