Revitalising audit and feedback to improve patient care

Healthcare systems face challenges in tackling variations in patient care and outcomes. Audit and feedback aim to improve patient care by reviewing clinical performance against explicit standards and directing action towards areas not meeting those standards. It is a widely used foundational component of quality improvement, included in around 60 national clinical audit programmes in the United Kingdom. Ironically, there is currently a gap between what audit and feedback can achieve and what they actually deliver, whether led locally or nationally. Several national audits have been successful in driving improvement and reducing variations in care, such as for stroke and lung cancer, but progress is also slower than hoped for in other aspects of care (table 1). Audit and feedback have a chequered past.6 Clinicians might feel threatened rather than supported by top-down feedback and rightly question whether rewards outweigh efforts invested in poorly designed audit. Healthcare organisations have limited resources to support and act on audit and feedback. Dysfunctional clinical and managerial relationships undermine effective responses to feedback, particularly when it is not clearly part of an integrated approach to quality assurance and improvement. Unsurprisingly, the full potential of audit and feedback has not been realised

Theories of behaviour change synthesised into a set of theoretical groupings: Introducing a thematic series on the Theoretical Domains Framework

Behaviour change is key to increasing the uptake of evidence into healthcare practice. Designing behaviour-change interventions first requires problem analysis, ideally informed by theory. Yet the large number of partly overlapping theories of behaviour makes it difficult to select the most appropriate theory. The need for an overarching theoretical framework of behaviour change was addressed in research in which 128 explanatory constructs from 33 theories of behaviour were identified and grouped. The resulting Theoretical Domains Framework (TDF) appears to be a helpful basis for investigating implementation problems. Research groups in several countries have conducted TDF-based studies. It seems timely to bring together the experience of these teams in a thematic series to demonstrate further applications and to report key developments. This overview article describes the TDF, provides a brief critique of the framework, and introduces this thematic series. In a brief review to assess the extent of TDF-based research, we identified 133 papers that cite the framework. Of these, 17 used the TDF as the basis for empirical studies to explore health professionals’ behaviour. The identified papers provide evidence of the impact of the TDF on implementation research. Two major strengths of the framework are its theoretical coverage and its capacity to elicit beliefs that could signify key mediators of behaviour change. The TDF provides a useful conceptual basis for assessing implementation problems, designing interventions to enhance healthcare practice, and understanding behaviour-change processes. We discuss limitations and research challenges and introduce papers in this series

Establishing a primary care audit and feedback implementation laboratory: a consensus study

Background: There is a significant variation among individual primary care providers in prescribing of potentially problematic, low-value medicines which cause avoidable patient harm. Audit and feedback is generally effective at improving prescribing. However, progress has been hindered by research waste, leading to unanswered questions about how to include audit and feedback for specific problems and circumstances. Trials of different ways of providing audit and feedback in implementation laboratories have been proposed as a way of improving population healthcare while generating robust evidence on feedback effects. However, there is limited experience in their design and delivery. Aim: To explore priorities, feasibility, and ethical challenges of establishing a primary care prescribing audit and feedback implementation laboratory. Design and setting: Two-stage Delphi consensus process involving primary care pharmacy leads, audit and feedback researchers, and patient and public. Method: Participants initially scored statements relating to priorities, feasibility, and ethical considerations for an implementation laboratory. These covered current feedback practice, priority topics for feedback, usefulness of feedback in improving prescribing and different types of prescribing data, acceptability and desirability of different organization levels of randomization, options for trial consent, different methods of delivering feedback, and interest in finding out how effective different ways of presenting feedback would be. After receiving collated results, participants then scored the items again. The consensus was defined using the GRADE criteria. The results were analyzed by group and overall score. Results: Fourteen participants reached consensus for 38 out of 55 statements. Addressing antibiotic and opioid prescribing emerged as the highest priorities for action. The panel supported statements around addressing highpriority prescribing issues, taking an “opt-out” approach to practice consent if waiving consent was not permitted, and randomizing at lower rather than higher organizational levels. Participants supported patient-level prescribing data and further research evaluating most of the different feedback methods we presented them with. Conclusions: There is a good level of support for evaluating a wide range of potential enhancements to improve the effects of feedback on prescribing. The successful design and delivery of a primary care audit and feedback implementation laboratory depend on identifying shared priorities and addressing practical and ethical considerations

An audit and feedback intervention for reducing antibiotic prescribing in general dental practice:the RAPiD Cluster Randomised Controlled Trial

Acknowledgments: We thank the TRiaDS Research Methodology Group, including Irene Black, Debbie Bonetti, Heather Cassie, Martin Eccles, Sandra Eldridge, Jill J. Francis, Jeremy M. Grimshaw, Lorna Macpherson, Lorna McKee, Susan Michie, Nigel Pitts, Derek Richards, Douglas Stirling, Colin Tilley, Carole Torgerson, Shaun Treweek, Luke Vale, and Alan Walker for their guidance and contribution to the design and development of the study. We also thank Maria Prior for overseeing the running of the study, drafting of the published protocol, and her contribution to the design and analysis of the process evaluation. Thanks are also extended to Jill Farnham, Jenny Eades, Sarah Blackburn, and Lorna Barnsley for providing invaluable administrative support for this study. The views expressed in this article are those of the authors and may not reflect those of the funder. Funding: This study was conducted as part of the TRiaDS programme of implementation research which is funded by NHS Education for Scotland (NES). The Health Services Research Unit which is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates supported the study. The funder had no influence over the design, conduct, analysis and write up of the study. Data Availability: Researchers can request to access the data from the Information Services Division of NHS National Services Scotland http://www.isdscotland.org/. Some restrictions may apply for the protection of privacy and appropriate usage of the data.Peer reviewedPublisher PD

Application of theory to enhance audit and feedback interventions to increase the uptake of evidence-based transfusion practice: an intervention development protocol

Background: Audits of blood transfusion demonstrate around 20% transfusions are outside national recommendations and guidelines. Audit and feedback is a widely used quality improvement intervention but effects on clinical practice are variable, suggesting potential for enhancement. Behavioural theory, theoretical frameworks of behaviour change and behaviour change techniques provide systematic processes to enhance intervention. This study is part of a larger programme of work to promote the uptake of evidence-based transfusion practice. Objectives: The objectives of this study are to design two theoretically enhanced audit and feedback interventions; one focused on content and one on delivery, and investigate the feasibility and acceptability. Methods: Study A (Content): A coding framework based on current evidence regarding audit and feedback, and behaviour change theory and frameworks will be developed and applied as part of a structured content analysis to specify the key components of existing feedback documents. Prototype feedback documents with enhanced content and also a protocol, describing principles for enhancing feedback content, will be developed. Study B (Delivery): Individual semi-structured interviews with healthcare professionals and observations of team meetings in four hospitals will be used to specify, and identify views about, current audit and feedback practice. Interviews will be based on a topic guide developed using the Theoretical Domains Framework and the Consolidated Framework for Implementation Research. Analysis of transcripts based on these frameworks will form the evidence base for developing a protocol describing an enhanced intervention that focuses on feedback delivery. Study C (Feasibility and Acceptability): Enhanced interventions will be piloted in four hospitals. Semi-structured interviews, questionnaires and observations will be used to assess feasibility and acceptability. Discussion: This intervention development work reflects the UK Medical Research Council’s guidance on development of complex interventions, which emphasises the importance of a robust theoretical basis for intervention design and recommends systematic assessment of feasibility and acceptability prior to taking interventions to evaluation in a full-scale randomised study. The work-up includes specification of current practice so that, in the trials to be conducted later in this programme, there will be a clear distinction between the control (usual practice) conditions and the interventions to be evaluated

Designing and undertaking randomised implementation trials: guide for researchers

Implementation science is the study of methods to promote the systematic uptake of evidence based interventions into practice and policy to improve health. Despite the need for high quality evidence from implementation research, randomised trials of implementation strategies often have serious limitations. These limitations include high risks of bias, limited use of theory, a lack of standard terminology to describe implementation strategies, narrowly focused implementation outcomes, and poor reporting. This paper aims to improve the evidence base in implementation science by providing guidance on the development, conduct, and reporting of randomised trials of implementation strategies. Established randomised trial methods from seminal texts and recent developments in implementation science were consolidated by an international group of researchers, health policy makers, and practitioners. This article provides guidance on the key components of randomised trials of implementation strategies, including articulation of trial aims, trial recruitment and retention strategies, randomised design selection, use of implementation science theory and frameworks, measures, sample size calculations, ethical review, and trial reporting. It also focuses on topics requiring special consideration or adaptation for implementation trials. We propose this guide as a resource for researchers, healthcare and public health policy makers or practitioners, research funders, and journal editors with the goal of advancing rigorous conduct and reporting of randomised trials of implementation strategies

The co-development of a linguistic and culturally tailored tele-retinopathy screening intervention for immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada

Background: Diabetic retinopathy is a sight-threatening ocular complication of diabetes. Screening is an effective way to reduce severe complications, but screening attendance rates are often low, particularly for newcomers and immigrants to Canada and people from cultural and linguistic minority groups. Building on previous work, in partnership with patient and health system stakeholders, we co-developed a linguistically and culturally tailored tele-retinopathy screening intervention for people living with diabetes who recently immigrated to Canada from either China or African-Caribbean countries. Methods: Following an environmental scan of diabetes eye care pathways in Ottawa, we conducted co-development workshops using a nominal group technique to create and prioritize personas of individuals requiring screening and identify barriers to screening that each persona may face. Next, we used the Theoretical Domains Framework to categorize the barriers/enablers and then mapped these categories to potential evidence-informed behaviour change techniques. Finally with these techniques in mind, participants prioritized strategies and channels of delivery, developed intervention content, and clarified actions required by different actors to overcome anticipated intervention delivery barriers. Results: We carried out iterative co-development workshops with Mandarin and French-speaking individuals living with diabetes (i.e., patients in the community) who immigrated to Canada from China and African-Caribbean countries (n = 13), patient partners (n = 7), and health system partners (n = 6) recruited from community health centres in Ottawa. Patients in the community co-development workshops were conducted in Mandarin or French. Together, we prioritized five barriers to attending diabetic retinopathy screening: language (TDF Domains: skills, social influences), retinopathy familiarity (knowledge, beliefs about consequences), physician barriers regarding communication for screening (social influences), lack of publicity about screening (knowledge, environmental context and resources), and fitting screening around other activities (environmental context and resources). The resulting intervention included the following behaviour change techniques to address prioritized local barriers: information about health consequence, providing instructions on how to attend screening, prompts/cues, adding objects to the environment, social support, and restructuring the social environment. Operationalized delivery channels incorporated language support, pre-booking screening and sending reminders, social support via social media and community champions, and providing using flyers and videos as delivery channels. Conclusion: Working with intervention users and stakeholders, we co-developed a culturally and linguistically relevant tele-retinopathy intervention to address barriers to attending diabetic retinopathy screening and increase uptake among two under-served groups

Increased risk of type I errors in cluster randomised trials with small or medium numbers of clusters: a review, reanalysis,and simulation study

Background: Cluster randomised trials (CRTs) are commonly analysed using mixed-effects models or generalised estimating equations (GEEs). However, these analyses do not always perform well with the small number of clusters typical of most CRTs. They can lead to increased risk of a type I error (finding a statistically significant treatment effect when it does not exist) if appropriate corrections are not used. Methods: We conducted a small simulation study to evaluate the impact of using small-sample corrections for mixed-effects models or GEEs in CRTs with a small number of clusters. We then reanalysed data from TRIGGER, a CRT with six clusters, to determine the effect of using an inappropriate analysis method in practice. Finally, we reviewed 100 CRTs previously identified by a search on PubMed in order to assess whether trials were using appropriate methods of analysis. Trials were classified as at risk of an increased type I error rate if they did not report using an analysis method which accounted for clustering, or if they had fewer than 40 clusters and performed an individual-level analysis without reporting the use of an appropriate small-sample correction. Results: Our simulation study found that using mixed-effects models or GEEs without an appropriate correction led to inflated type I error rates, even for as many as 70 clusters. Conversely, using small-sample corrections provided correct type I error rates across all scenarios. Reanalysis of the TRIGGER trial found that inappropriate methods of analysis gave much smaller P values (P ≤ 0.01) than appropriate methods (P = 0.04–0.15). In our review, of the 99 trials that reported the number of clusters, 64 (65 %) were at risk of an increased type I error rate; 14 trials did not report using an analysis method which accounted for clustering, and 50 trials with fewer than 40 clusters performed an individual-level analysis without reporting the use of an appropriate correction. Conclusions: CRTs with a small or medium number of clusters are at risk of an inflated type I error rate unless appropriate analysis methods are used. Investigators should consider using small-sample corrections with mixed-effects models or GEEs to ensure valid results. Abbreviations: CRT, Cluster randomised trial; CI, Confidence interval; GEE, Generalised estimating equations; TRIGGER, Trial in Gastrointestinal Transfusio