Journal of evaluation in clinical practice
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Randomized trials are undoubtedly different from observational studies, but authors sometimes propose differences between these designs that do not exist. In this article we examine two claims about randomized trials: first, a recent claim that the causal structure of exposure measurement (information) bias in a randomized trial differs from the causal structure of that bias in an observational study. ⋯ Using causal diagrams (causal directed acyclic graphs), we show that both claims are false in the context of an intention-to-treat analysis. We also describe a previously unrecognized mechanism of information bias, and suggest that the term 'information bias' should replace the terms 'measurement bias' and 'observation bias'.
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Rationale, aims and objectives Evidence-based medicine (EBM) claims to be based on 'evidence', rather than 'intuition'. However, EBM's fundamental distinction between quantitative 'evidence' and qualitative 'intuition' is not self-evident. The meaning of 'evidence' is unclear and no studies of quality exist to demonstrate the superiority of EBM in health care settings. ⋯ Results EBM's strict distinction between admissible evidence (based on RCTs) and other supposedly inadmissible evidence is not itself based on evidence, but rather, on intuition. In other words, according to EBM's own logic, there can be no 'evidentiary' basis for its distinction between admissible and inadmissible evidence. Ultimately, to uphold this fundamental distinction, EBM must seek recourse in (bio)political ideology and an epistemology akin to faith.
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Prescribing decisions are not always based on published clinical research; social and environmental influences can sometimes drive such decisions. However, little is known about this topic in prescribing in secondary care. The aim of this study was to explore such influences by asking doctors to discuss their uncomfortable prescribing decisions in secondary care. ⋯ Incorporating the research evidence into prescribing decisions was associated with much discomfort by secondary care doctors. Greater efforts should also be placed towards developing the model of EBM, so that it fits more explicitly with how medicine is currently practised. Perhaps more importantly, educators need to reinforce what EBM is and what it is not to all concerned in the delivery of health care.
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First, we examine whether clinical guidelines, designed to improve health care and reduce disparities in clinical practice, are achieving their intended consequences. Second, we contemplate potential unintended consequences of clinical guidelines. ⋯ Consistent with other research we find that clinical practice guidelines are not producing a principal intended result, and may even produce unintended consequences.
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The use of general clinical guidelines versus customization of patient care presents a dilemma for clinicians managing chronic illness. The objective of this project is to investigate the claim that the performance of customized strategies for the management of chronic illness depends on accurate patient categorization, and inaccurate categorization can lead to worse performance than that achievable using a general clinical guideline. ⋯ Results of the analysis have four implications regarding the design and use of clinical guidelines and customization of care: (i) the balance between the applications of more general strategies versus customization depends on the specificity and accuracy of the strategies; (ii) adoption of clinical guidelines may be stifled as the complexity of guidelines increases to account for growing evidence; (iii) clinical inertia (i.e. the failure to intensify an indicated treatment) can be a rational response to strategy specificity and the probability of misapplication; and, (iv) current clinical guidelines and other decision-support tools may be improved if they accommodate the need for customization of strategies for some patients while providing support for proper categorization of patients.