This paper advocates for making epistemic interests a central object of philosophical analysis in epistemology and philosophy of science. It is argued that the importance of epistemic interests derives from their fundamental importance for the notion of objectivity. Epistemic interests are defined as individuated by a set of objectives, each of which represents a dimension of the search for truth. Among these dimensions, specificity, sensitivity, and productivity are discussed in detail. It is argued that the relevance of productivity is often (...) overlooked in debates about the ends and means of science. A definition of the objectivity of inquiry is proposed that takes the notion of epistemic interest as its starting point. (shrink)

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)

Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.

COVID-19 presents many challenges, both clinical and philosophical. In this paper we discuss a major lacuna that COVID-19 revealed in our philosophy and understanding of medicine. Whereas we have some understanding of how physician-scientists interrogate the world to learn more about medicine, we do not understand the epistemological costs and benefits of the various ways clinicians acquire new knowledge in their fields. We will also identify reasons this topic is important both when the world is facing a pandemic and when (...) it is not. (shrink)

Heterogeneous treatment effects represent a major issue for medicine as they undermine reliable inference and clinical decision-making. To overcome the issue, the current vision of precision and personalized medicine acknowledges the need to control individual variability in response to treatment. In this paper, we argue that gene-treatment-environment interactions (G × T × E) undermine inferences about individual treatment effects from the results of both genomics-based methodologies—such as genome-wide association studies (GWAS) and genome-wide interaction studies (GWIS)—and randomized controlled trials (RCTs). Then, (...) we argue that N-of-1 trials can be a solution to overcome difficulties in handling individual variability in treatment response. Although this type of trial has been suggested as a promising strategy to assess individual treatment effects, it nonetheless has limitations that limit its use in everyday clinical practice. We analyze the existing variability within the designs of N-of-1 trials in terms of a continuum where each design prioritizes epistemic and pragmatic considerations. We then support wider use of the designs located at the pragmatic end of the explanatory-pragmatic continuum. (shrink)

Two approaches to evidential reasoning compete in the biomedical and social sciences: the experimental and the pragmatist. Whereas experimentalism has received considerable philosophical analysis and support since the times of Bacon and Mill, pragmatism about evidence has been neither articulated nor defended. The overall aim is to fill this gap and develop a theory that articulates the latter. The main ideas of the theory will be illustrated and supported by a case study on the smoking/lung cancer controversy in the 1950s.

Within public health, and increasingly other areas of social policy, there are widespread calls to increase or improve the use of evidence for policy-making. Often these calls rest on an assumption that increased evidence utilisation will be a more efficient or effective means of achieving social goals. Yet a clear elucidation of what can be considered “good evidence” for policy is rarely articulated. Many of the current discussions of best practise in the health policy sector derive from the evidence-based medicine (...) movement, embracing the “hierarchy of evidence” that places experimental trials as pre-eminent in terms of methodological quality. However, a number of problems arise if these hierarchies are used to rank or prioritise policy relevance. Challenges in applying evidence hierarchies to policy questions arise from the fact that the EBM hierarchies rank evidence of intervention effect on a specified and limited number of outcomes. Previous authors have noted that evidence forms at the top of... (shrink)

Scientific consensus is widely deferred to in public debates as a social indicator of the existence of knowledge. However, it is far from clear that such deference to consensus is always justified. The existence of agreement in a community of researchers is a contingent fact, and researchers may reach a consensus for all kinds of reasons, such as fighting a common foe or sharing a common bias. Scientific consensus, by itself, does not necessarily indicate the existence of shared knowledge among (...) the members of the consensus community. I address the question of under what conditions it is likely that a consensus is in fact knowledge based. I argue that a consensus is likely to be knowledge based when knowledge is the best explanation of the consensus, and I identify three conditions—social calibration, apparent consilience of evidence, and social diversity, for knowledge being the best explanation of a consensus. (shrink)

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments’ efficacy and a ground for drug approval. Our purpose is twofold. First, we (...) show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments’ efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results. (shrink)

The results of econometric modeling are fragile in the sense that minor changes in estimation techniques or sample can lead to statistical models that support inconsistent causal hypotheses. The fragility of econometric results undermines making conclusive inferences from the empirical literature. I argue that the program of evidential pluralism, which originated in the context of medicine and encapsulates to the normative reading of the Russo-Williamson Thesis that causal claims need the support of both difference-making and mechanistic evidence, offers a ground (...) for resolving empirical disagreements. I analyze a recent econometric controversy regarding the tax elasticity of cigarette consumption and smoking intensity. Both studies apply plausible estimation techniques but report inconsistent results. I show that mechanistic evidence allows for discriminating econometric models representing genuine causal relations from accidental dependencies in data. Furthermore, I discuss the differences between biological and social mechanisms and mechanistic evidence across the disciplines. I show that economists mainly rely on mathematical models to represent possible mechanisms. Still, claiming the actuality of the represented mechanisms requires establishing that crucial assumptions of these models are descriptively adequate. I exemplify my approach to assessing the quality of mechanistic evidence in economics with an analysis of two models of rational addiction. (shrink)

The existing philosophical views on what is the meaning of causality adequate to medicine are vastly divided. We approach this question and offer two arguments in favor of pluralism regarding concepts of causality. First, we analyze the three main types of research designs (randomized-controlled trials, observational epidemiology and laboratory research). We argue, using examples, that they allow for making causal conclusions that are best understood differently in each case (in agreement with a version of manipulationist, probabilistic and mechanistic definitions, respectively). (...) Second, we analyze clinical practice and argue that these manipulationist, probabilistic and mechanistic causal claims can be used as evidence for different therapeutic decisions. We differentiate among ‘predicting’ that does not change the relata of causal claims, (mechanistic) ‘interferences’, and ‘interventions’ in the strict sense that act on causes to change effects. The central conclusion is that causal claims agreeing with diverse concepts of causality can deliver evidence for different types of therapeutic decisions. (shrink)

There is now a general consensus amongst philosophers in the values in science literature that values necessarily play a role in core areas of scientific inquiry. We argue that attention should now be turned from debating the value-free ideal to delineating legitimate from illegitimate influences of values in science, a project we dub “The New Demarcation Problem.” First, we review past attempts to demarcate the uses of values and propose a categorization of the strategies by where they seek to draw (...) legitimacy from. Next, we propose a set of desiderata for what we take to be a satisfactory solution and present a case study where conflicting sets of values clearly impinge on science, but where the legitimacy of their influence is ambiguous. We use these desiderata and the case study to illustrate what we take to be the strengths and weaknesses of current strategies. To be clear, our goal is not to answer the question we pose, but to articulate a framework within which a solution can be judged. (shrink)

This empirical work attends to the tensions and contradictions medical students articulate when they discuss their objection to industry’s influence in medicine. Findings are based on 50 semi-structured interviews with medical students who are critical of the pharmaceutical industry’s influence in medical education in the United States and Canada. These students advocate evidence-based medicine as one solution to the problems with industry influence in medicine; namely industry bias in medical research. This investigation is an effort to understand why EBM is (...) posed as a solution to industry bias in light of the literature demonstrating the ways that what is considered ‘evidence-based’ is influenced by industry. Participants articulate a struggle to find the ‘best’ evidence in a context where industry interests are integral in the production of medical knowledge. (shrink)

Increasingly, policymakers within biomedicine argue that “non-financial” interests should be given equal scrutiny to individuals’ financial relationships with industry. Problematized as “non-financial conflicts of interest,” interests, ranging from intellectual commitments to personal beliefs, are managed through disclosure, restrictions on participation, and recusal where necessary. “Non-financial” interests, though vaguely and variably defined, are characterized as important influences on judgment and thus, are considered risks to scientific objectivity. This article explores the ways that “non-financial interests” have been constructed as an ethical problem (...) and the implications for research integrity. I conducted an interpretive, qualitative study, which triangulated two data sources: documents (including published accounts of identifying and managing “non-financial” interests and conflict of interest policies) and in-depth interviews with 16 leaders within evidence-based medicine, responsible for contributing to, directing, or overseeing conflict of interest policy development and implementation. This article outlines how evolutions in the definition of conflict of interest have opened the door to include myriad “non-financial” interests, resulting in the generalisation of a statistical concept—risk of bias—to social contexts. Consequently, biases appear equally pervasive among participants while in reality, a politics of objectivity is at play, with allegations of conflict of interest used as a means to undermine others’ credibility, or even participation. Iterations of the concept of conflict of interest within biomedicine have thus consistently failed to articulate or address questions of accountability including whose interests are able to dominate or distort evidence-led processes and why. Consequently, current policy solutions meant to mitigate bias may instead serve exclusionary purposes under the guise of impartiality while remaining vulnerable to interference from powerful stakeholders. (shrink)

As the quality movement in health care now enters its fourth decade, the language of quality is ubiquitous. Practitioners, organizations, and government agencies alike vociferously testify their commitments to quality and accept numerous forms of governance aimed at improving quality of care. Remarkably, the powerful phrase ‘‘quality of care’’ is rarely defined in the health care literature. Instead it operates as an accepted and assumed goal worth pursuing. The status of evidence-based medicine, for instance, hinges on its ability to improve (...) quality of care, and efforts are made by both proponents and detractors to unpack the contents and outcomes of evidence-based practice while the contents of ‘‘quality of care’’ are presumed to be understood. Because the goals of medicine are far from obvious, this paper investigates the neglected term, ‘‘quality of care,’’ in an effort to understand what it is that health care practices are so uncritically assumed to be striving for. Finding lack of consensus on the terminology in the quality literature, I propose that the term operates rhetorically by way of persuasive appeal (and lack of descriptive meaning). Unsatisfied that ‘‘quality of care’’ operates as a mere buzzword in morally contentious debates over resource allocation and duties of care, I implore health care communities to go beyond mere commitments to quality and, instead, to focus attention on the difficult task of specifying what counts as quality care within an economically constrained health care system. (shrink)

The question what scientific progress means for a particular domain such as medicine seems importantly different from the question what scientific progress is in general. While the latter question received ample treatment in the philosophical literature, the former question is hardly discussed. I argue that it is nonetheless important to think about this question in view of the methodological choices we make. I raise specific questions that should be tackled regarding scientific progress in the medical sciences and demonstrate their importance (...) by means of an analysis of what evidence-based medicine (EBM) has, and has not, to offer in terms of progress. I show how critically thinking about EBM from the point of view of progress can help us in putting EBM and its favoured methodologies in the right perspective. My conclusion will be that blindly favouring certain methods because of their immediately tangible short-term benefits implies that we parry the important question of how best to advance progress in the long run. This leads us to losing sight of our general goals in doing research in the medical sciences. (shrink)

Despite increasing recognition of the ways in which ethical and social values play a role in science (Kitcher 2001; Longino 1990, 2002), scientists are often still reluctant to acknowledge or discuss ethical and social values at stake in their research. Even when research is closely connected to developing public policy, it is generally held that it should be empirical data, and not the values of scientists, that inform policy. According to this view, scientists need not, and should not, endorse non-epistemic (...) values related to their research, as doing so may bias their assessment of what the evidence is. As a result, debates over science-based policy tend to be construed solely as empirical discussions to be .. (shrink)

The UK’s National Institute for Health and Care Excellence is responsible for conducting health technology assessment on behalf of the National Health Service. In seeking to justify its recommendations to the NHS about which technologies to fund, NICE claims to adopt two complementary ethical frameworks, one procedural—accountability for reasonableness —and one substantive—an ‘ethics of opportunity costs’ that rests primarily on the notion of allocative efficiency. This study is the first to empirically examine normative changes to NICE’s approach and to analyse (...) whether these enhance or diminish the fairness of its decision-making, as judged against these frameworks. It finds that increasing formalisation of NICE’s approach and a weakening of the burden of proof laid on technologies undergoing HTA have together undermined its commitment to EOC. This implies a loss of allocative efficiency and a shift in the balance of how the interests of different NHS users are served, in favour of those who benefit directly from NICE’s recommendations. These changes also weaken NICE’s commitment to AfR by diminishing the publicity of its decision-making and by encouraging the adoption of rationales that cannot easily be shown to meet the relevance condition. This signals a need for either substantial reform of NICE’s approach, or more accurate communication of the ethical reasoning on which it is based. The study also highlights the need for further empirical work to explore the impact of these policy changes on NICE’s practice of HTA and to better understand how and why they have come about. (shrink)

I argue that greater attention to human agency and normativity in both researching and practicing service improvement may be one strategy for enhancing improvement science, illustrating with examples from cancer screening. Improvement science tends to deliberately avoid explicit normativity, for paradigmatically coherent reasons. But there are good reasons to consider including explicit normativity in thinking about improvement. Values and moral judgements are central to social life, so an adequate account of social life must include these elements. And improvement itself is (...) unavoidably normative: it assumes that things could and should be better than they are. I seek to show that normativity will always be implicated in the creation of evidence, the design of programs, the practice of healthcare, and in citizens’ judgements about that care, and to make a case that engaging with this normativity is worthwhile. (shrink)

In Science as Social Knowledge in 1990 and The Fate of Knowledge in 2002, Helen Longino develops an epistemological theory known as Critical Contextual Empiricism (CCE). Knowledge production, she argues, is an active, value-laden practice, evidence is context dependent and relies on background assumptions, and science is a social inquiry that, under certain conditions, produces social knowledge with contextual objectivity. While Longino’s work has been generally well-received, there have been a number of criticisms of CCE raised in the philosophical literature (...) in recent years. In this paper I outline the key elements of Longino’s theory and propose modifications to the four norms offered by the account. The version of CCE I defend, which draws on lessons learned by medical researchers in recent years, gives principles of epistemic diversity a central role and also provides greater specification of three of the four norms. Further, it offers additional resources for defending CCE against Alvin Goldman’s suggestion that there is a need for a “healthy dogmatism” in science, as well as a concern about “manufactured uncertainty” arising out of recent work by David Michaels. Finally, the modified version proposed here is also well positioned to respond (negatively) to a suggestion from Kristen Intemann that CCE needs to be adapted to incorporate a central insight from feminist standpoint theory. In light of the variety of social pressures influencing contemporary scientific research, and the role of science in shaping public policy, I argue that a rigorous social epistemology such as CCE is indispensable for understanding and assessing contemporary scientific practice. (shrink)

Robert Truog describes the controversial randomized controlled trials (RCTs) of extracorporeal membrane oxygenation (ECMO) therapy in newborns. Because early results with ECMO indicated that it might be a great advance, saving many lives, Truog argues that ECMO should not have been tested using RCTs, but that a long-term, large-scale observational study of actual clinical practice should have been conducted instead. Central to Truog’s argument, however, is the idea that ECMO is an unusual case. Thus, it is an open question whether (...) Truog’s conclusions can be extended to other areas of medical research. In this paper, I look at epistemological and ethical issues arising in the care of patients with chronic diseases, using ECMO as a starting point. Both the similarities and the dissimilarities of these two cases highlight important issues in biomedical research and support a conclusion similar to Truog’s. Observational studies of clinical practice provide the best evidence to inform the treatment of patients with chronic disease. (shrink)

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.

The purpose of this chapter is to describe what we see as several important new directions for philosophy of medicine. This recent work (i) takes existing discussions in important and promising new directions, (ii) identifies areas that have not received sufficient and deserved attention to date, and/or (iii) brings together philosophy of medicine with other areas of philosophy (including bioethics, philosophy of psychiatry, and social epistemology). To this end, the next part focuses on what we call the “epistemological turn” in (...) recent work in the philosophy of medicine; the third part addresses new developments in medical research that raise interesting questions for philosophy of medicine; the fourth part is a discussion of philosophical issues within the practice of diagnosis; the fifth part focuses on the recent developments in psychiatric classification and scientific and ethical issues therein, and the final part focuses on the objectivity of medical research. (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)

The thesis consists of an introduction and two papers. In the introduction a brief historical survey of empirical investigations into the effectiveness of medicinal interventions is given. Also, the main ideas of the EBM movement are presented. Both included papers can be viewed as investigations into the reasonableness of EBM and its hierarchies of evidence. Paper I: Typically, in a clinical trial patients with specified symptoms are given either of two or more predetermined treatments. Health endpoints in these groups are (...) then compared using statistical methods. Concerns have been raised, not least from adherents of so-called alternative medicine, that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualized treatments, for example traditional homeopathy. It is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of the two treatment groups and the elimination of confounding variables or variations. These are delineated, and a few misunderstandings are corrected. It is concluded that the conditions do not preclude the testing of alternative medicine, whether individualized or not. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in standard EBM literature, although some recent authors have argued for an upgrading. Even so, mechanistic reasoning that has received attention has almost exclusively been positive -- both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected, both in the epistemic and in the health-related sense. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition of mechanistic reasoning in the context of assessing medical interventions. Although this definition is wider than a previous suggestion in the literature, there are still other instances of reasoning that concern mechanisms but do not count as mechanistic reasoning. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Each negative type corresponds to a range of evidential strengths, and it is argued that there are differences with respect to the typical strengths. The variety of negative mechanistic reasoning should be acknowledged in EBM, and presents a serious challenge to proponents of so-called medical hierarchies of evidence. (shrink)

The thesis consists of an introduction and five papers. The introduction gives a brief historical survey of empirical investigations into the effectiveness of medicinal interventions, as well as surveys of the concept of evidence and of the history and philosophy of experiments. The main ideas of the EBM movement are also presented. Paper I: Concerns have been raised that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualised treatments, for example traditional homeopathy. (...) With respect to individualised treatments, it is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of treatment groups and the elimination of confounding variables or variations. These conditions do not preclude the testing of individualised medicine. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in the EBM literature. When discussed, mechanistic reasoning has almost exclusively been positive – both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Paper III: Evidence hierarchies are lists of investigative strategies ordered with regard to the claimed strength of evidence. They have been used for a couple of decades within EBM, particularly for the assessment of evidence for treatment recommendations, but they remain controversial. An under-investigated question is what the order in the hierarchy means. Four interpretations of the order are distinguished and discussed. The two most credible ones are, in rough terms, “typically stronger” and “ideally stronger”. The GRADE framework seems to be based on the “typically stronger” reading. Even if the interpretation of an evidence hierarchy were established, hierarchies appear to be rather unhelpful for the task of evidence aggregation. However, specifying the intended order relation may help sort out disagreements. Paper IV: There are three main arguments for randomisation that connect inseparably to theoretical concepts: Randomisation is useful for performing null hypothesis testing. Randomisation is needed for plausible causal inferences from treatment to effect. Randomisation is acceptable and computationally convenient in a Bayesian setting. A critical scrutiny of these arguments shows that is acceptable in the context of clinical trials. As for, it is argued that randomisation only provides weak reasons for drawing causal inferences in the context of real clinical trials. Argument is weak because it is controversial among Bayesians, and because formally Bayesian analyses of trial results are rarely asked for. Paper V: Practical arguments for randomisation are arguments with no necessary connections to theoretical frameworks like null hypothesis testing or causal inferences. Four common practical arguments in the context of clinical trials are distinguished and assessed: Randomisation contributes to allocation concealment. Randomisation contributes to the baseline balance of treatment groups. Randomisation decreases self-selection bias. Randomisation removes allocation bias. Argument is rejected. Arguments and are approved. Argument is rejected if it is formulated so as to be independent from and, but it is true that randomisation contributes to balance through the mechanisms mentioned in and. It is judged that may be the strongest single argument. (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)

My doctoral project is a study of epistemological and ethical issues in Evidence-Based Medicine, a movement in medicine which emphasizes the use of randomized controlled trials. Much of the research on EBM suggests that, for a large part of the movement's history, EBM considered expertise, mechanisms, and values to be forces contrary to its goals and has sought to remove them, both from medical research and from the clinical encounter. I argue, however, that expertise, mechanisms and values have important epistemological (...) and ethical roles to play and can be incorporated into the current EBM movement. (shrink)