Reducing Bias and Increasing Diagnostic Utility Through Diagnostic Risk Models
View Presentation *Frank Eanes Harrell, Vanderbilt University Keywords: diagnostic model,diagnostic utility Medical diagnostic research is prone to bias and even more importantly to yielding information that is not useful to patients or physicians and sometimes overstates the value of diagnostics. Problems include conditioning on the wrong statistical information, reversing the flow of time, and categorization of inherently continuous test outputs and disease severity. Sensitivity, specificity, and ROC curves are highly problematic. So is categorical thinking. The many advantages of diagnostic risk modeling will be discussed, and this talk will show how pre- and post-test diagnostic models give rise to clinically useful displays that quantify diagnostic utility in a way that is useful to patients, physicians, and diagnostic device makers. And unlike sensitivity and specificity, post-test probabilities are immune to certain biases, including workup bias.
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Key Dates
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April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
Housing Deadline -
September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC