Seelye Sarah, Cano Jennifer, Hogan Cainnear K, Prescott Hallie C, Sussman Jeremy B
VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
J Gen Intern Med. 2024 Dec;39(16):3129-3137. doi: 10.1007/s11606-024-09104-y. Epub 2024 Oct 7.
Traditional risk prediction and risk adjustment models have focused on clinical characteristics, but accounting for social determinants of health (SDOH) and complex health conditions could improve understanding of sepsis outcomes and our ability to predict outcomes, treat patients, and assess quality of care.
To evaluate the impact of SDOH and health scales in sepsis mortality risk prediction and hospital performance assessment.
Observational cohort study.
One hundred twenty-nine hospitals in the nationwide Veterans Affairs (VA) Healthcare System between 2017 and 2021.
Veterans admitted through emergency departments with community-acquired sepsis.
Individual- and community-level SDOH (race, housing instability, marital status, Area Deprivation Index [ADI], and rural residence) and two health scales (the Care Assessment Need [CAN] score and Claims-Based Frailty Index [CFI]).
The primary outcome was 90-day mortality from emergency department arrival; secondary outcomes included 30-day mortality and in-hospital mortality.
Among 144,889 patients admitted to the hospital with community-acquired sepsis, 139,080 were men (96.0%), median (IQR) age was 71 (64-77) years, and median (IQR) ADI was 60 (38-81). Multivariable regression models had good calibration and discrimination across models that adjusted for different sets of variables (e.g., AUROC, 0.782; Brier score, 1.33; and standardized mortality rate, 1.00). Risk-adjusted hospital performance was similar across all models. Among 129 VA hospitals, three hospitals shifted from the lowest or highest quintile of performance when comparing models that excluded SDOH to models that adjusted for all variables. Models that adjusted for ADI reported odds ratios (CI) of 1.00 (1.00-1.00), indicating that ADI does not significantly predict sepsis mortality in this cohort of patients.
In patients with community-acquired sepsis, adjusting for community SDOH variables such as ADI did not improve 90-day sepsis mortality predictions in mortality models and did not substantively alter hospital performance within the VA Healthcare System. Understanding the role of SDOH in risk prediction and risk adjustment models is vital because it could prevent hospitals from being negatively evaluated for treating less advantaged patients. However, we found that in VA hospitals, the potential impact of SDOH on 90-day sepsis mortality was minimal.
传统的风险预测和风险调整模型侧重于临床特征，但纳入健康的社会决定因素（SDOH）和复杂的健康状况有助于加深对脓毒症预后的理解，并提高我们预测预后、治疗患者和评估医疗质量的能力。
评估SDOH和健康量表对脓毒症死亡风险预测和医院绩效评估的影响。
观察性队列研究。
2017年至2021年期间，全国退伍军人事务（VA）医疗系统中的129家医院。
通过急诊科收治的社区获得性脓毒症退伍军人。
个体和社区层面的SDOH（种族、住房不稳定、婚姻状况、地区贫困指数[ADI]和农村居住情况）以及两个健康量表（护理评估需求[CAN]评分和基于索赔的虚弱指数[CFI]）。
主要结局是从急诊科就诊起90天内的死亡率；次要结局包括30天死亡率和住院死亡率。
在144,889例因社区获得性脓毒症入院的患者中，139,080例为男性（96.0%），年龄中位数（四分位间距）为71（64 - 77）岁，ADI中位数（四分位间距）为60（38 - 81）。多变量回归模型在针对不同变量集进行调整的模型中具有良好的校准和区分度（例如，曲线下面积[AUC]为0.782；Brier评分1.33；标准化死亡率1.00）。所有模型的风险调整后医院绩效相似。在129家VA医院中，当比较排除SDOH的模型和针对所有变量进行调整的模型时，有三家医院的绩效排名从最低或最高五分位数发生了变化。针对ADI进行调整的模型报告的优势比（置信区间）为1.00（1.00 - 1.00），表明在该队列患者中，ADI并不能显著预测脓毒症死亡率。
在社区获得性脓毒症患者中，针对社区SDOH变量（如ADI）进行调整并不能改善死亡率模型中90天脓毒症死亡率的预测，也未实质性改变VA医疗系统内医院的绩效。了解SDOH在风险预测和风险调整模型中的作用至关重要，因为这可以防止医院因治疗条件较差的患者而受到负面评价。然而，我们发现，在VA医院中，SDOH对90天脓毒症死亡率的潜在影响极小。
