Krumholz Harlan M, Lin Zhenqiu, Drye Elizabeth E, Desai Mayur M, Han Lein F, Rapp Michael T, Mattera Jennifer A, Normand Sharon-Lise T
Section of Cardiovascular Medicine and Robert Wood Johnson Clinical Scholars Program, Department of Internal Medicine, and School of Public Health, Yale University School of Medicine, New Haven, CT 06510, USA.
Circ Cardiovasc Qual Outcomes. 2011 Mar;4(2):243-52. doi: 10.1161/CIRCOUTCOMES.110.957498.
National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction.
We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points).
This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.
全国范围内日益关注再入院情况，并将其作为质量改进的目标。我们介绍了一种经国家质量论坛批准、医疗保险和医疗补助服务中心用于对急性心肌梗死后出院患者的医院层面风险标准化再入院率进行公开报告的模型的开发与验证。
我们开发了一种分层逻辑回归模型，以计算急性心肌梗死住院患者的医院风险标准化30天全因再入院率。该模型使用2006年队列的医疗保险理赔数据推导得出，并使用理赔和病历数据进行验证。未调整的再入院率为18.9%。最终模型包含31个变量，其判别能力范围为：在预测能力最低的十分位数组中，观察到的30天再入院率为8%；在最高十分位数组中为32%，C统计量为0.63。3890家医院的风险标准化再入院率的第25百分位数和第75百分位数分别为18.6%和19.1%，第5百分位数和第95百分位数分别为18.0%和19.9%。高于平均水平1个标准差的医院发生全因再入院的几率是低于平均水平1个标准差的医院的1.35倍。使用理赔模型得出的医院层面调整后的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0.98；中位数差异为0.02个百分点）。
这种基于理赔数据的急性心肌梗死患者医院风险标准化再入院率模型所产生的估计值，是病历模型所产生估计值的优秀替代指标。
