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Ivers N, Yogasingam S, Lacroix M, Brown KA, Antony J, Soobiah C, Simeoni M, Willis TA, Crawshaw J, Antonopoulou V, Meyer C, Solbak NM, Murray BJ, Butler EA, Lepage S, Giltenane M, Carter MD, Fontaine G, Sykes M, Halasy M, Bazazo A, Seaton S, Canavan T, Alderson S, Reis C, Linklater S, Lalor A, Fletcher A, Gearon E, Jenkins H, Wallis JA, Grobler L, Beccaria L, Cyril S, Rozbroj T, Han JX, Xu AX, Wu K, Rouleau G, Shah M, Konnyu K, Colquhoun H, Presseau J, O'Connor D, Lorencatto F, Grimshaw JM. Audit and feedback: effects on professional practice. Cochrane Database Syst Rev 2025; 3:CD000259. [PMID: 40130784 PMCID: PMC11934852 DOI: 10.1002/14651858.cd000259.pub4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/26/2025]
Abstract
BACKGROUND Audit and feedback (A&F) is a widely used strategy to improve professional practice. This is supported by prior Cochrane reviews and behavioural theories describing how healthcare professionals are prompted to modify their practice when given data showing that their clinical practice is inconsistent with a desirable target. Yet there remains uncertainty regarding the effects of A&F on improving healthcare practice and the characteristics of A&F that lead to a greater impact. OBJECTIVES To assess the effects of A&F on the practice of healthcare professionals and to examine factors that may explain variation in the effectiveness of A&F. SEARCH METHODS With the Cochrane Effective Practice and Organisation of Care (EPOC) group information scientist, we updated our search strategy to include studies published from 2010 to June 2020. Search updates were performed on 28 February 2019 and 11 June 2020. We searched MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCO), the Cochrane Library, clinicaltrials.gov (all dates to June 2020), WHO ICTRP (all dates to February Week 3 2019, no information available in 2020 due to COVID-19 pandemic). An updated search and duplicate screen was completed on February 14, 2022; studies that met inclusion criteria are included in the 'Studies awaiting classification' section. SELECTION CRITERIA Randomised trials, including cluster-trials and cross-over and factorial designs, featuring A&F (defined as measurement of clinical performance over a specified period of time (audit) and provision of the resulting data to clinicians or clinical teams (feedback)) in any trial arm that reported objectively measured health professional practice outcomes. DATA COLLECTION AND ANALYSIS For this updated review, we re-extracted data for each study arm, including theory-informed variables regarding how the A&F was conducted and behaviour change techniques for each intervention, as well as study-level characteristics including risk of bias. For each study, we extracted outcome data for every healthcare professional practice targeted by A&F. All data were extracted by a minimum of two independent review authors. For studies with dichotomous outcomes that included arms with and without A&F, we calculated risk differences (RDs) (absolute difference between arms in proportion of desired practice completed) and also odds ratios (ORs). We synthesised the median RDs and interquartile ranges (IQRs) across all trials. We then conducted meta-analyses, accounting for multiple outcomes from a given study and weighted by effective sample size, using reported (or imputed, when necessary) intra-cluster correlation coefficients. Next, we explored the role of baseline performance, co-interventions, targeted behaviour, and study design factors on the estimated effects of A&F. Finally, we conducted exploratory meta-regressions to test preselected variables that might be associated with A&F effect size: characteristics of the audit (number of indicators, aggregation of data); delivery of the feedback (multi-modal format, local champion, nature of comparator, repeated delivery); and components supporting action (facilitation, provision of specific plans for improvement, co-development of action plans). MAIN RESULTS We included 292 studies with 678 arms; 133 (46%) had a low risk of bias, 41 (14%) unclear, and 113 (39%) had a high risk of bias. There were 26 (9%) studies conducted in low- or middle-income countries. In most studies (237, 81%), the recipients of A&F were physicians. Professional practices most commonly targeted in the studies were prescribing (138 studies, 47%) and test-ordering (103 studies, 35%). Most studies featured multifaceted interventions: the most common co-interventions were clinician education (377 study arms, 56%) and reminders (100 study arms, 15%). Forty-eight unique behaviour change techniques were identified within the study arms (mean 5.2, standard deviation 2.8, range 1 to 29). Synthesis of 558 dichotomous outcomes measuring professional practices from 177 studies testing A&F versus control revealed a median absolute improvement in desired practice of 2.7%, with an IQR of 0.0 to 8.6. Meta-analyses of these studies, accounting for multiple outcomes from the same study and weighting by effective sample size accounting for clustering, found a mean absolute increase in desired practice of 6.2% (95% confidence interval (CI) 4.1 to 8.2; moderate-certainty evidence) and an OR of 1.47 (95% CI 1.31 to 1.64; moderate-certainty evidence). Effects were similar for pre-planned subgroup analyses focused on prescribing and test-ordering outcomes. Lower baseline performance and increased number of co-interventions were both associated with larger intervention effects. Meta-regressions comparing the presence versus absence of specific A&F components to explore heterogeneity, accounting for baseline performance and number of co-interventions, suggested that A&F effects were greater with individual-recipient-level data rather than team-level data, comparing performance to top-peers or a benchmark, involving a local champion with whom the recipient had a relationship, using interactive modalities rather than just didactic or just written format, and with facilitation to support engagement, and action plans to improve performance. The meta-regressions did not find significant effects with the number of indicators in the audit, comparison to average performance of all peers, or co-development of action plans. Contrary to expectations, repeated delivery was associated with lower effect size. Direct comparisons from head-to-head trials support the use of peer-comparisons versus no comparison at all and the use of design elements in feedback that facilitate the identification and action of high-priority clinical items. AUTHORS' CONCLUSIONS A&F can be effective in improving professional practice, but effects vary in size. A&F is most often delivered along with co-interventions which can contribute additive effects. A&F may be most effective when designed to help recipients prioritise and take action on high-priority clinical issues and with the following characteristics: 1. targets important performance metrics where health professionals have substantial room for improvement (audit); 2. measures the individual recipient's practice, rather than their team or organisation (audit); 3. involves a local champion with an existing relationship with the recipient (feedback); 4. includes multiple, interactive modalities such as verbal and written (feedback); 5. compares performance to top peers or a benchmark (feedback); 6. facilitates engagement with the feedback (action); 7. features an actionable plan with specific advice for improvement (action). These conclusions require further confirmatory research; future research should focus on discerning ways to optimise the effectiveness of A&F interventions.
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Affiliation(s)
- Noah Ivers
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
| | | | | | - Kevin A Brown
- Public Health Ontario, 661 University Avenue, Suite 1701, Toronto, ON M5G1M1, Canada
| | - Jesmin Antony
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
| | | | | | - Thomas A Willis
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | | | - Vivi Antonopoulou
- Centre for Behaviour Change, Department of Clinical, Educational & Health Psychology, University College London (UCL), London WC1E 7HB, UK
- NIHR Policy Research Unit in Behavioural Science, Newcastle University, Newcastle upon Tyne NE2 4AX, UK
| | - Carly Meyer
- Centre for Behaviour Change, Department of Clinical, Educational & Health Psychology, University College London (UCL), London WC1E 7HB, UK
- NIHR Policy Research Unit in Behavioural Science, Newcastle University, Newcastle upon Tyne NE2 4AX, UK
| | - Nathan M Solbak
- Physician Learning Program, University of Calgary, Calgary, Canada
| | - Brenna J Murray
- Physician Learning Program, University of Calgary, Calgary, Canada
| | - Emily-Ann Butler
- Physician Learning Program, University of Calgary, Calgary, Canada
| | - Simone Lepage
- School of Nursing & Midwifery, University of Galway, Galway, Ireland
| | - Martina Giltenane
- School of Nursing & Midwifery, University of Galway, Galway, Ireland
- School of Nursing and Midwifery, Health Research Insitute, University of Limerick , Limerick , Ireland
| | - Mary D Carter
- Health & Community Sciences, University of Exeter, Exeter, UK
| | - Guillaume Fontaine
- Ingram School of Nursing, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, Montreal, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Kirby Institute, University of New South Wales, Sydney, Australia
| | | | - Michael Halasy
- Arizona School of Health Sciences, A.T. Still University, Mesa, Arizona, USA
| | - Abdalla Bazazo
- Northern Ontario School of Medicine (NOSM) University, Thunder Bay, ON, Canada
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
- Listowel Wingham Hospitals Alliance, Wingham, ON, Canada
| | | | - Tony Canavan
- Saolta University Health Care Group, University Hospital Galway, Galway, Ireland
| | | | | | | | - Aislinn Lalor
- Monash Department of Clinical Epidemiology, Cabrini Institute, School of Public Health and Preventive Medicine, Monash University, Malvern, Australia
- Rehabilitation, Ageing, and Independent Living (RAIL) Research Centre, Monash University, Melbourne, Australia
- Department of Occupational Therapy, Monash University, Melbourne, Australia
| | - Ashley Fletcher
- Monash Department of Clinical Epidemiology, Cabrini Institute and Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Malvern, Australia
| | - Emma Gearon
- Monash Department of Clinical Epidemiology, Cabrini Institute and Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Malvern, Australia
| | - Hazel Jenkins
- Department of Chiropractic , Macquarie University, Sydney, Australia
| | - Jason A Wallis
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Liesl Grobler
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Lisa Beccaria
- School of Nursing and Midwifery, Centre for Health Research , University of Southern Queensland , Toowoomba, Australia
| | - Sheila Cyril
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Tomas Rozbroj
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Jia Xi Han
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | | | | | - Geneviève Rouleau
- Nursing department, Université du Québec en Outaouais, Saint-Jérôme, Canada
| | - Maryam Shah
- Ottawa Hospital Research Institute, Ottawa, Canada
| | - Kristin Konnyu
- Aberdeen Centre for Evaluation, University of Aberdeen, Aberdeen, UK
| | - Heather Colquhoun
- Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada
| | | | - Denise O'Connor
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Fabiana Lorencatto
- Centre for Behaviour Change, Department of Clinical, Educational & Health Psychology, University College London (UCL), London WC1E 7HB, UK
- NIHR Policy Research Unit in Behavioural Science, Newcastle University, Newcastle upon Tyne NE2 4AX, UK
| | - Jeremy M Grimshaw
- Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
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