Optimizing ACS NSQIP Modeling for Evaluation of Surgical Quality and Risk: Patient Risk Adjustment, Procedure Mix Adjustment, Shrinkage Adjustment, and Surgical Focus

被引:469
作者
Cohen, Mark E. [1 ]
Ko, Clifford Y. [1 ,3 ,4 ]
Bilimoria, Karl Y. [1 ,2 ]
Zhou, Lynn [1 ]
Huffman, Kristopher [1 ]
Wang, Xue [1 ]
Liu, Yaoming [1 ]
Kraemer, Kari [1 ]
Meng, Xiangju [1 ]
Merkow, Ryan [1 ]
Chow, Warren [1 ]
Matel, Brian [1 ]
Richards, Karen [1 ]
Hart, Amy J. [1 ]
Dimick, Justin B. [5 ]
Hall, Bruce L. [1 ,6 ,7 ,8 ,9 ,10 ]
机构
[1] Amer Coll Surg, Div Res & Optimal Patient Care, Chicago, IL 60611 USA
[2] Northwestern Univ, Surg Outcomes & Qual Improvement Ctr, Dept Surg, Feinberg Sch Med, Chicago, IL 60611 USA
[3] Univ Calif Los Angeles, David Geffen Sch Med, Dept Surg, Los Angeles, CA 90095 USA
[4] VA Greater Los Angeles Healthcare Syst, Los Angeles, CA USA
[5] Univ Michigan, Dept Surg, Michigan Surg Collaborat Outcomes Res & Evaluat, Ann Arbor, MI 48109 USA
[6] Washington Univ, Dept Surg, St Louis, MO USA
[7] Washington Univ, BJC Healthcare, St Louis, MO USA
[8] Washington Univ, Ctr Hlth Policy, St Louis, MO USA
[9] Washington Univ, John M Olin Sch Business, St Louis, MO 63130 USA
[10] John Cochran Vet Affairs Med Ctr, St Louis, MO USA
关键词
SUPPORT VECTOR MACHINE; IMPROVEMENT PROGRAM; HOSPITAL OUTCOMES; PREDICTION MODELS; MORTALITY-RATE; REPORT CARDS; ROC CURVE; SURGERY; PERFORMANCE; REGRESSION;
D O I
10.1016/j.jamcollsurg.2013.02.027
中图分类号
R61 [外科手术学];
学科分类号
摘要
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) collects detailed clinical data from participating hospitals using standardized data definitions, analyzes these data, and provides participating hospitals with reports that permit risk-adjusted comparisons with a surgical quality standard. Since its inception, the ACS NSQIP has worked to refine surgical outcomes measurements and enhance statistical methods to improve the reliability and validity of this hospital profiling. From an original focus on controlling for between-hospital differences in patient risk factors with logistic regression, ACS NSQIP has added a variable to better adjust for the complexity and risk profile of surgical procedures (procedure mix adjustment) and stabilized estimates derived from small samples by using a hierarchical model with shrinkage adjustment. New models have been developed focusing on specific surgical procedures (eg, "Procedure Targeted" models), which provide opportunities to incorporate indication and other procedure-specific variables and outcomes to improve risk adjustment. In addition, comparative benchmark reports given to participating hospitals have been expanded considerably to allow more detailed evaluations of performance. Finally, procedures have been developed to estimate surgical risk for individual patients. This article describes the development of, and justification for, these new statistical methods and reporting strategies in ACS NSQIP. (C) 2013 by the American College of Surgeons
引用
收藏
页码:336 / +
页数:12
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