Search

Abstract Background Audit and feedback (A&F) interventions are one of the most common approaches for implementing evidence-based practices. A key barrier to more effective A&F interventions is the lack of a theory-guided approach to the accumulation of evidence. Recent interviews with theory experts identified 313 theory-informed hypotheses, spread across 30 themes, about how to create more effective A&F interventions. In the current survey, we sought to elicit from stakeholders which hypotheses were most likely to advance the field if studied further. Methods From the list of 313, three members of the research team identified 216 that were clear and distinguishable enough for prioritization. A web-based survey was then sent to 211 A&F intervention stakeholders asking them to choose up to 50 ‘priority’ hypotheses following the header “A&F interventions will be more effective if…”. Analyses included frequencies of endorsement of the individual hypotheses and themes into which they were grouped. Results 68 of the 211 invited participants responded to the survey. Seven hypotheses were chosen by > 50% of respondents, including A&F interventions will be more effective… “if feedback is provided by a trusted source”; “if recipients are involved in the design/development of the feedback intervention”; “if recommendations related to the feedback are based on good quality evidence”; “if the behaviour is under the control of the recipient”; “if it addresses barriers and facilitators (drivers) to behaviour change”; “if it suggests clear action plans”; and “if target/goal/optimal rates are clear and explicit”. The most endorsed theme was Recipient Priorities (four hypotheses were chosen 92 times as a ‘priority’ hypotheses). Conclusions This work determined a set of hypotheses thought by respondents to be to be most likely to advance the field through future A&F intervention research. This work can inform a coordinated research agenda that may more efficiently lead to more effective A&F interventions.

Abstract Background Audit 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. Methods We 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. Results We 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. Conclusion Clinical 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.

Introduction. Occupational therapists have shown low adoption rates for many evidence-based practices. One such practice is the limited uptake of standardized outcome measures such as the Canadian Occupational Performance Measure. Use of this measure has not consistently translated into practice despite decades of encouragement. Theory-based approaches to understanding healthcare provider behaviour change are needed if we are to realize the goal of attaining practice that is in keeping with evidence. This study utilized the Theoretical Domains Framework, a theory-based approach for understanding barriers to evidence-based practice, in order to increase our understanding of the limited uptake of the Canadian Occupational Performance Measure in occupational therapy practice. Methods. Theoretical Domains Framework methods were followed. First, primary data was collected from occupational therapists through semistructured interviews that focused on key behaviour change domains as they related to the use of the Canadian Occupational Performance Measure. Two independent researchers coded interview data into domains, derived belief statements from the data, and used belief strength, conflict, and frequency to determine the more and less influential domains for using the Canadian Occupational Performance Measure. Results. Interviews with 15 practicing occupational therapists across a range of practice areas yielded six key behaviour change domains for increasing the use of the Canadian Occupational Performance Measure. The more relevant domains were Social influences, Social professional role and identity, Beliefs about consequences, Beliefs about capabilities, Skills, and Behavioural regulation). The other eight domains were found to be less relevant. Conclusion. We identified important domains and beliefs that influence the use of the Canadian Occupational Performance Measure by occupational therapists. Results inform our understanding of the use of this measure in practice and identify potential targets for behaviour change interventions.

Abstract Background Audit and feedback (A&F) is a common strategy for helping health providers to implement evidence into practice. Despite being extensively studied, health care A&F interventions remain variably effective, with overall effect sizes that have not improved since 2003. Contributing to this stagnation is the fact that most health care A&F interventions have largely been designed without being informed by theoretical understanding from the behavioral and social sciences. To determine if the trend can be improved, the objective of this study was to develop a list of testable, theory-informed hypotheses about how to design more effective A&F interventions. Methods Using purposive sampling, semi-structured 60–90-min telephone interviews were conducted with experts in theories related to A&F from a range of fields (e.g., cognitive, health and organizational psychology, medical decision-making, economics). Guided by detailed descriptions of A&F interventions from the health care literature, interviewees described how they would approach the problem of designing improved A&F interventions. Specific, theory-informed hypotheses about the conditions for effective design and delivery of A&F interventions were elicited from the interviews. The resulting hypotheses were assigned by three coders working independently into themes, and categories of themes, in an iterative process. Results We conducted 28 interviews and identified 313 theory-informed hypotheses, which were placed into 30 themes. The 30 themes included hypotheses related to the following five categories: A&F recipient (seven themes), content of the A&F (ten themes), process of delivery of the A&F (six themes), behavior that was the focus of the A&F (three themes), and other (four themes). Conclusions We have identified a set of testable, theory-informed hypotheses from a broad range of behavioral and social science that suggest conditions for more effective A&F interventions. This work demonstrates the breadth of perspectives about A&F from non-healthcare-specific disciplines in a way that yields testable hypotheses for healthcare A&F interventions. These results will serve as the foundation for further work seeking to set research priorities among the A&F research community.