Determinants of long-term survival after major surgery and the adverse effect of postoperative complications

Abstract

Objective: The objective of this study was to identify the determinants of 30-day postoperative mortality and long-term survival after major surgery as exemplified by 8 common operations.

Summary background data: The National Surgical Quality Improvement Program (NSQIP) database contains pre-, intra-, and 30-day postoperative data, prospectively collected in a standardized fashion by a dedicated nurse reviewer, on major surgery in the Veterans Administration (VA). The Beneficiary Identification and Records Locator Subsystem (BIRLS) is a VA file that depicts the vital status of U.S. veterans with 87% to 95% accuracy.

Methods: NSQIP data were merged with BIRLS to determine the vital status of 105,951 patients who underwent 8 types of operations performed between 1991 and 1999, providing an average follow up of 8 years. Logistic and Cox regression analyses were performed to identify the predictors of 30-day mortality and long-term survival, respectively.

Results: The most important determinant of decreased postoperative survival was the occurrence, within 30 days postoperatively, of any one of 22 types of complications collected in the NSQIP. Independent of preoperative patient risk, the occurrence of a 30-day complication in the total patient group reduced median patient survival by 69%. The adverse effect of a complication on patient survival was also influenced by the operation type and was sustained even when patients who did not survive for 30 days were excluded from the analyses.

Conclusions: The occurrence of a 30-day postoperative complication is more important than preoperative patient risk and intraoperative factors in determining the survival after major surgery in the VA. Quality and process improvement in surgery should be directed toward the prevention of postoperative complications.

Figures

FIGURE 1. Kaplan-Meier survival curves of patients undergoing major surgery in the Veterans Affairs between 1991 and 2003, calculated for each type of operation included in the study.

FIGURE 2. A, Cox survival curves of all study patients who sustained a 30-day postoperative complication compared with those who did not. B, Cox survival curves of study patients who survived 30 days after major surgery stratified as to whether or not patients had sustained a complication within the first 30 postoperative days. The difference in survival between the 2 groups in each panel reflects the independent effect of the occurrence of a postoperative complication on postoperative survival, ie, corrected for other confounding variables captured in the National Surgical Quality Improvement Program.

FIGURE 3. Cox survival curves of study patients undergoing abdominal aortic aneurysmectomy (A) and laparoscopic cholecystectomy (B) stratified as to whether or not patients had sustained a complication within the first 30 postoperative days. The difference in survival between the 2 groups in each panel reflects the independent effect of the occurrence of a postoperative complication on postoperative survival, ie, corrected for other confounding variables captured in the National Surgical Quality Improvement Program.

FIGURE 4. Cox survival curves of all study patients stratified as to whether or not the patients had sustained a pulmonary complication (A) or a wound complication (B) within the first 30 postoperative days. The difference in survival between the 2 groups in each panel reflects the independent effect of the occurrence of the respective complication on postoperative survival, ie, corrected for other confounding variables captured in the National Surgical Quality Improvement Program. Pulmonary complications include one or more of the following: pneumonia, prolonged intubation, and failure to wean. Wound complications include superficial wound infection, deep wound infection, and wound dehiscence.

FIGURE 5. Survival curve of patients undergoing colectomy who developed one or more complications in the first 30 days postoperatively showing the 2 slopes of the curve and the inflection point. The inflection points for the 8 procedures studied are shown in the table insert.

FIGURE 6. Time course of the observed to expected (O/E) 30-day morbidity ratio in the all-operations model over 4 fiscal years in 2 separate Veterans Affairs medical centers. A statistically significant high outlier at the 99% confidence level is indicated by the asterisk (*) and a statistically significant low outlier is indicated by the pound sign (#). (A; hospital A) This hospital was a low outlier in FY 01; the morbidity rate increased over the next 2 years, mostly in general surgery and orthopedics, causing it to become a high outlier in FY 03. Process improvement reversed the overall O/E ratio, but although it ceased to be an outlier in the all operations model and general surgery, it continued to be a high outlier in orthopedics, indicating that additional process improvement needed to be directed toward orthopedic surgery at that hospital. (B; hospital B) This hospital was a high outlier in morbidity for 3 consecutive years. Negative press about the quality of care at that hospital prompted process improvement that resulted in a marked decrease in morbidity rate from 17.5% to 10.8%. These 2 case studies exemplify the fact that surgical morbidity rates can be reduced effectively through local process improvement.