How do experts determine where to intervene on test ordering? An interview study.

OBJECTIVES: Lab testing is a high-volume activity that is often overused, leading to wasted resources and inappropriate care. Improving test ordering practices in tertiary care involves deciding where to focus scarce intervention resources, but clear guidance on how to optimize these resources is lacking. We aimed to explore context-sensitive factors and processes that inform individual decisions about laboratory stewardship interventions by speaking to key interest holders in this area. METHODS: We conducted semi-structured interviews with test-ordering intervention development experts and authors of test-ordering guidance documents to explore five broad topics: 1) processes used to prioritize tests for intervention; 2) factors considered when deciding which tests to target; 3) measurement of these factors; 4) interventions selected; 5) suggestions for a framework to support these decisions. Transcripts were double coded using directed-content and thematic analysis. RESULTS: We interviewed 14 intervention development experts. Experts noted they frequently consider test volume, test value, and patient care when deciding on a test to target. Experts indicated that quantifying many relevant factors was challenging. Processes to support these decisions often involved examining local data, obtaining buy-in, and relying on an existing guideline. Suggestions for building a framework emphasized the importance of collaboration, consideration of context and resources, and starting with "easy wins" to gain support and experience. CONCLUSIONS: Our study provides insight into the factors and processes experts consider when deciding which tests to target for intervention and can inform the development of a framework to guide the selection of tests for intervention and guideline development.

Choosing which in-hospital laboratory tests to target for intervention: a scoping review.

INTRODUCTION: Some laboratory testing practices may be of low value, leading to wasted resources and potential patient harm. Our scoping review investigated factors and processes that developers report using to inform decisions about what tests to target for practice improvement. METHODS: We searched Medline on May 30th, 2019 and June 28th, 2021 and included guidelines, recommendation statements, or empirical studies related to test ordering practices. Studies were included if they were conducted in a tertiary care setting, reported making a choice about a specific test requiring intervention, and reported at least one factor informing that choice. We extracted descriptive details, tests chosen, processes used to make the choice, and factors guiding test choice. RESULTS: From 114 eligible studies, we identified 30 factors related to test choice including clinical value, cost, prevalence of test, quality of test, and actionability of test results. We identified nine different processes used to inform decisions regarding where to spend intervention resources. CONCLUSIONS: Intervention developers face difficult choices when deciding where to put scarce resources intended to improve test utilization. Factors and processes identified here can be used to inform a framework to help intervention developers make choices relevant to improving testing practices.

The effects of resistant starches on inflammatory bowel disease in preclinical and clinical settings: a systematic review and meta-analysis.

BACKGROUND: Inflammatory bowel disease (IBD) is a debilitating chronic disease with limited treatment options. Resistant starches may represent a novel treatment for IBD. However, its efficacy and safety remain unclear. Our objective was to perform a systematic review to summarize the preclinical and clinical effects of resistant starch, which may help guide future studies. METHODS: Medline, EMBASE, and the Cochrane Central Register were searched. Included studies investigated the use of resistant starch therapy in in vivo animal models of IBD or human patients with IBD. Articles were screened, and data extracted, independently and in duplicate. The primary outcomes were clinical remission (clinical) and bowel mucosal damage (preclinical). RESULTS: 21 preclinical (n = 989 animals) and seven clinical (n = 164 patients) studies met eligibility. Preclinically, resistant starch was associated with a significant reduction in bowel mucosal damage compared to placebo (standardized mean difference - 1.83, 95% CI - 2.45 to - 1.20). Clinically, five studies reported data on clinical remission but clinical and methodological heterogeneity precluded pooling. In all five, a positive effect was seen in patients who consumed resistant starch supplemented diets. The majority of studies in both the preclinical and clinical settings were at a high or unclear risk of bias due to poor methodological reporting. CONCLUSIONS: Our review demonstrates that resistant starch is associated with reduced histology damage in animal studies, and improvements in clinical remission in IBD patients. These results need to be tempered by the risk of bias of included studies. Rigorously designed preclinical and clinical studies are warranted. Trial registration The review protocols were registered on PROSPERO (preclinical: CRD42019130896; clinical: CRD42019129513).

How well do critical care audit and feedback interventions adhere to best practice? Development and application of the REFLECT-52 evaluation tool.

BACKGROUND: Healthcare Audit and Feedback (A&F) interventions have been shown to be an effective means of changing healthcare professional behavior, but work is required to optimize them, as evidence suggests that A&F interventions are not improving over time. Recent published guidance has suggested an initial set of best practices that may help to increase intervention effectiveness, which focus on the "Nature of the desired action," "Nature of the data available for feedback," "Feedback display," and "Delivering the feedback intervention." We aimed to develop a generalizable evaluation tool that can be used to assess whether A&F interventions conform to these suggestions for best practice and conducted initial testing of the tool through application to a sample of critical care A&F interventions. METHODS: We used a consensus-based approach to develop an evaluation tool from published guidance and subsequently applied the tool to conduct a secondary analysis of A&F interventions. To start, the 15 suggestions for improved feedback interventions published by Brehaut et al. were deconstructed into rateable items. Items were developed through iterative consensus meetings among researchers. These items were then piloted on 12 A&F studies (two reviewers met for consensus each time after independently applying the tool to four A&F intervention studies). After each consensus meeting, items were modified to improve clarity and specificity, and to help increase the reliability between coders. We then assessed the conformity to best practices of 17 critical care A&F interventions, sourced from a systematic review of A&F interventions on provider ordering of laboratory tests and transfusions in the critical care setting. Data for each criteria item was extracted by one coder and confirmed by a second; results were then aggregated and presented graphically or in a table and described narratively. RESULTS: In total, 52 criteria items were developed (38 ratable items and 14 descriptive items). Eight studies targeted lab test ordering behaviors, and 10 studies targeted blood transfusion ordering. Items focused on specifying the "Nature of the Desired Action" were adhered to most commonly-feedback was often presented in the context of an external priority (13/17), showed or described a discrepancy in performance (14/17), and in all cases it was reasonable for the recipients to be responsible for the change in behavior (17/17). Items focused on the "Nature of the Data Available for Feedback" were adhered to less often-only some interventions provided individual (5/17) or patient-level data (5/17), and few included aspirational comparators (2/17), or justifications for specificity of feedback (4/17), choice of comparator (0/9) or the interval between reports (3/13). Items focused on the "Nature of the Feedback Display" were reported poorly-just under half of interventions reported providing feedback in more than one way (8/17) and interventions rarely included pilot-testing of the feedback (1/17 unclear) or presentation of a visual display and summary message in close proximity of each other (1/13). Items focused on "Delivering the Feedback Intervention" were also poorly reported-feedback rarely reported use of barrier/enabler assessments (0/17), involved target members in the development of the feedback (0/17), or involved explicit design to be received and discussed in a social context (3/17); however, most interventions clearly indicated who was providing the feedback (11/17), involved a facilitator (8/12) or involved engaging in self-assessment around the target behavior prior to receipt of feedback (12/17). CONCLUSIONS: Many of the theory-informed best practice items were not consistently applied in critical care and can suggest clear ways to improve interventions. Standardized reporting of detailed intervention descriptions and feedback templates may also help to further advance research in this field. The 52-item tool can serve as a basis for reliably assessing concordance with best practice guidance in existing A&F interventions trialed in other healthcare settings, and could be used to inform future A&F intervention development. TRIAL REGISTRATION: Not applicable.