Evidence map›Paper›PMID 31014352›Full record

ReviewImplementation science : IS2019

Clinical performance comparators in audit and feedback: a review of theory and evidence.

Wouter T Gude, Benjamin Brown, Sabine N van der Veer, Heather L Colquhoun, Noah M Ivers, Jamie C Brehaut, Zach Landis-Lewis, Christopher J Armitage, Nicolette F de Keizer, Niels Peek

Abstract readReview
In one paragraph

Review in Implementation science : IS, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 5 pooled it
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  5. Systematic review and narrative synthesis of computerized audit and feedback systems in healthcare.Journal of the American Medical Informatics Association : JAMIA · 2022
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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

10 authors.

Wouter T GudeDepartment of Medical Informatics, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands. w.t.gude@amc.uva.nl.ORCID 0000-0001-7941-5281
Benjamin BrownCentre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
Sabine N van der VeerNIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
Heather L ColquhounOccupational Science and Occupational Therapy, University of Toronto, Toronto, Ontario, Canada.
Noah M IversFamily and Community Medicine, Women's College Hospital, University of Toronto, Toronto, Ontario, Canada.
Jamie C BrehautClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Zach Landis-LewisCenter for Health Informatics for the Underserved, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
Christopher J ArmitageNIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
Nicolette F de KeizerDepartment of Medical Informatics, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands.
Niels PeekNIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.

Funding

A knowledge-based message tailoring systemK01LM012528 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANDIS-LEWIS, ZACHARY · 2017 to 2019
$523k
Department of HealthMedical Research Council MC_PC_13042NLM NIH HHS K01 LM012528
6 · The paper itself

Abstract

backgroundAudit and feedback (A&F) is a common quality improvement strategy with highly variable effects on patient care. It is unclear how A&F effectiveness can be maximised. Since the core mechanism of action of A&F depends on drawing attention to a discrepancy between actual and desired performance, we aimed to understand current and best practices in the choice of performance comparator.

methodsWe described current choices for performance comparators by conducting a secondary review of randomised trials of A&F interventions and identifying the associated mechanisms that might have implications for effective A&F by reviewing theories and empirical studies from a recent qualitative evidence synthesis.

resultsWe found across 146 trials that feedback recipients' performance was most frequently compared against the performance of others (benchmarks; 60.3%). Other comparators included recipients' own performance over time (trends; 9.6%) and target standards (explicit targets; 11.0%), and 13% of trials used a combination of these options. In studies featuring benchmarks, 42% compared against mean performance. Eight (5.5%) trials provided a rationale for using a specific comparator. We distilled mechanisms of each comparator from 12 behavioural theories, 5 randomised trials, and 42 qualitative A&F studies.

conclusionClinical performance comparators in published literature were poorly informed by theory and did not explicitly account for mechanisms reported in qualitative studies. Based on our review, we argue that there is considerable opportunity to improve the design of performance comparators by (1) providing tailored comparisons rather than benchmarking everyone against the mean, (2) limiting the amount of comparators being displayed while providing more comparative information upon request to balance the feedback's credibility and actionability, (3) providing performance trends but not trends alone, and (4) encouraging feedback recipients to set personal, explicit targets guided by relevant information.

Indexed as

Evidence-Based PracticeFormative FeedbackModels, TheoreticalProcess Assessment, Health CareBenchmarkingClinical AuditHealth Services ResearchHumansQuality ImprovementRandomized Controlled Trials as TopicBenchmarkingFeedbackMedical auditQuality improvement

Identifiers

PMID31014352
PMCPMC6480497

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.