Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania.
Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Medical Center, Iowa City, Iowa; Department of Internal Medicine, Carver College of Medicine, The University of Iowa, Iowa City, Iowa.
J Surg Res. 2024 Aug;300:514-525. doi: 10.1016/j.jss.2024.04.082. Epub 2024 Jun 14.
Veterans Affairs Surgical Quality Improvement Program (VASQIP) benchmarking algorithms helped the Veterans Health Administration (VHA) reduce postoperative mortality. Despite calls to consider social risk factors, these algorithms do not adjust for social determinants of health (SDoH) or account for services fragmented between the VHA and the private sector. This investigation examines how the addition of SDoH change model performance and quantifies associations between SDoH and 30-d postoperative mortality.
VASQIP (2013-2019) cohort study in patients ≥65 y old with 2-30-d inpatient stays. VASQIP was linked to other VHA and Medicare/Medicaid data. 30-d postoperative mortality was examined using multivariable logistic regression models, adjusting first for clinical variables, then adding SDoH.
In adjusted analyses of 93,644 inpatient cases (97.7% male, 79.7% non-Hispanic White), higher proportions of non-veterans affairs care (adjusted odds ratio [aOR] = 1.02, 95% CI = 1.01-1.04) and living in highly deprived areas (aOR = 1.15, 95% CI = 1.02-1.29) were associated with increased postoperative mortality. Black race (aOR = 0.77, CI = 0.68-0.88) and rurality (aOR = 0.87, CI = 0.79-0.96) were associated with lower postoperative mortality. Adding SDoH to models with only clinical variables did not improve discrimination (c = 0.836 versus c = 0.835).
Postoperative mortality is worse among Veterans receiving more health care outside the VA and living in highly deprived neighborhoods. However, adjusting for SDoH is unlikely to improve existing mortality-benchmarking models. Reduction efforts for postoperative mortality could focus on alleviating care fragmentation and designing care pathways that consider area deprivation. The adjusted survival advantage for rural and Black Veterans may be of interest to private sector hospitals as they attempt to alleviate enduring health-care disparities.
退伍军人事务部手术质量改进计划（VASQIP）基准算法帮助退伍军人事务部（VHA）降低了术后死亡率。尽管有人呼吁考虑社会风险因素，但这些算法并没有调整健康的社会决定因素（SDoH），也没有考虑到 VHA 和私营部门之间分散的服务。本研究考察了 SDoH 的加入如何改变模型性能，并量化了 SDoH 与 30 天术后死亡率之间的关联。
对 2013 年至 2019 年期间年龄在 65 岁及以上、住院时间为 2-30 天的患者进行 VASQIP 队列研究。VASQIP 与其他 VHA 和 Medicare/Medicaid 数据相关联。使用多变量逻辑回归模型检查 30 天术后死亡率，首先调整临床变量，然后添加 SDoH。
在对 93644 例住院病例（97.7%为男性，79.7%为非西班牙裔白人）的调整分析中，非退伍军人事务护理比例较高（调整后的优势比[aOR] = 1.02，95%CI = 1.01-1.04）和生活在高度贫困地区（aOR = 1.15，95%CI = 1.02-1.29）与术后死亡率增加相关。黑人种族（aOR = 0.77，CI = 0.68-0.88）和农村地区（aOR = 0.87，CI = 0.79-0.96）与较低的术后死亡率相关。将 SDoH 添加到仅包含临床变量的模型中不会提高区分度（c = 0.836 与 c = 0.835）。
在退伍军人事务部接受更多非退伍军人事务部医疗保健和生活在高度贫困社区的退伍军人中，术后死亡率更差。然而，调整 SDoH 不太可能改善现有的死亡率基准模型。减少术后死亡率的努力可以集中在减轻医疗保健碎片化和设计考虑地区贫困的护理途径上。农村和黑人退伍军人的调整后生存优势可能会引起私营部门医院的兴趣，因为他们试图减轻持久的医疗保健差距。
