title: For every complex problem, there is an answer that is clear, simple and wrong: and other aphorisms about medical statistical fallacies.
abstract: This essay examines the notions of knowledge, truth and certainty as they apply to medical research and patient care. The human body does not behave in mechanistic but rather complex adaptive ways; thus, its behaviour to challenges is non-deterministic. This insight has important ramifications for experimental studies in health care and their statistical interrogation that are described in detail.
  
  
  CONCLUSIONS
  Four implications are highlighted: one, there is an urgent need to develop a greater awareness of uncertainties and how to respond to them in clinical practice, namely, what is important and what is not in the context of this patient; two, there is an equally urgent need for health professionals to understand some basic statistical terms and their meanings, specifically absolute risk, its reciprocal, numbers needed to treat and its inverse, index of therapeutic impotence, as well as seeking out the effect size of an intervention rather than blindly accepting P-values; three, there is an urgent need to accurately present the known in comprehensible ways through the use of visual tools; and four, there is a need to overcome the perception, that errors of commission are less troublesome than errors of omission as neither's consequences are predictable.
authors.affiliation: Newcastle University, Australia.
authors.forename: Joachim
authors.initials: J
authors.lastname: Sturmberg
authors.forename: Stefan
authors.initials: S
authors.lastname: Topolski
mesh_terms: D001045:Aphorisms and Proverbs as Topic; D019317:Evidence-Based Medicine / Q000266:history*; D005260:Female; D049668:History, 15th Century; D049669:History, 16th Century; D049670:History, 17th Century; D049671:History, 18th Century; D049672:History, 19th Century; D049673:History, 20th Century; D049691:History, Medieval; D006801:Humans; D008297:Male
keywords: complex adaptive systems; evaluation; evidence-based medicine; knowledge; nonlinear dynamics; patient-centred care; risk