Keenan Patricia S, Normand Sharon-Lise T, Lin Zhenqiu, Drye Elizabeth E, Bhat Kanchana R, Ross Joseph S, Schuur Jeremiah D, Stauffer Brett D, Bernheim Susannah M, Epstein Andrew J, Wang Yongfei, Herrin Jeph, Chen Jersey, Federer Jessica J, Mattera Jennifer A, Wang Yun, Krumholz Harlan M
Section of Health Policy and Administration, School of Public Health, Yale University School of Medicine, New Haven, CT 06520-8088, USA.
Circ Cardiovasc Qual Outcomes. 2008 Sep;1(1):29-37. doi: 10.1161/CIRCOUTCOMES.108.802686.
Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services.
We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points).
This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.
对于心力衰竭患者而言,出院后不久再次入院是一个代价高昂且往往可预防的事件。我们提出了一个经国家质量论坛批准的模型,用于医疗保险和医疗补助服务中心公开报告医院层面的再入院率。
我们开发了一个分层逻辑回归模型,以计算因心力衰竭住院患者的医院风险标准化30天全因再入院率。该模型是利用2004年队列的医疗保险理赔数据推导出来的,并使用理赔和病历数据进行了验证。未调整的再入院率为23.6%。最终模型包含37个变量,辨别能力范围从预测最低十分位数中观察到的30天再入院率的15%到最高十分位数中的37%,c统计量为0.60。4669家医院风险标准化再入院率的第25和第75百分位数分别为23.1%和24.0%,第5和第95百分位数分别为22.2%和25.1%。高于平均水平1个标准差的医院全因再入院几率是低于平均水平1个标准差医院的1.30倍。使用理赔模型得出的州层面调整后再入院率与使用病历模型针对同一队列得出的率相似(相关性为0.97;中位数差异为0.06个百分点)。
这种基于理赔的心力衰竭患者医院风险标准化再入院率模型所产生的估计值可作为源自病历模型的估计值的替代指标。