Hu Guizhou, Root Martin
BioSignia Inc., 1822 E. NC Highway 54, Suite 350, Durham, NC 27713, USA.
Dis Manag. 2005 Feb;8(1):42-7. doi: 10.1089/dis.2005.8.42.
There has been a significantly increased interest in the adoption of prediction modeling by many disease and case management programs to risk stratify members in order to optimize the utilization of available clinical resources. Before adopting any prediction model, it is critical to understand how to evaluate the model's accuracy. This paper explains the basic concepts of prediction accuracy, the relevant parameters, their drawbacks, and their interpretations. It also introduces a new accuracy parameter termed "cost concentration," which indicates the model accuracy more explicitly in the context of disease management.
许多疾病和病例管理项目对采用预测模型进行风险分层以优化可用临床资源的利用表现出了显著增加的兴趣。在采用任何预测模型之前，了解如何评估模型的准确性至关重要。本文解释了预测准确性的基本概念、相关参数、它们的缺点及其解释。它还引入了一个新的准确性参数，称为“成本集中度”，该参数在疾病管理背景下更明确地表明了模型的准确性。
