Systematic Noise in Medicine
The latest book from Nobel Laureate Daniel Kahneman, Olivier Siboni and Cass Sunstien discusses random factors that cause decisions to deviate from best practice. The book addresses the complexities of using algorithms to reduce such noise.
Avoiding such systemic noise is an aim of evidence based medicine that uses objective and reproducible evidence to inform decision makers about the right cause of action, despite any personal biases they may have. The field of medicine is full of decisions about individuals who are all different from each other and so the amount of reliable evidence required to support decisions is incomprehensible; Medicine suffers from a crisis-level shortage of evidence.
Ironically, a large contributor to this shortage is more systemic noise and unwarranted variation among researchers.
Evidentli is on a mission to address these issues by reducing noise. For example, at least 80% of clinical studies have established methodology. Piano enables clinicians, researchers, epidemiologists and healthcare administrators without advanced training in data science, statistics or AI to conduct such research using drag-and-drop UI with clincal (not data science) terms in minutes not months. These studies follow best practice research and are instantly reproducible.
Noise: a flaw in human judgment, 2021, Daniel Kahneman, Olivier Siboni and Cass R. Sunstien
Unwarranted clinical variation in health care: Definitions and proposal of an analytic framework, Jean-Frederic Levesque
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