Zalkind D L, Eastaugh S R
Department of Management Science, George Washington University, Washington, DC 20052, USA.
Hosp Health Serv Adm. 1997 Spring;42(1):3-15.
This study examines the relationship between outlier status based on adjusted mortality rates and theoretical underlying quality of care in hospitals. We use Monte Carlo stimulation to determine, in the absence of case mix variation, if random variation noise could obscure the signal of differences in underlying rates of quality of care problems. Classification of hospitals as "outliers" is done compared with "true" hospital quality, based on underlying rates for quality of care problems in mortality cases. Predictive error rates with respect to "quality" for both "outlier" and "non-outlier" hospitals are substantial under a variety of patient load and cutoff point choices for determining outlier status. Using overall death rates as an indicator of underlying quality of care problems may lead to substantial predictive error rates, even when adjustment for case mix is excellent. Outlier status should only be used as a screening tool and not as the information provided to the public to make informed choices about hospitals.
本研究探讨了基于调整后死亡率的异常值状态与医院理论上的潜在医疗质量之间的关系。我们使用蒙特卡罗模拟来确定，在不存在病例组合差异的情况下，随机变异噪声是否会掩盖潜在医疗质量问题发生率差异的信号。根据死亡率病例中医疗质量问题的潜在发生率，将医院分类为“异常值”并与“真实”医院质量进行比较。在确定异常值状态的各种患者负荷和临界点选择下，“异常值”和“非异常值”医院在“质量”方面的预测错误率都很高。即使对病例组合进行了出色的调整，使用总体死亡率作为潜在医疗质量问题的指标也可能导致很高的预测错误率。异常值状态仅应用作筛选工具，而不应作为向公众提供的信息，以便他们对医院做出明智的选择。
