Aida’s lecture explores how decision making is limited by a human’s capacity to process information: statistical tools can be used to incorporate more data into decision making, to support clinicians. She introduces clinical prediction models, which use a range of information to estimate the probability that a patient has a particular disease (diagnostic model), or may develop a particular health condition (prognostic model). Aida explains how to create a prediction model, using a group of patients and identifying multiple factors (predictors) to document about each patient, before observing the disease progression outcome. She discusses the example of QRISK 3, which predicts an individuals risk of cardiovascular disease over the next 10 years, and how this can support GPs in prescribing medication.
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