Evidence map›Paper›PMID 27412170›Full record

ArticleBMC health services research2016

Model depicting aspects of audit and feedback that impact physicians' acceptance of clinical performance feedback.

Velma L Payne, Sylvia J Hysong

Abstract read
In one paragraph

Article in BMC health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 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

32 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. A Systematic Review of Electronic Medical Record Driven Quality Measurement and Feedback Systems.International journal of environmental research and public health · 2022
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  8. Designing Communication Feedback Systems To Reduce Healthcare Providers' Implicit Biases In Patient Encounters.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
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  16. Battling Bias in Primary Care Encounters: Informatics Designs to Support Clinicians.Extended abstracts on Human factors in computing systems. CHI Conference · 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

2 authors.

Velma L PayneHouston Center for Innovations in Quality, Effectiveness & Safety, Michael E. DeBakey Veterans Affairs Medical Center, 2002 Holcombe Blvd (MEDVAMC 152), Houston, TX, 77030, USA. Velma.Payne@va.gov.
Sylvia J HysongHouston Center for Innovations in Quality, Effectiveness & Safety, Michael E. DeBakey Veterans Affairs Medical Center, 2002 Holcombe Blvd (MEDVAMC 152), Houston, TX, 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAudit and feedback (A&F) is a strategy that has been used in various disciplines for performance and quality improvement. There is limited research regarding medical professionals' acceptance of clinical-performance feedback and whether feedback impacts clinical practice. The objectives of our research were to (1) investigate aspects of A&F that impact physicians' acceptance of performance feedback; (2) determine actions physicians take when receiving feedback; and (3) determine if feedback impacts physicians' patient-management behavior.

methodsIn this qualitative study, we employed grounded theory methods to perform a secondary analysis of semi-structured interviews with 12 VA primary care physicians. We analyzed a subset of interview questions from the primary study, which aimed to determine how providers of high, low and moderately performing VA medical centers use performance feedback to maintain and improve quality of care, and determine perceived utility of performance feedback.

resultsBased on the themes emergent from our analysis and their observed relationships, we developed a model depicting aspects of the A&F process that impact feedback acceptance and physicians' patient-management behavior. The model is comprised of three core components - Reaction, Action and Impact - and depicts elements associated with feedback recipients' reaction to feedback, action taken when feedback is received, and physicians modifying their patient-management behavior. Feedback characteristics, the environment, external locus-of-control components, core values, emotion and the assessment process induce or deter reaction, action and impact. Feedback characteristics (content and timeliness), and the procedural justice of the assessment process (unjust penalties) impact feedback acceptance. External locus-of-control elements (financial incentives, competition), the environment (patient volume, time constraints) and emotion impact patient-management behavior. Receiving feedback generated intense emotion within physicians. The underlying source of the emotion was the assessment process, not the feedback. The emotional response impacted acceptance, impelled action or inaction, and impacted patient-management behavior. Emotion intensity was associated with type of action taken (defensive, proactive, retroactive).

conclusionsFeedback acceptance and impact have as much to do with the performance assessment process as it does the feedback. In order to enhance feedback acceptance and the impact of feedback, developers of clinical performance systems and feedback interventions should consider multiple design elements.

Indexed as

Attitude of Health PersonnelFeedbackPeer Review, Health CareQuality ImprovementHumansInterviews as TopicMedical AuditModels, TheoreticalPhysician-Patient RelationsPhysicians, Primary CareProfessional PracticeQualitative ResearchUnited StatesUnited States Department of Veterans AffairsAudit and feedbackFeedback acceptancePerformance improvement

Identifiers

PMID27412170
PMCPMC4944319

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.