3. Preoperative Risk Factors and Surgical Complexity Are More Predictive Of Costs Than Postoperative Complications: A Case Study Using the National Surgical Quality Improvement (NSQIP) Database
Daniel L. Davenport, MBA* 1, William G. Henderson, PhD* 2, Shukri F. Khuri, MD3, Robert M. Mentzer, Jr., MD1
1University of Kentucky, Lexington, KY; 2University of Colorado Health Outcomes Program, Denver, CO; 3National Surgery Quality Improvement Program, West Roxbury, MA
This single center study tested the hypothesis that preoperative risk factors and surgical complexity predict more variation in hospital costs than complications.
The National Surgical Quality Improvement Program (NSQIP) database and the hospital financial system (TSI) were used to track preoperative risk factors, surgical complexity, outcomes, and costs in 5,878 patients. Operation complexity was assessed by work RVUs. Linear regression was used to determine the total variation in hospital costs associated with surgical complications (Model A). Staged multiple regression was used to determine the variation associated with preoperative risk factors, surgical complexity and postoperative complications (Models B1-3).
Results are shown in Table 1.
Table . Linear regression results of clinical factors versus costs.*
|Multiple Regression||R2||Significance||Change in R2|
|Model A. Complications Only||0.20||P < 0.001|
|Staged Multiple Regression|
|Model B1. Preop. Risk Factors Only||0.33||P < 0.001||0.33|
|Model B2. Risk Factors + Work RVUs||0.49||P < 0.001||0.16|
|Model B3. Risk Factors + Work RVUs + Complications||0.53||P < 0.001||0.04|
*Costs were transformed by taking the quartic root.
Using Model A, twenty percent of hospital cost variation was associated with the occurrence of complications. (P<0.001) However, when risks and complexity were sequentially integrated in Model B2, they predicted 49% of hospital cost variation. Adding complications to this staged model only predicted an additional 4% of cost variation. (P<0.001)
Preoperative risk factors and surgical complexity are more effective predictors of hospital costs than complications. Efforts to decrease these costs will therefore require improvement in our ability to manage the preoperative disease state of the patient and/or improve the effectiveness of the operation.