ICES, G106, 2075 Bayview Avenue, Toronto, Ontario, Canada.
Department of Public Health, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
BMC Med Res Methodol. 2019 Jun 26;19(1):131. doi: 10.1186/s12874-019-0769-x.
Report 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.
Monte 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.
Creation 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.
Pooling 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.
医疗系统的绩效报告越来越多地报告提供特定服务的机构在衡量所提供医疗服务质量的指标上的表现。发布特定医院在特定指标上的表现后，人们自然会想到根据绩效对医院进行排名，创建“排行榜”。然而，许多指标的可排名性都较低或中等，这意味着它们无法准确地对医院进行排名。我们的目标是定义通过结合几个低到中等可排名性的二进制指标来提高医院排名能力的条件。
使用蒙特卡罗模拟来检查通过组合三个低到中等可排名性的二进制指标创建的组合有序指标的可排名性。我们考虑了以下情况：三个二进制指标的流行率分别为 0.05、0.10 和 0.25，并且这些指标之间的医院内相关性在-0.25 到 0.90 之间变化。
当三个组成的二进制指标彼此高度相关时（指标之间的医院内相关性至少为 0.5），创建高可排名性的有序指标是可能的。当二进制指标彼此独立或弱相关时（指标之间的医院内相关性小于 0.5），组合有序指标的可排名性通常低于至少一个其组成的二进制指标。组合指标的可排名性受最流行指标的可排名性和指标之间的医院内相关性的大小影响最大。
组合高度相关的二进制指标可以得到具有高可排名性的组合有序指标。否则，组合有序指标的可排名性可能低于其组成部分中的一些。建议仅在二进制指标代表相同的护理质量概念时，才将它们组合以提高可排名性。
