Statistical Prediction Models Bayes' theorem, as presented above, deals with a clinical prediction problem that is unrealistically simple relative to most problems a clinician faces. Prediction models, based on multivariable statistical models, can handle much more complex problems and substantially enhance predictive accuracy for specific situations. Their particular advantage is the ability to take into account many overlapping pieces of information and assign a relative weight to each based on its unique contribution to the prediction in question. For example, a logistic regression model to predict the probability of CAD takes into account all of the relevant independent factors from. | Chapter 003. Decision-Making in Clinical Medicine Part 8 Statistical Prediction Models Bayes theorem as presented above deals with a clinical prediction problem that is unrealistically simple relative to most problems a clinician faces. Prediction models based on multivariable statistical models can handle much more complex problems and substantially enhance predictive accuracy for specific situations. Their particular advantage is the ability to take into account many overlapping pieces of information and assign a relative weight to each based on its unique contribution to the prediction in question. For example a logistic regression model to predict the probability of CAD takes into account all of the relevant independent factors from the clinical examination and diagnostic testing instead of the small handful of data that clinicians can manage in their heads or with Bayes theorem. However despite this strength the models are too complex computationally to use without a calculator or computer although this limit may be overcome once medicine is practiced from a fully computerized platform . To date only a handful of prediction models have been properly validated. The importance of independent validation in a population separate from the one used to develop the model cannot be overstated. An unvalidated prediction model should be viewed with the same skepticism appropriate for a new drug or medical device that has not been through rigorous clinical trial testing. When statistical models have been compared directly with expert clinicians they have been found to be more consistent as would be expected but not significantly more accurate. Their biggest promise then would seem to be to make less-experienced clinicians more accurate predictors of outcome. Decision Support Tools Decision Support Systems Over the past 35 years many attempts have been made to develop computer systems to help clinicians make decisions and manage patients. Conceptually computers offer a .
