Evaluating trauma center quality: Does the choice of the severity-adjustment model make a difference?
Evaluating trauma center quality: Does the choice of the severity-adjustment model make a difference?
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DOI：
10.1097/01.ta.0000169429.58786.c6
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发表时间：
2005-06-01
影响因子：
--
通讯作者：
Dick, AW
中科院分区：
文献类型：
--
作者：
Glance, LG;Osler, TM;Dick, AW
背景：主要创伤结局研究（MTOS）数据库是由美国外科医师学会在20多年前创建的，目的是建立创伤护理的国家规范。使用MTOS数据库开发了用于评估创伤护理质量的主要创伤结局预测模型TRISS和ASCOT（创伤严重程度表征）。首先，确定TRISS和ASCOT对医院质量的看法是否一致。其次，确定TRISS和ASCOT是否准确反映了当代创伤护理的结果。设计，环境和病人。一项基于国家创伤数据库2000年至2001年间69家医院收治的91112名患者的回顾性队列研究。采用TRISS和ASCOT，计算各医院的观察死亡率与预期死亡率之比（O/E ratio）。0 /E比与1有统计学差异的医院为质量异常值。采用Kappa分析来评估TRISS和ASCOT在医院质量异常值识别上的一致程度。TRISS和ASCOT对69家医院中35家的异常状况意见不一致。Kappa分析显示TRISS和ASCOT在识别质量异常值方面只有一般的一致性（Kappa = 0.23; p = 0.0015）。通过TRISS方法确定38家医院为高绩效医院。结论：首先，TRISS和ASCOT在NTDB中质量异常值的身份上表现出实质性的分歧。其次，使用TRISS或ASCOT将大量医院确定为高性能异常值。这些发现对使用TRISS和ASCOT进行基准性能和质量改进具有重要意义。
Context: The Major Trauma Outcome Study (MTOS) database was created by the American College of Surgeons over 20 years ago to establish national norms for trauma care. The primary trauma outcome prediction models used for evaluating the quality of trauma care, TRISS and ASCOT (A Severity Characterization of Trauma), were developed using the MTOS database.Objective. First, to determine whether TRISS and ASCOT agree on hospital quality. Second, to determine whether TRISS and ASCOT accurately reflect contemporary outcomes in trauma care.Design, Setting and Patients. A retrospective cohort study based on 91,112 patients admitted to 69 hospitals between 2000 and 2001 in the National Trauma Databank. Using TRISS and ASCOT, the ratio of the observed to expected mortality rate (O/E ratio) was calculated for each hospital. Hospitals whose O/E ratio was statistically different from 1 were identified as quality outliers. Kappa analysis was used to assess the degree to which TRISS and ASCOT agreed on the identity of hospital quality outliers.Results:. TRISS and ASCOT disagreed on the outlier status of 35 of the 69 hospitals. Kappa analysis revealed only fair agreement (kappa = 0.23; p = 0.0015) between TRISS and ASCOT in identifying quality outliers. Thirty-eight hospitals were identified by the TRISS method as high-performance hospitals.Conclusion: First, TRISS and ASCOT exhibit substantial disagreement on the identity of quality outliers within the NTDB. Second, an unrealistically high number of hospitals were identified as high-performance outliers using either TRISS or ASCOT. These findings have important implications for the use of TRISS and ASCOT for benchmarking performance and quality improvement.