Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey VA Medical Center, Houston, Texas; Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas; Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Texas.
Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
J Surg Res. 2021 Aug;264:58-67. doi: 10.1016/j.jss.2021.02.004. Epub 2021 Mar 26.
Risk-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.
Veterans 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.
Based 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).
Modest 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.
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）计划用于衡量医院级别的外科质量。然而，当代外科 QI 计划所收集的死亡率、发病率和其他围手术期结果（如再次手术）的医院水平相关性程度尚未得到很好的描述。
使用退伍军人事务部（VA）外科质量改进计划（VASQIP）数据（2015-2016 年）评估非心脏手术后风险调整后 30 天死亡率、发病率、主要发病率、再次手术以及 2 种复合结局（1-死亡率、主要发病率或再次手术；2-死亡率或主要发病率）之间的医院水平相关性。使用 Pearson 相关系数评估结局发生率之间的相关性。使用 Spearman 相关系数评估医院风险调整绩效排名之间的相关性。
根据 VASQIP 每季度平均 232 例（IQR 95-331）手术病例的中位数，确定 30 天死亡率异常医院的观察到的与预期比值为 1.1 时的观察到的与预期比值为 3.0 时的统计能力估计分别为 3.3%和 45.7%。在接受 137 家 VA 医院非心脏手术的 230247 名退伍军人中，各种风险调整后结局率之间存在中度的医院水平相关性（最高 r=0.40，死亡率和复合 1；最低 r=0.32，死亡率和发病率）。当根据绩效对医院进行排名时，各种结局的排名之间存在低到中度的相关性（最高 ρ=0.47，死亡率和复合 1；最低 ρ=0.37，死亡率和主要发病率）。
围手术期结局之间的适度医院水平相关性表明，使用单一指标可能难以确定表现良好（或表现不佳）的医院。此外，虽然目前测量结果的组合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），但需要进一步研究，以了解它们是否提供了医院质量的更稳健和准确的图景，或者评估单个措施组合的绩效是否最有利于推动 QI。
