Journal of evaluation in clinical practice
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Evidence-based medicine (EBM), one of the most important movements in health care, has been a lightning rod for controversy. Conflicts about the meaning and value of EBM are owing in part to lack of clarity about basic questions regarding its development, the importance of expertise and intuition, and the role of evidence in clinical decision making. These issues have persisted in part because of unclarity at the outset, but also because of how EBM evolved, why it was introduced when it was, and how it was modified following its introduction. ⋯ The paper discusses the impact of this merger, in particular how it led to EBM's identification with managed care and has added momentum to the effort at forging a connection between a normative decision model and clinical judgement. This effort would turn clinical decision making into a conduit for bringing administrative rules and regulations into the consulting room and would result in expertise becoming a surplus skill. The paper closes by discussing a challenge yet unmet by EBM's advocates and critics-to chronicle the dangers that EBM in the framework of DA during the current era of industrialization poses to health and health care, and discover ways of unhinging the relationship between model and judgement.
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In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. ⋯ The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making.
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Parts 1 and 2 in this series of three articles have shown that and how strong evidence-based medicine has neither a coherent theoretical foundation nor creditable application to clinical practice. Because of its core commitment to the discredited positivist tradition it holds both a false concept of scientific knowledge and misunderstandings concerning clinical decision-making. Strong EBM continues attempts to use flawed adjustments to recover from the unsalvageable base view. ⋯ While most of papers 1, 2, and 3 are written in the classical mode of contrasting the theoretical-logical and empirical evidence offered by contending positions bearing on the decision making and judgement in clinical practice, a shift occurs when considerations move beyond what is possible for clinical practitioners to accomplish. A different, discontinuous level of power operates in the trans-personal realm of instrumental policy, insurance, and hospital management practices. In this social-economic-political-ethical realm what happens in clinical practice today increasingly becomes a matter of what is "done unto" clinical practitioners, of what hampers their professional action and thus care of individual patients and clients.