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  • Title: Pediatric American College of Surgeons National Surgical Quality Improvement Program: feasibility of a novel, prospective assessment of surgical outcomes.
    Author: Raval MV, Dillon PW, Bruny JL, Ko CY, Hall BL, Moss RL, Oldham KT, Richards KE, Vinocur CD, Ziegler MM, ACS NSQIP Pediatric Steering Committee.
    Journal: J Pediatr Surg; 2011 Jan; 46(1):115-21. PubMed ID: 21238651.
    Abstract:
    PURPOSE: The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) provides validated assessment of surgical outcomes. This study reports initiation of an ACS NSQIP Pediatric at 4 children's hospitals. METHODS: From October 2008 to June 2009, 121 data variables were prospectively collected for 3315 patients, including 30-day outcomes and tailoring the ACS NSQIP methodology to children's surgical specialties. RESULTS: Three hundred seven postoperative complications/occurrences were detected in 231 patients representing 7.0% of the study population. Of the patients with complications, 175 (75.7%) had 1, 39 (16.9%) had 2, and 17 (7.4%) had 3 or more complications. There were 13 deaths (0.39%) and 14 intraoperative occurrences (0.42%) detected. The most common complications were infection, 105 (34%) (SSI, 54; sepsis, 31; pneumonia, 13; urinary tract infection, 7); airway/respiratory events, 27 (9%); wound disruption, 18 (6%); neurologic events, 8 (3%) (nerve injury, 4; stroke/vascular event, 2; hemorrhage, 2); deep vein thrombosis, 3 (<1%); renal failure, 3 (<1%); and cardiac events, 3 (<1%). Current sampling captures 17.5% of cases across institutions with unadjusted complication rates ranging from 6.8% to 10.2%. Completeness of data collection for all variables exceeded 95% with 98% interrater reliability and 87% of patients having full 30-day follow-up. CONCLUSION: These data represent the first multiinstitutional prospective assessment of specialty-specific surgical outcomes in children. The ACS NSQIP Pediatric is poised for institutional expansion and future development of risk-adjusted models.
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