
AbstractThe recent sacking of Peter Gøtzsche from the Cochrane Collaboration Board raised strong responses and highlights the neglected issue about priorities—maintaining the reputation of the organization or vigorously debating the merits of scientific approaches to find answers to complex problems? The Cochrane approach hales the randomized trial (RCT) as the gold standard research approach and affirms that meta‐analysis provides the ultimate proof (or platinum standard) to settle contentious issues confronting the clinician. However, most published medical research is wrong, and critics coined the acronym GIGO (garbage in, garbage out) as a meme to highlight the risks of blind faith in the hyped‐up procedures of the EBM movement.This paper firstly explores the differences between the prevailing scientific method arising from the linear cause‐and‐effect assumption and the complex adaptive systems science methods arising from observations that most phenomena emerge from nonlinearity in networked systems. Most medical conditions are characterized by necessary features that by themselves are not sufficient to explain their nature and behaviour. Such nonlinear phenomena require modelling approaches rather than linear statistical and/or meta‐analysis approaches to be understood. These considerations also highlight that research is largely stuck at the data and information levels of understanding which fails clinicians who depend on knowledge—the synthesis of information—to apply in an adaptive way in the clinical encounter.Clinicians are constantly confronted with the linked challenges of doing things right and doing the right thing for their patients. EBM and Cochrane with their restrictive approaches are the antithesis to a practice of medicine that is responsive to constantly changing patient needs. As such, the EBM/Cochrane crisis opens a window of opportunity to re‐examine the nature of health, illness and disease, and the nature of health care and its systems for the benefits of its professionals and their patients. We are at the cusp of a paradigmatic shift towards an understanding a praxis of health care that takes account of its complexities.
Biomedical Research, Evidence-Based Medicine, Models, Statistical, 170, Clinical Decision-Making, Standard of Care, hyped-up procedures, Patient Care Planning, meta-analysis, Meta-Analysis as Topic, Research Design, proof, Outcome Assessment, Health Care, Humans, complex problems, Quality of Health Care, Randomized Controlled Trials as Topic
Biomedical Research, Evidence-Based Medicine, Models, Statistical, 170, Clinical Decision-Making, Standard of Care, hyped-up procedures, Patient Care Planning, meta-analysis, Meta-Analysis as Topic, Research Design, proof, Outcome Assessment, Health Care, Humans, complex problems, Quality of Health Care, Randomized Controlled Trials as Topic
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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