Section of Thoracic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan; Center for Health Outcomes and Policy, University of Michigan, Ann Arbor, Michigan.
Center for Health Outcomes and Policy, University of Michigan, Ann Arbor, Michigan.
Ann Thorac Surg. 2022 Jul;114(1):225-232. doi: 10.1016/j.athoracsur.2022.02.028. Epub 2022 Mar 2.
In the United States, the Organ Procurement and Transplant Network (OPTN) uses 1-year mortality as the primary measure of transplant center quality. We sought to evaluate the reliability of mortality outcomes in lung transplantation and to compare statistical methods of program performance evaluation.
We used the Standard Transplant Analysis and Research files from the United Network for Organ Sharing to identify lung transplant recipients from 2013 to 2018 in the United States. We stratified hospitals on the basis of 30-day, 1-year, and 5-year survival by risk adjustment, reliability adjustment with empirical Bayes technique, and hierarchical bayesian mixed effects models currently used by the OPTN. We measured variation in mortality rates and identification of performance outliers between techniques.
We identified 12,769 recipients in 69 centers. Reliability adjustment reduced variation in hospital outcomes and had a large impact on hospital mortality rankings. For example, with 1-year mortality, 28% (5 hospitals) of the "best" hospitals (top 25%) and 18% (3 hospitals) of the "worst" hospitals (bottom 25%) were reclassified after reliability adjustment. The overall reliability of 1-year mortality was low at 0.42. Compared with the bayesian method used by the OPTN, reliability adjustment identified fewer outliers. The 5-year survival reached a higher reliability plateau with a lower volume of cases required.
The reliability of 1-year mortality in lung transplantation is low, whereas 5-year survival estimates may be more reliable at lower case volumes. Reliability adjustment yielded more conservative measures of center performance and fewer outliers compared with current bayesian methods.
在美国,器官获取与移植网络(OPTN)使用 1 年死亡率作为移植中心质量的主要衡量标准。我们试图评估肺移植死亡率结果的可靠性,并比较程序绩效评估的统计方法。
我们使用美国器官共享联合网络的标准移植分析和研究文件,确定了 2013 年至 2018 年在美国进行的肺移植受者。我们根据风险调整、使用经验贝叶斯技术的可靠性调整以及 OPTN 当前使用的分层贝叶斯混合效应模型,对 30 天、1 年和 5 年生存率进行分层。我们衡量了不同技术之间死亡率和绩效异常值的变化。
我们在 69 个中心确定了 12769 名受者。可靠性调整降低了医院结果的变异性,并对医院死亡率排名产生了重大影响。例如,在 1 年死亡率方面,经过可靠性调整后,“最佳”医院(前 25%)中有 28%(5 家医院)和“最差”医院(后 25%)中有 18%(3 家医院)被重新分类。1 年死亡率的总体可靠性较低,为 0.42。与 OPTN 使用的贝叶斯方法相比,可靠性调整确定的异常值较少。5 年生存率达到了更高的可靠性平台,所需的病例量更少。
肺移植 1 年死亡率的可靠性较低,而 5 年生存率估计在病例量较少时可能更可靠。与当前的贝叶斯方法相比,可靠性调整产生了更保守的中心绩效衡量标准和更少的异常值。