Practice Feedback Interventions: 15 Suggestions for Optimizing Effectiveness

Electronic practice data are increasingly being used to provide feedback to encourage practice improvement. However, evidence suggests that despite decades of experience, the effects of such interventions vary greatly and are not improving over time. Guidance on providing more effective feedback does exist, but it is distributed across a wide range of disciplines and theoretical perspectives. Through expert interviews; systematic reviews; and experience with providing, evaluating, and receiving practice feedback, 15 suggestions that are believed to be associated with effective feedback interventions have been identified. These suggestions are intended to provide practical guidance to quality improvement professionals, information technology developers, educators, administrators, and practitioners who receive such interventions. Designing interventions with these suggestions in mind should improve their effect, and studying the mechanisms underlying these suggestions will advance a stagnant literature

When piloting health services interventions, what predicts real world behaviours? A systematic concept mapping review

Modeling studies to inform the design of complex health services interventions often involves elements that differ from the intervention's ultimate real-world use. These "hypothetical" elements include pilot participants, materials, and settings. Understanding the conditions under which studies with "hypothetical" elements can yield valid results would greatly help advance health services research. Our objectives are: 1) to conduct a systematic review of the literature to identify factors affecting the relationship between hypothetical decisions and real-world behaviours, and 2) to summarise and organize these factors into a preliminary framework. Methods: We conducted an electronic database search using PsycINFO and Medline on November 30th, 2015, updated March 7th, 2019. We also conducted a supplemental snowball search on December 9th 2015 and a reverse citation search using Scopus and Web of Science. Studies were eligible to be included in this review if they clearly addressed the consistency between some type of hypothetical decision and a corresponding real decision or behaviour. Two reviewers extracted data using a standardized data collection form developed through an iterative consensus-based process. We extracted basic study information and data about each study's research area, design, and research question. Quotations from the articles were extracted and summarized into standardized factor statements. Results: Of the 2444 articles that were screened, 68 articles were included in the review. The articles identified 27 factors that we grouped into 4 categories: decision maker factors, cognitive factors, task factors, and matching factors. Conclusions: We have summarized a large number of factors that may be relevant when considering whether hypothetical health services pilot work can be expected to yield results that are consistent with real-world behaviours. Our descriptive framework can serve as the basis for organizing future work exploring which factors are most relevant when seeking to develop complex health services interventions

Patient information leaflets (PILs) for UK randomised controlled trials : a feasibility study exploring whether they contain information to support decision making about trial participation

Peer reviewedPublisher PD

Computer-supported feedback message tailoring: Theory-informed adaptation of clinical audit and feedback for learning and behavior change

Background: Evidence shows that clinical audit and feedback can significantly improve compliance with desired practice, but it is unclear when and how it is effective. Audit and feedback is likely to be more effective when feedback messages can influence barriers to behavior change, but barriers to change differ across individual health-care providers, stemming from differences in providers' individual characteristics. Discussion: The purpose of this article is to invite debate and direct research attention towards a novel audit and feedback component that could enable interventions to adapt to barriers to behavior change for individual health-care providers: computer-supported tailoring of feedback messages. We argue that, by leveraging available clinical data, theory-informed knowledge about behavior change, and the knowledge of clinical supervisors or peers who deliver feedback messages, a software application that supports feedback message tailoring could improve feedback message relevance for barriers to behavior change, thereby increasing the effectiveness of audit and feedback interventions. We describe a prototype system that supports the provision of tailored feedback messages by generating a menu of graphical and textual messages with associated descriptions of targeted barriers to behavior change. Supervisors could use the menu to select messages based on their awareness of each feedback recipient's specific barriers to behavior change. We anticipate that such a system, if designed appropriately, could guide supervisors towards giving more effective feedback for health-care providers. Summary: A foundation of evidence and knowledge in related health research domains supports the development of feedback message tailoring systems for clinical audit and feedback. Creating and evaluating computer-supported feedback tailoring tools is a promising approach to improving the effectiveness of clinical audit and feedback

Measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM)

© 2008 Sladek et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background Understanding how doctors think may inform both undergraduate and postgraduate medical education. Developing such an understanding requires valid and reliable measurement tools. We examined the measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM), designed to tap this domain with specific reference to medicine, but with previously questionable measurement properties. Methods First year postgraduate entry medical students at Flinders University, and trainees (postgraduate doctors in any specialty) and consultants (N = 348) based at two teaching hospitals in Adelaide, Australia, completed the ICBM and a questionnaire measuring thinking styles (Rational Experiential Inventory). Results Questions with the lowest item-total correlation were deleted from the original 22 item ICBM, although the resultant 17 item scale only marginally improved internal consistency (Cronbach's α = 0.61 compared with 0.57). A factor analysis identified two scales, both achieving only α = 0.58. Construct validity was assessed by correlating Rational Experiential Inventory scores with the ICBM, with some positive correlations noted for students only, suggesting that those who are naïve to the knowledge base required to "successfully" respond to the ICBM may profit by a thinking style in tune with logical reasoning. Conclusion The ICBM failed to demonstrate adequate content validity, internal consistency and construct validity. It is unlikely that improvements can be achieved without considered attention to both the audience for which it is designed and its item content. The latter may need to involve both removal of some items deemed to measure multiple biases and the addition of new items in the attempt to survey the range of biases that may compromise medical decision making

Arduous implementation: Does the Normalisation Process Model explain why it's so difficult to embed decision support technologies for patients in routine clinical practice

Background: decision support technologies (DSTs, also known as decision aids) help patients and professionals take part in collaborative decision-making processes. Trials have shown favorable impacts on patient knowledge, satisfaction, decisional conflict and confidence. However, they have not become routinely embedded in health care settings. Few studies have approached this issue using a theoretical framework. We explained problems of implementing DSTs using the Normalization Process Model, a conceptual model that focuses attention on how complex interventions become routinely embedded in practice.Methods: the Normalization Process Model was used as the basis of conceptual analysis of the outcomes of previous primary research and reviews. Using a virtual working environment we applied the model and its main concepts to examine: the 'workability' of DSTs in professional-patient interactions; how DSTs affect knowledge relations between their users; how DSTs impact on users' skills and performance; and the impact of DSTs on the allocation of organizational resources.Results: conceptual analysis using the Normalization Process Model provided insight on implementation problems for DSTs in routine settings. Current research focuses mainly on the interactional workability of these technologies, but factors related to divisions of labor and health care, and the organizational contexts in which DSTs are used, are poorly described and understood.Conclusion: the model successfully provided a framework for helping to identify factors that promote and inhibit the implementation of DSTs in healthcare and gave us insights into factors influencing the introduction of new technologies into contexts where negotiations are characterized by asymmetries of power and knowledge. Future research and development on the deployment of DSTs needs to take a more holistic approach and give emphasis to the structural conditions and social norms in which these technologies are enacte

Do physician outcome judgments and judgment biases contribute to inappropriate use of treatments? Study protocol

<p>Abstract</p> <p>Background</p> <p>There are many examples of physicians using treatments inappropriately, despite clear evidence about the circumstances under which the benefits of such treatments outweigh their harms. When such over- or under- use of treatments occurs for common diseases, the burden to the healthcare system and risks to patients can be substantial. We propose that a major contributor to inappropriate treatment may be how clinicians judge the likelihood of important treatment outcomes, and how these judgments influence their treatment decisions. The current study will examine the role of judged outcome probabilities and other cognitive factors in the context of two clinical treatment decisions: 1) prescription of antibiotics for sore throat, where we hypothesize overestimation of benefit and underestimation of harm leads to over-prescription of antibiotics; and 2) initiation of anticoagulation for patients with atrial fibrillation (AF), where we hypothesize that underestimation of benefit and overestimation of harm leads to under-prescription of warfarin.</p> <p>Methods</p> <p>For each of the two conditions, we will administer surveys of two types (Type 1 and Type 2) to different samples of Canadian physicians. The primary goal of the Type 1 survey is to assess physicians' perceived outcome probabilities (both good and bad outcomes) for the target treatment. Type 1 surveys will assess judged outcome probabilities in the context of a representative patient, and include questions about how physicians currently treat such cases, the recollection of rare or vivid outcomes, as well as practice and demographic details. The primary goal of the Type 2 surveys is to measure the specific factors that drive individual clinical judgments and treatment decisions, using a 'clinical judgment analysis' or 'lens modeling' approach. This survey will manipulate eight clinical variables across a series of sixteen realistic case vignettes. Based on the survey responses, we will be able to identify which variables have the greatest effect on physician judgments, and whether judgments are affected by inappropriate cues or incorrect weighting of appropriate cues. We will send antibiotics surveys to family physicians (300 per survey), and warfarin surveys to both family physicians and internal medicine specialists (300 per group per survey), for a total of 1,800 physicians. Each Type 1 survey will be two to four pages in length and take about fifteen minutes to complete, while each Type 2 survey will be eight to ten pages in length and take about thirty minutes to complete.</p> <p>Discussion</p> <p>This work will provide insight into the extent to which clinicians' judgments about the likelihood of important treatment outcomes explain inappropriate treatment decisions. This work will also provide information necessary for the development of an individualized feedback tool designed to improve treatment decisions. The techniques developed here have the potential to be applicable to a wide range of clinical areas where inappropriate utilization stems from biased judgments.</p