Literature DB >> 27714397

Comparing Graphical Formats for Feedback of Clinical Practice Data. A Multicenter Study among Anesthesiologists in France.

Aurelie Petit-Monéger1, Florence Saillour-Glénisson, Karine Nouette-Gaulain, Vianney Jouhet, Louis-Rachid Salmi.   

Abstract

OBJECTIVES: Although graphical formats used to feedback clinical practice data may have an important impact, the most effective formats remain unknown. Using prevention of postoperative nausea and vomiting by anesthesiologists as an application, the objective of this study was to assess which graphical formats for feedback of clinical practice data are the most incentive to change practice.
METHODS: We conducted a multicenter cross-sectional study among anesthesiologists randomized in two groups between March and June 2014. Each anesthesiologist assessed 15 graphical formats displaying an indicator of either prescription conformity or prescription effectiveness. Graphical formats varied by: type of graph (bar charts, linear sliders, or pictographs), presence or not of a target to reach, presence or not of a contrast between a hypothetical physician and his / her team, direction of the difference between the physician and his / her team, and restitution or not of the quality indicator evolution over the previous six months. The primary outcome was a numerical scale score expressing the anesthesiologists' motivation to change his / her practice (ranging from 1 to 10 points). A linear mixed model was fitted to explain variation in motivation.
RESULTS: Sixty-six anesthesiologists assessed the conformity indicator and 67 assessed the effectiveness indicator. Factors associated with an increased motivation to change practice were: (i) presence of a clearly defined target to reach (conformity: β = 0.24 points, p = 0.0046; effectiveness: β = 1.11 points, p < 0.0001); (ii) contrast between the physician and his / her team (conformity: β = 0.38 points, p < 0.0001; effectiveness: β = 0.33 points, p = 0.0021); (iii) better results for the team than for the physician (conformity: β = 0.65 points, p < 0.0001; effectiveness β = 1.16 points, p < 0.0001). For the effectiveness indicator, anesthesiologists were more motivated to change practice with bar charts (β = 0.24 points, p = 0.0447) and pictographs (β = 0.45 points, p = 0.0001) than with linear sliders.
CONCLUSIONS: Graphs associated with a defined target to reach should be preferred to deliver feedback, especially bar graphs or pictographs for indicators which are more complex to represent such as effectiveness indicators. Anesthesiologists are also more motivated to change practice when graphs report contrasted data between the physician and his / her team and a lower conformity or effectiveness for the physician than for his / her team.

Entities:  

Keywords:  Feedback; anesthesia; clinical practice; graphical formats; quality of care

Mesh:

Year:  2016        PMID: 27714397     DOI: 10.3414/ME15-01-0163

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  4 in total

1.  What was visualized? A method for describing content of performance summary displays in feedback interventions.

Authors:  Dahee Lee; Veena Panicker; Colin Gross; Jessica Zhang; Zach Landis-Lewis
Journal:  BMC Med Res Methodol       Date:  2020-04-23       Impact factor: 4.615

2.  A Scalable Service to Improve Health Care Quality Through Precision Audit and Feedback: Proposal for a Randomized Controlled Trial.

Authors:  Zach Landis-Lewis; Allen Flynn; Allison Janda; Nirav Shah
Journal:  JMIR Res Protoc       Date:  2022-05-10

3.  Development and validation of hospital information system-generated indicators of the appropriateness of oral anticoagulant prescriptions in hospitalised adults: the PACHA study protocol.

Authors:  Aurélie Petit-Monéger; Frantz Thiessard; Vianney Jouhet; Pernelle Noize; Driss Berdaï; Marion Kret; Rémi Sitta; Louis-Rachid Salmi; Florence Saillour-Glénisson
Journal:  BMJ Open       Date:  2017-08-31       Impact factor: 2.692

Review 4.  Optimizing lung cancer MDT data for maximum clinical impact-a scoping literature review.

Authors:  Emily Stone; Nicole Rankin; David Currow; Kwun M Fong; Jane L Phillips; Tim Shaw
Journal:  Transl Lung Cancer Res       Date:  2020-08
  4 in total

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