American College of Surgeons, Division of Research and Optimal Patient Care, Chicago, IL.
University of Chicago Medical Center, Department of Surgery, Chicago, IL.
Ann Surg. 2018 Jul;268(1):93-99. doi: 10.1097/SLA.0000000000002436.
To explore hospital-level variation in postoperative delirium using a multi-institutional data source.
Postoperative delirium is closely related to serious morbidity, disability, and death in older adults. Yet, surgeons and hospitals rarely measure delirium rates, which limits quality improvement efforts.
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Geriatric Surgery Pilot (2014 to 2015) collects geriatric-specific variables, including postoperative delirium using a standardized definition. Hierarchical logistic regression models, adjusted for case mix [Current Procedural Terminology (CPT) code] and patient risk factors, yielded risk-adjusted and smoothed odds ratios (ORs) for hospital performance. Model performance was assessed with Hosmer-Lemeshow (HL) statistic and c-statistics, and compared across surgical specialties.
Twenty thousand two hundred twelve older adults (≥65 years) underwent inpatient operations at 30 hospitals. Postoperative delirium occurred in 2427 patients (12.0%) with variation across specialties, from 4.7% in gynecology to 13.7% in cardiothoracic surgery. Hierarchical modeling with 20 risk factors (HL = 9.423, P = 0.31; c-statistic 0.86) identified 13 hospitals as statistical outliers (5 good, 8 poor performers). Per hospital, the median risk-adjusted delirium rate was 10.4% (range 3.2% to 27.5%). Operation-specific risk and preoperative cognitive impairment (OR 2.9, 95% confidence interval 2.5-3.5) were the strongest predictors. The model performed well across surgical specialties (orthopedic, general surgery, and vascular surgery).
Rates of postoperative delirium varied 8.5-fold across hospitals, and can feasibly be measured in surgical quality datasets. The model performed well with 10 to 12 variables and demonstrated applicability across surgical specialties. Such efforts are critical to better tailor quality improvement to older surgical patients.
利用多机构数据源探讨术后谵妄的医院间差异。
术后谵妄与老年人严重发病率、残疾和死亡密切相关。然而,外科医生和医院很少测量谵妄发生率,这限制了质量改进工作。
美国外科医师学会国家外科质量改进计划(ACS NSQIP)老年手术试点(2014 年至 2015 年)收集老年特定变量,包括使用标准化定义的术后谵妄。分层逻辑回归模型,根据病例组合(当前程序术语 [CPT] 代码)和患者风险因素进行调整,得出医院表现的风险调整和平滑优势比(OR)。采用 Hosmer-Lemeshow(HL)统计量和 c 统计量评估模型性能,并比较不同外科专业。
30 家医院的 22121 名老年人(≥65 岁)接受了住院手术。2427 名患者(12.0%)发生术后谵妄,不同专业的发生率存在差异,从妇科的 4.7%到心胸外科的 13.7%不等。使用 20 个风险因素的分层建模(HL = 9.423,P = 0.31;c 统计量 0.86)确定了 13 家医院为统计学异常值(5 家表现良好,8 家表现不佳)。按医院计算,中位风险调整后谵妄发生率为 10.4%(范围 3.2%至 27.5%)。手术特异性风险和术前认知障碍(OR 2.9,95%置信区间 2.5-3.5)是最强的预测因素。该模型在不同的外科专业中表现良好(骨科、普通外科和血管外科)。
医院间术后谵妄发生率差异高达 8.5 倍,在外科质量数据集内可实际测量。该模型在使用 10 到 12 个变量时表现良好,适用于不同的外科专业。这种努力对于更好地为老年手术患者量身定制质量改进措施至关重要。