Context Urologists regularly develop clinical risk prediction models to support clinical
decisions. In contrast to traditional performance measures, decision curve analysis (DCA) …

Models—mathematical frameworks that facilitate estimation of the consequences of health
care decisions—have become essential tools for health technology assessment. Evolution …

Background Decision curve analysis is a method to evaluate prediction models and
diagnostic tests that was introduced in a 2006 publication. Decision curves are now …

A goal of many health studies is to determine the causal effect of a treatment or intervention
on health outcomes. Often, it is not ethically or practically possible to conduct a perfectly …

State-transition modeling (STM) is an intuitive, flexible, and transparent approach of
computer-based decision-analytic modeling, including both Markov model cohort simulation …

Background Physicians routinely encounter diagnostic uncertainty in practice. Despite its
impact on health care utilization, costs and error, measurement of diagnostic uncertainty is …

The purpose of economic evaluation is to inform decisions intended to improve healthcare.
The new edition of Methods for the Economic Evaluation of Health Care Programmes equips …

Background. Diagnostic and prognostic models are typically evaluated with measures of
accuracy that do not address clinical consequences. Decision-analytic techniques allow …

The Internet of Things (IoT) envisions a world-wide, interconnected network of smart
physical entities. These physical entities generate a large amount of data in operation, and …

Background Sensitivity analyses play a crucial role in assessing the robustness of the
findings or conclusions based on primary analyses of data in clinical trials. They are a critical …