Center for Health Equity Promotion and Research, Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA.
Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
J Am Geriatr Soc. 2020 Sep;68(9):2090-2094. doi: 10.1111/jgs.16650. Epub 2020 Jul 1.
BACKGROUND/OBJECTIVES: Prognostic tools are needed to identify patients at high risk for adverse outcomes receiving post-acute care in skilled nursing facilities (SNFs) and provide high-value care. The SNF Prognosis Score was developed in a Medicare sample to predict a composite of long-term SNF stay, hospital readmission, or death during the SNF stay. Our goal was to evaluate the score's performance in an external validation cohort.
Retrospective observational analysis.
We used a Veterans Administration (VA) Residential History File that concatenates VA, Medicare, and Medicaid claims to identify care trajectories across settings and payers for individual veterans.
Previously community-dwelling veterans receiving post-acute care in a SNF after hospitalization from January 1, 2012, to December 31, 2014. Both VA and non-VA hospitals and SNFs were included.
We calculated the five-item SNF Prognosis Score for all eligible veterans in our sample and determined its discrimination (using a receiver operating characteristic curve) and calibration (plotting observed and expected events).
The 386,483 veterans in our sample had worse physical function, more comorbidities, and were more likely to be treated for heart failure, but they had shorter index hospital lengths of stay and fewer catheters than the original Medicare cohort. The SNF Prognosis Score had similar discrimination (C-statistic = .70; .75 in the derivation cohort) and calibration at low to moderate levels of risk; at high levels, calibration was poorer with the score overestimating risks of adverse events.
The SNF Prognosis Score has reasonable discrimination and calibration, and it is simple to calculate using an admission SNF assessment and a nomogram. Future work embedding the score into practice is needed to determine real-world feasibility, acceptability, and effectiveness.
背景/目的:需要预后工具来识别在熟练护理机构(SNF)接受急性后护理的高风险患者,并提供高价值的护理。SNF 预后评分是在 Medicare 样本中开发的,用于预测 SNF 住院期间长期 SNF 住院、医院再入院或死亡的综合指标。我们的目标是在外部验证队列中评估该评分的性能。
回顾性观察性分析。
我们使用 Veterans Administration(VA)Residential History File,该文件将 VA、Medicare 和 Medicaid 的索赔合并在一起,以识别个体退伍军人在不同环境和支付方之间的护理轨迹。
先前在社区居住的退伍军人,在 2012 年 1 月 1 日至 2014 年 12 月 31 日期间因住院后在 SNF 接受急性后护理。VA 和非 VA 医院和 SNF 都包括在内。
我们为我们样本中的所有合格退伍军人计算了 SNF 预后评分的五个项目,并确定了其判别能力(使用接受者操作特征曲线)和校准能力(绘制观察到的和预期的事件)。
我们的样本中的 386483 名退伍军人的身体功能更差,合并症更多,更有可能因心力衰竭接受治疗,但他们的指数住院时间更短,导尿管更少,比原始 Medicare 队列。SNF 预后评分在低至中度风险水平具有相似的判别能力(C 统计量=0.70;在推导队列中为 0.75)和校准;在高风险水平下,评分的校准较差,高估了不良事件的风险。
SNF 预后评分具有合理的判别能力和校准能力,并且可以使用入院 SNF 评估和列线图进行简单计算。需要进一步的实际工作来确定现实世界的可行性、可接受性和有效性。