ArticleImplementation science : IS2018
Mental models of audit and feedback in primary care settings.
Article in Implementation science : IS, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 22 citations in OpenAlex.
- Do medical specialists accept claims-based Audit and Feedback for quality improvement? A focus group study.BMJ open · 2024Article
- Study protocol: maintaining preventive care during public health emergencies through effective coordination.Implementation science communications · 2023Article
- A structured approach to applying systems analysis methods for examining implementation mechanisms.Implementation science communications · 2023Article
- Unpacking the intention to action gap: a qualitative study understanding how physicians engage with audit and feedback.Implementation science : IS · 2021Article
- The Importance of Mental Models in Implementation Science.Frontiers in public health · 2021Review
- Overview of Mental Models research using bibliometric indicators.Cognitive processing · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundAudit 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.
methodsWe 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.
resultsWe 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.
conclusionsResults 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.