Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Apr 9;8(3):e10419.
doi: 10.1002/lrh2.10419. eCollection 2024 Jul.

Precision feedback: A conceptual model

Zach Landis-Lewis  1 , Allison M Janda  2 , Hana Chung  3 , Patrick Galante  1 , Yidan Cao  1 , Andrew E Krumm  1   3   4
Affiliations

Precision feedback: A conceptual model

Zach Landis-Lewis et al. Learn Health Syst. .

Abstract

Introduction: When performance data are provided as feedback to healthcare professionals, they may use it to significantly improve care quality. However, the question of how to provide effective feedback remains unanswered, as decades of evidence have produced a consistent pattern of effects-with wide variation. From a coaching perspective, feedback is often based on a learner's objectives and goals. Furthermore, when coaches provide feedback, it is ideally informed by their understanding of the learner's needs and motivation. We anticipate that a "coaching"-informed approach to feedback may improve its effectiveness in two ways. First, by aligning feedback with healthcare professionals' chosen goals and objectives, and second, by enabling large-scale feedback systems to use new types of data to learn what kind of performance information is motivating in general. Our objective is to propose a conceptual model of precision feedback to support these anticipated enhancements to feedback interventions.

Methods: We iteratively represented models of feedback's influence from theories of motivation and behavior change, visualization, and human-computer interaction. Through cycles of discussion and reflection, application to clinical examples, and software development, we implemented and refined the models in a software application to generate precision feedback messages from performance data for anesthesia providers.

Results: We propose that precision feedback is feedback that is prioritized according to its motivational potential for a specific recipient. We identified three factors that influence motivational potential: (1) the motivating information in a recipient's performance data, (2) the surprisingness of the motivating information, and (3) a recipient's preferences for motivating information and its visual display.

Conclusions: We propose a model of precision feedback that is aligned with leading theories of feedback interventions to support learning about the success of feedback interventions. We plan to evaluate this model in a randomized controlled trial of a precision feedback system that enhances feedback emails to anesthesia providers.

Keywords: audit and feedback; coaching; healthcare quality; learning; performance improvement.

PubMed Disclaimer

Conflict of interest statement

Zach Landis‐Lewis has received research support, paid to the University of Michigan, and related to this work, from the National Library of Medicine (K01 LM012528, R01LM013894). Allison M. Janda has received research support, paid to the University of Michigan and unrelated to this work, from Becton, Dickinson, and Company.

Figures

FIGURE 1
FIGURE 1
A conceptual model of precision feedback.
FIGURE 2
FIGURE 2
Precision feedback message types and examples.
FIGURE 3
FIGURE 3
Example precision‐feedback enhanced email to an anesthesia provider.
FIGURE 4
FIGURE 4
A one‐size‐fits‐n spectrum.
See this image and copyright information in PMC

References

    1. Ivers N, Jamtvedt G, Flottorp S, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;6:CD000259. - PMC - PubMed
    1. Ivers NM, Grimshaw JM, Jamtvedt G, et al. Growing literature, stagnant science? Systematic review, meta‐regression and cumulative analysis of audit and feedback interventions in health care. J Gen Intern Med. 2014;29(11):1534‐1541. - PMC - PubMed
    1. Brehaut JC, Colquhoun HL, Eva KW, et al. Practice feedback interventions: 15 suggestions for optimizing effectiveness. Ann Intern Med. 2016;164(6):435‐441. - PubMed
    1. Ivers NM, Sales A, Colquhoun H, et al. No more “business as usual” with audit and feedback interventions: towards an agenda for a reinvigorated intervention. Implement Sci. 2014;9(1):14. - PMC - PubMed
    1. Foy R, Skrypak M, Alderson S, et al. Revitalising audit and feedback to improve patient care. BMJ. 2020;368:27. Available from: https://www.bmj.com/content/368/bmj.m213 - PMC - PubMed

LinkOut - more resources