ObjectivesTo evaluate the effectiveness of practices used to support appropriate clinical laboratory test utilization.MethodsThis review followed the Centers for Disease Control and Prevention (CDC) Laboratory Medicine Best Practices A6 cycle method. Eligible studies assessed one of the following practices for effect on outcomes relating to over- or underutilization: computerized provider order entry (CPOE), clinical decision support systems/tools (CDSS/CDST), education, feedback, test review, reflex testing, laboratory test utilization (LTU) teams, and any combination of these practices. Eligible outcomes included intermediate, systems outcomes (eg, number of tests ordered/performed and cost of tests), as well as patient-related outcomes (eg, length of hospital stay, readmission rates, morbidity, and mortality).ResultsEighty-three studies met inclusion criteria. Fifty-one of these studies could be meta-analyzed. Strength of evidence ratings for each practice ranged from high to insufficient.ConclusionPractice recommendations are made for CPOE (specifically, modifications to existing CPOE), reflex testing, and combined practices. No recommendation for or against could be made for CDSS/CDST, education, feedback, test review, and LTU. Findings from this review serve to inform guidance for future studies.

Background Diagnostic test accuracy (DTA) systematic reviews (SRs) characterize a test’s potential for diagnostic quality and safety. However, interpreting DTA measures in the context of SRs is challenging. Further, some evidence grading methods (e.g. Centers for Disease Control and Prevention, Division of Laboratory Systems Laboratory Medicine Best Practices method) require determination of qualitative effect size ratings as a contributor to practice recommendations. This paper describes a recently developed effect size rating approach for assessing a DTA evidence base. Methods A likelihood ratio scatter matrix will plot positive and negative likelihood ratio pairings for DTA studies. Pairings are graphed as single point estimates with confidence intervals, positioned in one of four quadrants derived from established thresholds for test clinical validity. These quadrants support defensible judgments on “substantial”, “moderate”, or “minimal” effect size ratings for each plotted study. The approach is flexible in relation to a priori determinations of the relative clinical importance of false positive and false negative test results. Results and conclusions This qualitative effect size rating approach was operationalized in a recent SR that assessed effectiveness of test practices for the diagnosis of Clostridium difficile. Relevance of this approach to other methods of grading evidence, and efforts to measure diagnostic quality and safety are described. Limitations of the approach arise from understanding that a diagnostic test is not an isolated element in the diagnostic process, but provides information in clinical context towards diagnostic quality and safety.

SUMMARY The evidence base for the optimal laboratory diagnosis of Clostridioides (Clostridium) difficile in adults is currently unresolved due to the uncertain performance characteristics and various combinations of tests. This systematic review evaluates the diagnostic accuracy of laboratory testing algorithms that include nucleic acid amplification tests (NAATs) to detect the presence of C. difficile. The systematic review and meta-analysis included eligible studies (those that had PICO [population, intervention, comparison, outcome] elements) that assessed the diagnostic accuracy of NAAT alone or following glutamate dehydrogenase (GDH) enzyme immunoassays (EIAs) or GDH EIAs plus C. difficile toxin EIAs (toxin). The diagnostic yield of NAAT for repeat testing after an initial negative result was also assessed. Two hundred thirty-eight studies met inclusion criteria. Seventy-two of these studies had sufficient data for meta-analysis. The strength of evidence ranged from high to insufficient. The uses of NAAT only, GDH-positive EIA followed by NAAT, and GDH-positive/toxin-negative EIA followed by NAAT are all recommended as American Society for Microbiology (ASM) best practices for the detection of the C. difficile toxin gene or organism. Meta-analysis of published evidence supports the use of testing algorithms that use NAAT alone or in combination with GDH or GDH plus toxin EIA to detect the presence of C. difficile in adults. There is insufficient evidence to recommend against repeat testing of the sample using NAAT after an initial negative result due to a lack of evidence of harm (i.e., financial, length of stay, or delay of treatment) as specified by the Laboratory Medicine Best Practices (LMBP) systematic review method in making such an assessment. Findings from this systematic review provide clarity to diagnostic testing strategies and highlight gaps, such as low numbers of GDH/toxin/PCR studies, in existing evidence on diagnostic performance, which can be used to guide future clinical research studies.

The role of metacognitive skills in the evidence analysis process has received little attention in the research literature. While the steps of the evidence analysis process are well defined, the role of higher-level cognitive operations (metacognitive strategies) in integrating the steps of the process is not well understood. In part, this is because it is not clear where and how metacognition is implicated in the evidence analysis process nor how these skills might be taught.The purposes of this paper are to (a) suggest a model for identifying critical thinking and metacognitive skills in evidence analysis instruction grounded in current educational theory and research and (b) demonstrate how freely available systematic review/meta-analysis tools can be used to focus on higher-order metacognitive skills, while providing a framework for addressing common student weaknesses. The final goal of this paper is to provide an instructional framework that can generate critique and elaboration while providing the conceptual basis and rationale for future research agendas on this topic.

ObjectivesClinical laboratory testing provides essential data for making medical diagnoses. Generating accurate and timely test results clearly communicated to the treating clinician, and ultimately the patient, is a critical component that supports diagnostic excellence. On the other hand, failure to achieve this can lead to diagnostic errors that manifest in missed, delayed and wrong diagnoses.ContentInnovations that support diagnostic excellence address: 1) test utilization, 2) leveraging clinical and laboratory data, 3) promoting the use of credible information resources, 4) enhancing communication among laboratory professionals, health care providers and the patient, and 5) advancing the use of diagnostic management teams. Integrating evidence-based laboratory and patient-care quality management approaches may provide a strategy to support diagnostic excellence. Professional societies, government agencies, and healthcare systems are actively engaged in efforts to advance diagnostic excellence. Leveraging clinical laboratory capabilities within a healthcare system can measurably improve the diagnostic process and reduce diagnostic errors.SummaryAn expanded quality management approach that builds on existing processes and measures can promote diagnostic excellence and provide a pathway to transition innovative concepts to practice.OutlookThere are increasing opportunities for clinical laboratory professionals and organizations to be part of a strategy to improve diagnoses.