论文标题
多层质量指标（MQI）：方法和蒙特卡洛证据
Multilevel Quality Indicators (MQI): Methodology and Monte Carlo evidence
论文作者
论文摘要
背景：质量指标经常用于评估医疗保健提供者，特别是医院的表现。由于间接的标准化和估计器的较高差异，建立的此类指标设计方法可能会扭曲。很少考虑地理区域的指标。 目标：为医疗保健提供者和地理区域开发和评估多级质量指标（MQI）的方法。 研究设计：我们从统计多级模型中正式得出MQI，该模型可能包括患者，提供者和地区的特征。我们使用蒙特卡洛模拟来评估基于标准化死亡率/发病率（SMR）和风险标准化死亡率（RSMR）的MQI相对于已建立方法的性能。 措施：真正的提供商/地区效应与质量指标估计值之间的等级相关性；质量指标确定的10％最佳和10％最差的提供商的股份。 结果：拟议的MQI是1）标准化的医院结局率（SHOR），2）区域Shor（RSHOR）和3）区域标准化患者结局率（RSPOR）。 Monte Carlo模拟表明，在几乎所有情况下，SHOR提供了比SMR和RSMR的提供商性能的估计值得得多。 RSPOR比区域SMR略有稳定。我们还发现，区域特征的建模通常可以提高提供者级别估计值的充分性。 结论：MQI方法论促进了医疗保健提供者和地理区域的质量指标的足够有效估计。
Background: Quality indicators are frequently used to assess the performance of healthcare providers, in particular hospitals. Established approaches to the design of such indicators are subject to distortions due to indirect standardization and high variance of estimators. Indicators for geographical regions are rarely considered. Objectives: To develop and evaluate a methodology of Multilevel Quality Indicators (MQI) for both healthcare providers and geographical regions. Research Design: We formally derived MQI from a statistical multilevel model, which may include characteristics of patients, providers, and regions. We used Monte Carlo simulation to assess the performance of MQI relative to established approaches based on the standardized mortality/morbidity ratio (SMR) and the risk-standardized mortality rate (RSMR). Measures: Rank correlation between true provider/region effects and quality indicator estimates; shares of the 10% best and 10% worst providers identified by the quality indicators. Results: The proposed MQI are 1) standardized hospital outcome rate (SHOR), 2) regional SHOR (RSHOR), and 3) regional standardized patient outcome rate (RSPOR). Monte Carlo simulations indicated that the SHOR provides substantially better estimates of provider performance than the SMR and RSMR in almost all scenarios. RSPOR was slightly more stable than the regional SMR. We also found that modeling of regional characteristics generally improves the adequacy of provider-level estimates. Conclusions: MQI methodology facilitates adequate and efficient estimation of quality indicators for both healthcare providers and geographical regions.
