Publication:
Data and Lifelong Learning Protocol: Understanding Cultural Barriers and Facilitators to Using Clinical Performance Data to Support Continuing Professional Development.

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Date

2018-10

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Research Projects

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Abstract

Abstract: Continuing professional development (CPD) can support delivery of high-quality care, but may not be optimized until we can understand cultural barriers and facilitators, especially as innovations emerge. Lifelong learning (LLL), linked with quality improvement, competence, and professionalism, is a core competency in medical education. The purpose of this study is to examine cultural factors (individual, organizational, and systemic) that influence CPD and specifically the use of clinical data to inform LLL and CPD activities. This mixed-method study will examine the perceptions of two learner groups (psychiatrists and general surgeons) in three phases: (1) a survey to understand the relationship between data-informed learning and orientation to LLL; (2) semistructured interviews using purposive and maximum variation sampling techniques to identify individual-, organizational-, and system-level barriers and facilitators to engaging in data-informed LLL to support practice change; and (3) a document analysis of legislation, policies, and procedures related to the access and the use of clinical data for performance improvement in CPD. We obtained research ethics approval from the University Health Network in Toronto, Ontario, Canada. By exploring two distinct learner groups, we will identify contextual features that may inform what educators should consider when conceptualizing and designing CPD activities and what initial actions need to be taken before CPD activities can be optimized. This study will lead to the development of a framework reflective of barriers and facilitators that can be implemented when planning to use data in CPD activities to support data adoption for LLL.

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Continuing Professional Development (CPD), Continuing Education, Medical education, Lifelong learning, Self-directed learning, Data-informed learning, Data-driven learning

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