Mental models of audit and feedback in primary care settings

Sylvia J. Hysong, Kristen Smitham, Richard SoRelle, Amber Amspoker, Ashley M. Hughes, Paul Haidet

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Background: Audit and feedback has been shown to be instrumental in improving quality of care, particularly in outpatient settings. The mental model individuals and organizations hold regarding audit and feedback can moderate its effectiveness, yet this has received limited study in the quality improvement literature. In this study we sought to uncover patterns in mental models of current feedback practices within high- and low-performing healthcare facilities. Methods: We purposively sampled 16 geographically dispersed VA hospitals based on high and low performance on a set of chronic and preventive care measures. We interviewed up to 4 personnel from each location (n = 48) to determine the facility's receptivity to audit and feedback practices. Interview transcripts were analyzed via content and framework analysis to identify emergent themes. Results: We found high variability in the mental models of audit and feedback, which we organized into positive and negative themes. We were unable to associate mental models of audit and feedback with clinical performance due to high variance in facility performance over time. Positive mental models exhibit perceived utility of audit and feedback practices in improving performance; whereas, negative mental models did not. Conclusions: Results speak to the variability of mental models of feedback, highlighting how facilities perceive current audit and feedback practices. Findings are consistent with prior research in that variability in feedback mental models is associated with lower performance.; Future research should seek to empirically link mental models revealed in this paper to high and low levels of clinical performance.

Original languageEnglish (US)
Article number73
JournalImplementation Science
Issue number1
StatePublished - May 30 2018

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Health Informatics
  • Public Health, Environmental and Occupational Health


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