Relationship Between Perioperative Outcomes Used for Profiling Hospital Noncardiac Surgical Quality.
Relationship Between Perioperative Outcomes Used for Profiling Hospital Noncardiac Surgical Quality.
复制标题
用于分析医院非心脏手术质量的围手术期结果之间的关系。
DOI：
10.1016/j.jss.2021.02.004
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Petersen,LauraA
中科院分区：
文献类型：
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作者：
Massarweh,NaderN;Chen,ViviW;Rosen,Tracey;Richardson,PeterA;Harris,AlexHS;Petersen,LauraA
风险调整后的发病率和死亡率通常被国家外科质量改进(QI)项目用来衡量医院级的手术质量。然而，现代外科QI计划收集的死亡率、发病率和其他围手术期结果(如再手术)之间的医院水平相关性程度尚未得到很好的表征。材料和方法使用退伍军人事务部(VA)外科质量改进计划(VASQIP)的数据(2015-2016)，评估风险调整后的30d死亡率、发病率、主要发病率、再手术与非心脏手术后2种综合结果(1-死亡率、主要发病率或再手术；2-死亡率或主要发病率)之间的医院级相关性。用皮尔逊相关系数评价转化率之间的相关性。结果基于VASQIP提取的232例季度手术病例的中位数，用于识别30天死亡率异常医院的统计能力估计在3.3%(观察与预期比率为1.1)和45.7%(观察与预期比率为3.0)之间。在137家退伍军人医院接受非心脏手术的230,247名退伍军人中，各种风险调整后的结局比率在医院层面上存在中等程度的相关性(最高的相关系数=0.40，死亡率和综合指数1；最低的相关系数=0.32，死亡率和发病率)。当医院根据表现进行排名时，不同结果的排名之间存在低到中等的相关性(最高ρ=100.47，死亡率和综合1；最低ρ=100.37，死亡率和主要发病率)。结论围手术期结果之间最典型的医院水平相关性表明，使用单一衡量标准可能很难识别表现良好(或低)的医院。此外，虽然综合目前测量的结果可能是提高分析样本量的有效方法(相对于基于任何单个结果的评估)，但还需要进一步的工作来了解它们是否提供了更稳健和准确的医院质量图景，或者评估一系列单独测量的绩效是否对推动QI最有效。
BackgroundRisk-adjusted morbidity and mortality are commonly used by national surgical quality improvement (QI) programs to measure hospital-level surgical quality. However, the degree of hospital-level correlation between mortality, morbidity, and other perioperative outcomes (like reoperation) collected by contemporary surgical QI programs has not been well-characterized.Materials and MethodsVeterans Affairs (VA) Surgical Quality Improvement Program (VASQIP) data (2015-2016) were used to evaluate hospital-level correlation in performance between risk-adjusted 30-d mortality, morbidity, major morbidity, reoperation, and 2 composite outcomes (1- mortality, major morbidity, or reoperation; 2- mortality or major morbidity) after noncardiac surgery. Correlation between outcomes rates was evaluated using Pearson's correlation coefficient. Correlation between hospital risk-adjusted performance rankings was evaluated using Spearman's correlation.ResultsBased on a median of 232 [IQR 95-331] quarterly surgical cases abstracted by VASQIP, statistical power for identifying 30-d mortality outlier hospitals was estimated between 3.3% for an observed-to-expected ratio of 1.1 and 45.7% for 3.0. Among 230,247 Veterans who underwent a noncardiac operation at 137 VA hospitals, there were moderate hospital-level correlations between various risk-adjusted outcome rates (highest r = 0.40, mortality and composite 1; lowest r = 0.32, mortality and morbidity). When hospitals were ranked based on performance, there was low-to-moderate correlation between rankings on the various outcomes (highest ρ = 0.47, mortality and composite 1; lowest ρ = 0.37, mortality and major morbidity).ConclusionsModest hospital-level correlations between perioperative outcomes suggests it may be difficult to identify high (or low) performing hospitals using a single measure. Additionally, while composites of currently measured outcomes may be an efficient way to improve analytic sample size (relative to evaluations based on any individual outcome), further work is needed to understand whether they provide a more robust and accurate picture of hospital quality or whether evaluating performance across a portfolio of individual measures is most effective for driving QI.