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Enabling Positive Practice Improvement through Data-Driven Growth: A model for understanding how data and self-perception lead to practice change
  • Rana Kamhawy,
  • Teresa Chan,
  • Shawn Mondoux
Rana Kamhawy
McMaster University

Corresponding Author:[email protected]

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Teresa Chan
McMaster University
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Shawn Mondoux
McMaster University
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Abstract

Purpose This paper aims to elucidate the factors that play into physicians’ experience of receiving practice data and to subsequently develop a model that describes how individuals may interact with the data they receive. Methods In a prior study, we conducted a needs analysis of 105 physicians in the Hamilton-Niagara area in order to understand which data metrics were most valuable to physicians. Using these results, 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 duration 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 environmental and personal 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 model shows how data feedback systems and individual growth-oriented mindsets interact to augment or hinder clinical practice improvement. This model provides important guidance to academic and administrative structures looking to develop appropriate performance feedback systems with clinicians.
24 Jun 2020Submitted to Journal of Evaluation in Clinical Practice
26 Jun 2020Submission Checks Completed
26 Jun 2020Assigned to Editor
28 Jun 2020Reviewer(s) Assigned
01 Sep 2020Review(s) Completed, Editorial Evaluation Pending
01 Sep 2020Editorial Decision: Revise Major
08 Sep 20201st Revision Received
10 Sep 2020Submission Checks Completed
10 Sep 2020Assigned to Editor
13 Sep 2020Review(s) Completed, Editorial Evaluation Pending
13 Sep 2020Editorial Decision: Revise Major
28 Sep 20202nd Revision Received
29 Sep 2020Submission Checks Completed
29 Sep 2020Assigned to Editor
02 Oct 2020Review(s) Completed, Editorial Evaluation Pending
02 Oct 2020Editorial Decision: Accept