Ranking hospital performance based on individual indicators: can we increase reliability by creating composite indicators?
Ranking hospital performance based on individual indicators: can we increase reliability by creating composite indicators?
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DOI：
10.1186/s12874-019-0769-x
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发表时间：
2019-06-26
影响因子：
4
通讯作者：
Marang-van de Mheen, Perla J.
中科院分区：
文献类型：
--
作者：
Austin, Peter C.;Ceyisakar, Iris E.;Marang-van de Mheen, Perla J.
背景 医疗保健系统的报告卡越来越多地报告提供者在衡量医疗保健质量的指标方面的具体表现。对发布医院特定指标绩效的自然反应是创建排名表，根据绩效对医院进行排名。然而，许多指标已被证明具有低到中等的排名能力，这意味着它们不能用于准确地对医院进行排名。我们的目标是通过组合几个具有低到中等排名能力的二元指标来定义提高医院排名能力的条件。方法蒙特卡罗模拟检查通过汇集三个具有低到中等排名能力的二元指标创建的复合序数指标的排名能力。我们考虑了三个二元指标的患病率分别为 0.05、0.10 和 0.25，并且这些指标之间的院内相关性在 -0.25 和 0.90 之间变化的情景。结果当三个组成的二元指标彼此强相关时（指标的院内相关性至少为 0.5），可以创建具有高排名性的序数指标。当二元指标相互独立或弱相关时（指标的院内相关性小于0.5），复合序数指标的排序能力往往小于至少一个二元分量。综合指标的可排序性受最普遍指标的可排序性和指标之间的院内相关性大小的影响最大。结论汇集高度相关的二元指标可以产生具有高可排序性的复合序数指标。否则，复合序数指标的可排序性可能低于其某些组成部分。建议仅当二元指标代表相同的护理质量概念时才将其组合起来以提高排名。
BackgroundReport cards on the health care system increasingly report provider-specific performance on indicators that measure the quality of health care delivered. A natural reaction to the publishing of hospital-specific performance on a given indicator is to create league tables' that rank hospitals according to their performance. However, many indicators have been shown to have low to moderate rankability, meaning that they cannot be used to accurately rank hospitals. Our objective was to define conditions for improving the ability to rank hospitals by combining several binary indicators with low to moderate rankability.MethodsMonte Carlo simulations to examine the rankability of composite ordinal indicators created by pooling three binary indicators with low to moderate rankability. We considered scenarios in which the prevalences of the three binary indicators were 0.05, 0.10, and 0.25 and the within-hospital correlation between these indicators varied between -0.25 and 0.90.ResultsCreation of an ordinal indicator with high rankability was possible when the three component binary indicators were strongly correlated with one another (the within-hospital correlation in indicators was at least 0.5). When the binary indicators were independent or weakly correlated with one another (the within-hospital correlation in indicators was less than 0.5), the rankability of the composite ordinal indicator was often less than at least one of its binary components. The rankability of the composite indicator was most affected by the rankability of the most prevalent indicator and the magnitude of the within-hospital correlation between the indicators.ConclusionsPooling highly-correlated binary indicators can result in a composite ordinal indicator with high rankability. Otherwise, the composite ordinal indicator may have lower rankability than some of its constituent components. It is recommended that binary indicators be combined to increase rankability only if they represent the same concept of quality of care.