Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.

译文

诊断或预测准确性问题在疾病管理(DM)计划的所有阶段中都很常见,最终在评估计划有效性中起着重要作用。诸如疾病患者的识别,未来健康状况和成本的预测模型以及风险分层等领域只是对准确性进行评估(即使不是很重要)的几个领域。为此目的,最常用的分析模型是标准的2 x 2表格方法,在其中计算灵敏度和特异性。但是,这种方法存在一些局限性,包括依赖单个定义的标准或确定真实阳性结果的临界值,使用非标准化的测量工具以及对结果普遍性的敏感性。本文介绍了接收机操作员特征(ROC)分析,这是一种用于评估DM诊断和预测准确性的更合适和有用的技术。它的优点包括:整个评分范围内的测试准确性,因此不需要预定的临界点,可以轻松检查跨测试或评分的视觉和统计比较,并且不受结局患病率影响。因此,应在DM计划的各个阶段中强烈考虑将ROC用作评估工具。

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