Arguments in favor of greater research-practice integration in medicine have tended to be ethical, political, or pragmatic. There are good epistemic reasons to pursue greater integration, and it is important to think through these reasons in order to avoid inadvertently designing new systems in ways that replicate the epistemic elitism common within current systems. Meaningful transformation within health care is possible with close attention to all reasons in favor of greater research-practice integration, including epistemic reasons.

Harms of medical interventions are systematically underestimated in clinical research. Numerous factors—conceptual, methodological, and social—contribute to this underestimation. I articulate the depth of such underestimation by describing these factors at the various stages of clinical research. Before any evidence is gathered, the ways harms are operationalized in clinical research contributes to their underestimation. Medical interventions are first tested in phase 1 ‘first in human’ trials, but evidence from these trials is rarely published, despite the fact that such trials provide the (...) foundation for assessing the harm profile of medical interventions. If a medical intervention is deemed safe in a phase 1 trial, it is tested in larger phase 2 and 3 clinical trials. One way to think about the problem of underestimating harms is in terms of the statistical ‘power’ of a clinical trial—the ability of a trial to detect a difference of a certain effect size between the experimental group and the control group. Power is normally thought to be pertinent to detecting benefits of medical interventions. It is important, though, to distinguish between the ability of a trial to detect benefits and the ability of a trial to detect harms. I refer to the former as power-B and the latter as power-H. I identify several factors that maximize power-B by sacrificing powerH in phase 3 clinical trials. If a medical intervention is approved for general use, it is evaluated by phase 4 post-market surveillance. Phase 4 surveillance of harms further contributes to underestimating the harm profile of medical interventions. At every stage of clinical research the hunt for harms is shrouded in secrecy, which further contributes to the underestimation of the harm profiles of medical interventions. (shrink)

Measurement outcomes are frequently used as evidence in favor of or against medical and surgical interventions, health policies, and system designs. Indeed, in the medical and health services research literature, outcomes are the currency of policy debate and decision making. Yet in the philosophy of science and philosophy of medicine, the measures used in evidence-based medicine (EBM) are rarely discussed. Rather, the focus here is almost exclusively on study design and hierarchies of evidence. This concentration on the methodology of study (...) design has meant that for practical purposes the measures used in randomized controlled trials, observational studies, audits, and so forth, appear as a “black box.” Yet as I argue in the first part of this article, an engagement with measurement can improve our understanding of EBM and the quality of our evidence. In the second part of the article, I develop such an engagement with one aspect of measurement, namely, the validity of patient-reported outcome measures. Here, I illustrate some of the complexity that is required to improve the validity of these measures and hence the validity of our study outcomes, that is, evidence. The concentration in philosophy of science on study design over measurement methodology perhaps reveals the interest that many philosophers of medicine have in causation, but there is more to the production of high-quality scientific evidence than securing the causal inference. (shrink)

The Belmont Report’s distinction between research and the practice of accepted therapy has led various authors to suggest that these purportedly distinct activities should be governed by different ethical principles. We consider some of the ethical consequences of attempts to separate the two and conclude that separation fails along ontological, ethical, and epistemological dimensions. Clinical practice and clinical research, as with yin and yang, can be thought of as complementary forces interacting to form a dynamic system in which the whole (...) exceeds the sum of its parts. Just as effective clinical practice cannot exist without clinical research, meaningful clinical research requires the context of clinical practice. We defend this thesis by triangulation, that is, by outlining how multiple investigators have reached this conclusion on the basis of varied theoretical and applied approaches. More confidence can be placed in a result if different methods/viewpoints have led to that result. (shrink)

Since its introduction just over two decades ago, evidence-based medicine (EBM) has come to dominate medical practice, teaching, and policy. There are a growing number of textbooks, journals, and websites dedicated to EBM research, teaching, and evidence dissemination. EBM was most recently defined as a method that integrates best research evidence with clinical expertise and patient values and circumstances in the treatment of patients. There have been debates throughout the early 21st century about what counts as good research evidence between (...) EBM proponents and philosophical critics and even within the EBM community itself. Similar controversy arises about the relative worth of patient values and clinical expertise (and how these can be integrated). EBM has also evolved in ways that have come under scrutiny. Specifically, policymakers have used EBM research methodology to increase the relative importance of clinical guidelines that some clinicians have argued are tyrannical. Philosophers have addressed all of these controversies, and with very few exceptions have been critical of EBM. In addition most philosophical attention has been on the epistemic role of Randomization and evidence hierarchies, with relatively little attention being paid to the role of Diagnosis, expertise, patient values, and Systematic Reviews within EBM. (shrink)

Hierarchies of evidence are an important and influential tool for appraising evidence in medicine. In recent years, hierarchies have been formally adopted by organizations including the Cochrane Collaboration [1], NICE [2,3], the WHO [4], the US Preventive Services Task Force [5], and the Australian NHMRC [6,7]. The development of such hierarchies has been regarded as a central part of Evidence-Based Medicine, a movement within healthcare which prioritises the use of epidemiological evidence such as that provided by Randomised Controlled Trials. Philosophical (...) work on the methodology of medicine has so far mostly focused on claims about the superiority of RCTs, and hence has largely neglected the questions of what hierarchies are, what assumptions they require, and how they affect clinical practice. This thesis shows that there is great variation in the hierarchies defended and in the interpretations they are, and can be, given. The interpretative assumptions made in using hierarchies are crucial to the content and defensibility of the underlying philosophical commitments concerning evidence and medical practice. Once this variation is been identified, it becomes clear that the little philosophical work that has been done so far affects only some hierarchies, under some interpretations. Modest interpretations offered by La Caze [11], conditional hierarchies like GRADE [12-14], and heuristic approaches such as that defended by Howick et al. [15,16] all survive previous philosophical criticism. This thesis extends previous criticisms by arguing that modest interpretations are so weak as to be unhelpful for clinical practice; that GRADE and similar conditional models omit clinically relevant information, such as information about variation in treatments’ effects and the causes of different responses to therapy; and that heuristic approaches lack the necessary empirical support. The conclusion is that hierarchies in general embed untenable philosophical assumptions: principally that information about average treatment effects backed by high-quality evidence can justify strong recommendations, and that the impact of evidence from individual studies can and should be appraised in isolation. Hierarchies are a poor basis for the application of evidence in clinical practice. The Evidence-Based Medicine movement should move beyond them and explore alternative tools for appraising the overall evidence for therapeutic claims. (shrink)