Evidence map›Paper›PMID 34404449›Full record

SynthesisImplementation science : IS2021

How well do critical care audit and feedback interventions adhere to best practice? Development and application of the REFLECT-52 evaluation tool.

Madison Foster, Justin Presseau, Eyal Podolsky, Lauralyn McIntyre, Maria Papoulias, Jamie C Brehaut

Registry-linked trialAbstract readSystematic Review
In one paragraph

Synthesis in Implementation science : IS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05920499 (The Effect of AUDIT and Feedback on Pneumococcal Vaccination Coverage in Adults At Risk in General Practice), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT05920499 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

The Effect of AUDIT and Feedback on Pneumococcal Vaccination Coverage in Adults At Risk in General Practice: a Cluster Randomized Trial

TypeinterventionalSponsorBert VaesRan2025 to 2026Enrolled36ConditionsPneumococcal InfectionsArmsAUDIT and Feedback
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025
    Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Madison FosterSchool of Epidemiology and Public Health, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada.
Justin PresseauSchool of Epidemiology and Public Health, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada.
Eyal PodolskySchool of Epidemiology and Public Health, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada.
Lauralyn McIntyreSchool of Epidemiology and Public Health, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada.
Maria PapouliasOttawa Hospital Research Institute, Clinical Epidemiology Program, The Ottawa Hospital, General Campus, 501 Smyth Road, Centre for Practice Changing Research, Box 201B, Ottawa, ON, K1H 8L6, Canada.
Jamie C BrehautSchool of Epidemiology and Public Health, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada. jbrehaut@ohri.ca.ORCID 0000-0002-4213-1143

Funding

CIHR PJT156031
6 · The paper itself

Abstract

backgroundHealthcare Audit and Feedback (A&F) interventions have been shown to be an effective means of changing healthcare professional behavior, but work is required to optimize them, as evidence suggests that A&F interventions are not improving over time. Recent published guidance has suggested an initial set of best practices that may help to increase intervention effectiveness, which focus on the "Nature of the desired action," "Nature of the data available for feedback," "Feedback display," and "Delivering the feedback intervention." We aimed to develop a generalizable evaluation tool that can be used to assess whether A&F interventions conform to these suggestions for best practice and conducted initial testing of the tool through application to a sample of critical care A&F interventions.

methodsWe used a consensus-based approach to develop an evaluation tool from published guidance and subsequently applied the tool to conduct a secondary analysis of A&F interventions. To start, the 15 suggestions for improved feedback interventions published by Brehaut et al. were deconstructed into rateable items. Items were developed through iterative consensus meetings among researchers. These items were then piloted on 12 A&F studies (two reviewers met for consensus each time after independently applying the tool to four A&F intervention studies). After each consensus meeting, items were modified to improve clarity and specificity, and to help increase the reliability between coders. We then assessed the conformity to best practices of 17 critical care A&F interventions, sourced from a systematic review of A&F interventions on provider ordering of laboratory tests and transfusions in the critical care setting. Data for each criteria item was extracted by one coder and confirmed by a second; results were then aggregated and presented graphically or in a table and described narratively.

resultsIn total, 52 criteria items were developed (38 ratable items and 14 descriptive items). Eight studies targeted lab test ordering behaviors, and 10 studies targeted blood transfusion ordering. Items focused on specifying the "Nature of the Desired Action" were adhered to most commonly-feedback was often presented in the context of an external priority (13/17), showed or described a discrepancy in performance (14/17), and in all cases it was reasonable for the recipients to be responsible for the change in behavior (17/17). Items focused on the "Nature of the Data Available for Feedback" were adhered to less often-only some interventions provided individual (5/17) or patient-level data (5/17), and few included aspirational comparators (2/17), or justifications for specificity of feedback (4/17), choice of comparator (0/9) or the interval between reports (3/13). Items focused on the "Nature of the Feedback Display" were reported poorly-just under half of interventions reported providing feedback in more than one way (8/17) and interventions rarely included pilot-testing of the feedback (1/17 unclear) or presentation of a visual display and summary message in close proximity of each other (1/13). Items focused on "Delivering the Feedback Intervention" were also poorly reported-feedback rarely reported use of barrier/enabler assessments (0/17), involved target members in the development of the feedback (0/17), or involved explicit design to be received and discussed in a social context (3/17); however, most interventions clearly indicated who was providing the feedback (11/17), involved a facilitator (8/12) or involved engaging in self-assessment around the target behavior prior to receipt of feedback (12/17).

conclusionsMany of the theory-informed best practice items were not consistently applied in critical care and can suggest clear ways to improve interventions. Standardized reporting of detailed intervention descriptions and feedback templates may also help to further advance research in this field. The 52-item tool can serve as a basis for reliably assessing concordance with best practice guidance in existing A&F interventions trialed in other healthcare settings, and could be used to inform future A&F intervention development.

trial registrationNot applicable.

Indexed as

Critical CareHealth PersonnelDelivery of Health CareFeedbackHumansReproducibility of ResultsA&FAuditCritical careEvaluation toolFeedback

Identifiers

PMID34404449
PMCPMC8369748

What OpenQuestion holds

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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.