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Enabling positive practice improvement through data-driven feedback: A model for understanding how data and self-perception lead to practice change

NA-SM-Data Driven Feedback Model


Purpose: This article aims to identify the factors   that affect physicians' experiences of receiving practice data and to use   these data to develop a model describing how individuals interact with the   data. 

Methods: We   designed an interview guide to study physicians' perspectives on audit and   feedback. By intentional sampling, we recruited 15 physicians amongst gender   groups, types of practice (academic vs community), and durations of practice.   The interviews were conducted by a single author and transcribed without   identifiers. We then began with an open coding analysis for all of the   transcripts, and thereafter conducted axial coding to group the data into larger themes. 

Results:   Several attributes were identified as either enabling or counterproductive   attributes for participant improvement. The final proposed model identifies   different zones of engagement on the basis of both the individual   practitioner's growth mindset and the quality of the existing data system. In   the highest engagement zone, the mindset of the collective leadership is one   of growth. Systemic supports are in place, which potentiates learning that   may come from an individual motivated to use their own data. 

Conclusion: Our novel model depicts   the relationship between data feedback systems and individuals' mindsets   interact to augment or hinder clinical practice improvement. This model may   provide leaders with a framework to examine their academic and administrative   structures and how they might interface with performance feedback systems with clinicians.

Authors: Rana Kamhawy, Teresa M. Chan, Shawn Mondoux

Planning / Thinking

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