Audit and feedback: effects on professional practice.

IF 8.8 2区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Noah Ivers, Sharlini Yogasingam, Meagan Lacroix, Kevin A Brown, Jesmin Antony, Charlene Soobiah, Michelle Simeoni, Thomas A Willis, Jacob Crawshaw, Vivi Antonopoulou, Carly Meyer, Nathan M Solbak, Brenna J Murray, Emily-Ann Butler, Simone Lepage, Martina Giltenane, Mary D Carter, Guillaume Fontaine, Michael Sykes, Michael Halasy, Abdalla Bazazo, Samantha Seaton, Tony Canavan, Sarah Alderson, Catherine Reis, Stefanie Linklater, Aislinn Lalor, Ashley Fletcher, Emma Gearon, Hazel Jenkins, Jason A Wallis, Liesl Grobler, Lisa Beccaria, Sheila Cyril, Tomas Rozbroj, Jia Xi Han, Alice Xt Xu, Kelly Wu, Geneviève Rouleau, Maryam Shah, Kristin Konnyu, Heather Colquhoun, Justin Presseau, Denise O'Connor, Fabiana Lorencatto, Jeremy M Grimshaw
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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. 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引用次数: 0

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.

审核与反馈:对专业实践的影响。
背景:审计与反馈(A&F)是一种广泛使用的改进专业实践的策略。这得到了先前Cochrane综述和行为理论的支持,这些理论描述了当医疗保健专业人员的临床实践与理想目标不一致时,他们是如何被提示修改他们的实践的。然而,关于A&F对改善医疗保健实践的影响以及导致更大影响的A&F特征仍然存在不确定性。目的:评估A&F对医疗保健专业人员实践的影响,并检查可能解释A&F有效性变化的因素。检索方法:通过Cochrane有效实践和护理组织(EPOC)组信息科学家,我们更新了检索策略,纳入了2010年至2020年6月发表的研究。检索更新于2019年2月28日和2020年6月11日进行。我们检索了MEDLINE (Ovid)、Embase (Ovid)、CINAHL (EBSCO)、Cochrane图书馆、clinicaltrials.gov(所有日期至2020年6月)、WHO ICTRP(所有日期至2019年2月第3周,由于COVID-19大流行,没有2020年的信息)。更新的搜索和重复屏幕于2022年2月14日完成;符合纳入标准的研究包括在“等待分类的研究”部分。选择标准:随机试验,包括聚类试验和交叉和析因设计,在任何报告客观测量的卫生专业实践结果的试验组中,具有A&F(定义为在特定时期内临床表现的测量(审计)和向临床医生或临床团队提供结果数据(反馈))。数据收集和分析:在这篇更新的综述中,我们重新提取了每个研究组的数据,包括关于A&F如何进行和每次干预的行为改变技术的理论变量,以及包括偏倚风险在内的研究水平特征。对于每项研究,我们提取了A&F针对的每个医疗保健专业实践的结果数据。所有数据均由至少两名独立综述作者提取。对于包括有A&F组和没有A&F组的二元结果的研究,我们计算了风险差异(RDs)(两组之间完成期望练习的绝对差异)和优势比(ORs)。我们综合了所有试验的中位rd和四分位间距(IQRs)。然后,我们进行了荟萃分析,考虑了给定研究的多个结果,并通过有效样本量加权,使用报告的(或必要时输入的)集群内相关系数。接下来,我们探讨了基线表现、联合干预、目标行为和研究设计因素对A&F估计效果的作用。最后,我们进行了探索性元回归,以检验可能与A&F效应大小相关的预选变量:审计特征(指标数量、数据汇总);反馈交付(多模式、本地冠军、比较者性质、重复交付);以及支持行动的组成部分(促进、提供具体的改进计划、共同制定行动计划)。主要结果:我们纳入了292项研究,678组;133例(46%)具有低偏倚风险,41例(14%)不清楚,113例(39%)具有高偏倚风险。在低收入或中等收入国家进行了26项(9%)研究。在大多数研究中(237.81%),A&F的接受者是医生。研究中最常针对的专业实践是开处方(138项研究,47%)和安排测试(103项研究,35%)。大多数研究采用多方面的干预措施:最常见的联合干预措施是临床医生教育(377个研究组,56%)和提醒(100个研究组,15%)。在研究组中确定了48种独特的行为改变技术(平均值5.2,标准差2.8,范围1至29)。综合来自177项测试A&F与对照组的研究中测量专业实践的558个二分类结果显示,期望实践的绝对改善中位数为2.7%,IQR为0.0至8.6。对这些研究进行荟萃分析,考虑同一研究的多个结果,并通过有效样本量加权,考虑聚类,发现期望实践的平均绝对增长为6.2%(95%置信区间(CI) 4.1至8.2;中等确定性证据),OR为1.47 (95% CI 1.31至1.64;moderate-certainty证据)。针对处方和测试排序结果的预先计划亚组分析效果相似。较低的基线表现和增加的联合干预次数都与较大的干预效果相关。 meta回归比较了特定的A&F成分的存在与缺失,以探索异质性,考虑了基线表现和共同干预的数量,表明A&F效应在个人层面的数据比团队层面的数据更大,与顶级同行或基准进行比较,涉及与接受者有关系的当地冠军,使用互动方式而不仅仅是教学或仅仅是书面形式。并提供便利,以支持参与,并制定行动计划,以提高绩效。元回归没有发现审计中指标的数量、与所有同行的平均绩效比较或共同制定行动计划的显著影响。与预期相反,重复交付与较低的效应大小相关。正面试验的直接比较支持使用同伴比较而不是根本不进行比较,并在反馈中使用设计元素,以促进高优先级临床项目的识别和行动。作者的结论是:A&F可以有效地改善专业实践,但效果大小不一。A&F通常与联合干预措施一起实施,可产生叠加效应。当A&F被设计用来帮助接受者优先考虑并对高优先级的临床问题采取行动时,它可能是最有效的,并具有以下特征:针对卫生专业人员有很大改进空间的重要绩效指标(审计);2. 衡量个人的实践,而不是他们的团队或组织(审计);3. 涉及与接受者有现有关系的当地冠军(反馈);4. 包括多种互动方式,如口头和书面(反馈);5. 将绩效与顶级同行或基准进行比较(反馈);6. 促进参与反馈(行动);7. 具有可操作的计划和具体的改进建议(行动)。这些结论需要进一步的验证性研究;未来的研究应侧重于找出优化A&F干预措施有效性的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.60
自引率
2.40%
发文量
173
审稿时长
1-2 weeks
期刊介绍: The Cochrane Database of Systematic Reviews (CDSR) stands as the premier database for systematic reviews in healthcare. It comprises Cochrane Reviews, along with protocols for these reviews, editorials, and supplements. Owned and operated by Cochrane, a worldwide independent network of healthcare stakeholders, the CDSR (ISSN 1469-493X) encompasses a broad spectrum of health-related topics, including health services.
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