Journal of evaluation in clinical practice
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One of the sectors challenged by the COVID-19 pandemic is medical research. COVID-19 originates from a novel coronavirus (SARS-CoV-2) and the scientific community is faced with the daunting task of creating a novel model for this pandemic or, in other words, creating novel science. This paper is the first part of a series of two papers that explore the intricate relationship between the different challenges that have hindered biomedical research and the generation of scientific knowledge during the COVID-19 pandemic. ⋯ The COVID-19 pandemic presented challenges in terms of (1) finding and prioritising relevant research questions and (2) choosing study designs that are appropriate for a time of emergency.
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Despite the great promises that artificial intelligence (AI) holds for health care, the uptake of such technologies into medical practice is slow. In this paper, we focus on the epistemological issues arising from the development and implementation of a class of AI for clinical practice, namely clinical decision support systems (CDSS). We will first provide an overview of the epistemic tasks of medical professionals, and then analyse which of these tasks can be supported by CDSS, while also explaining why some of them should remain the territory of human experts. ⋯ In practice, this means that the system indicates what factors contributed to arriving at an advice, allowing the user (clinician) to evaluate whether these factors are medically plausible and applicable to the patient. Finally, we defend that proper implementation of CRSS allows combining human and artificial intelligence into hybrid intelligence, were both perform clearly delineated and complementary empirical tasks. Whereas CRSSs can assist with statistical reasoning and finding patterns in complex data, it is the clinicians' task to interpret, integrate and contextualize.
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In today's culture of the medical profession, it is fairly unusual for students to actually witness physicians talking with patients about anything outside scientific explanation. That other side of medicine - the one that goes beyond explanation to understanding - goes unexplored, and the patient's personal narrative is consequently less understood. Meanwhile, though reflective writing is the most frequently used didactic method to promote introspection and deeper consolidation of new ideas for medical learners, there is robust evidence that other art forms - such as storytelling, dance, theatre, literature and the visual arts - can also help deepen reflection and understanding of the human aspect of medical practice. ⋯ BEAM is envisioned as a modular, online resource of "third things" that any clinician anywhere will be able to access via a smartphone application to deliver brief, focused, humanistic clinical teaching in either hospital or ambulatory care settings. This commentary foregrounds a learner's perspective to model BEAM's usage in an in-depth manner; it examines the relation of a painting by Edward Hopper to medical education through the lens of a poem by Victoria Chang, in the context of the BEAM web-based app educational resource. By assessing the poignancy of the painting via the poem, I demonstrate the capacity of the arts and humanities in medical education, with a specific focus on the development of interpretative skills and tolerance for ambiguity that all authentic, engaged physicians need.
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Conventional models of cultural humility - even those extending analysis beyond the dyad of healthcare provider-patient to include concentric social influences such as families, communities and institutions that make clinical relationships possible - aren't conceptually or methodologically calibrated to accommodate shifts occurring in contemporary biomedical cultures. More complex methodological frameworks are required that are attuned to how advances in biomedical, communications and information technologies are increasingly transforming the very cultural and material conditions of health care and its delivery structures, and thus how power manifests in clinical encounters. ⋯ Engaging evaluative inquiry diffractively allows for a different ethical practice of care, one that attends to the forms of patient and health provider accountability and responsibility emerging in the clinical encounter.
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Evidence-based medicine (EBM), the dominant approach to assessing the effectiveness of clinical and public health interventions, focuses on the results of association studies. EBM+ is a development of EBM that systematically considers mechanistic studies alongside association studies. ⋯ (a) Assessment of combination therapy for MERS highlights the need for systematic assessment of mechanistic evidence. (b) That hypertension is a risk factor for severe disease in the case of SARS-CoV-2 suggests that altering hypertension treatment might alleviate disease, but the mechanisms are complex, and it is essential to consider and evaluate multiple mechanistic hypotheses. (c) Confidence that public health interventions will be effective requires a detailed assessment of social and psychological components of the mechanisms of their action, in addition to mechanisms of disease. (d) In particular, if vaccination programmes are to be effective, they must be carefully tailored to the social context; again, mechanistic evidence is crucial. We conclude that coronavirus research is best situated within the EBM+ evaluation framework.