From pre-test and post-test probabilities to medical decision making.

ABSTRACT:

Background

A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive.

Metho

SUBMITTER: Nixon MP 

PROVIDER: S-EPMC11285418 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature