Comparison of the PCPLC Database to NSQIP-P: A Patient Matched Comparison of Surgical Complications Following Repair of Anorectal Malformation.

BACKGROUND: Anorectal malformations (ARM) are rare and heterogenous which creates a challenge in conducting research and offering recommendations for best practice. The Pediatric Colorectal and Pelvic Learning Consortium (PCPLC) was formed in 2016 to address this challenge and created a shared national data registry to collect information about pediatric colorectal patients. There has been no external validation of the data collected. We sought to evaluate the database by performing a patient matched analysis comparing 30-day outcomes identified in the PCPLC registry with the NSQIP-P database for patients undergoing surgical repair of ARM. METHODS: Patients captured in the PCPLC database from 2016 to 2021 at institutions also participating in NSQIP-P who underwent ARM repair younger than 12 months old were reviewed for 30-day complications. These patients were matched to their NSQIP-P record using their hospital identification number, and records were compared for concordance in identified complications. RESULTS: A total of 591 patient records met inclusion criteria in the PCPLC database. Of these, 180 patients were also reviewed by NSQIP-P. One hundred and fifty-six patient records had no complications recorded. Twenty-four patient records had a complication listed in one or both databases. There was a 91 % concordance rate between databases. When excluding complications not tracked in the PCPLC registry, this agreement improved to 93 %. CONCLUSION: Including all patients evaluated for this subpopulation, a 91 % concordance rate was observed when comparing PCPLC collected complications to NSQIP-P. Future efforts can focus on further validating the data within the PCPLC for other patient populations. LEVEL OF EVIDENCE: V.

NSQIP versus institutional morbidity and mortality conference: complementary complication reporting in pediatric spine fusion.

PURPOSE: Other fields of medicine have demonstrated underreported surgical complication rates by institutional M&M compared to NSQIP. However, a study comparing surgical complication rates in the pediatric spine population, using an identical set of patients rather than nationally extrapolated, has not been performed. METHODS: A single institution's ASC-NSQIP Pediatric spine fusion cases and its departmental team-reported M&M database for the same were reviewed for January 1, 2012 to December 31, 2018. Differences in surgical complication reporting between the two databases for the identical patient cohort were recorded. RESULTS: NSQIP identified 50 pediatric spine fusion patients with complications out of 386 NSQIP-algorithm-sampled cases (13%). Of these complications, 23 were not reported in the M&M conference database (6% of NSQIP-sampled cases, 2.5% of all M&M cases). The most common under-reported complication categories include pneumonia (100% under-reported), clostridium difficile (100%), urinary tract infection (83%), and superficial wound disruption (67%). During the same 7 years, M&M covered 924 spine fusions and identified 162 complications. Of these 162 patients, 22 were included in the NSQIP sampling and were not reported as complications (6% of NSQIP sampled patients). CONCLUSION: Recognizing complication rates is central to implement strategies for delivering better quality care. NSQIP data may serve as an important quality check for pediatric spine institutional M&M data, but both may not include all complications even within its sampled patients. In general, NSQIP's protocols identified more medical complications, while M&M has a surgical focus, benefits from the limitless follow-up, and involves timely departmental awareness of complications.

Validation of an Electronic Surveillance Algorithm to Identify Patients With Post-Operative Surgical Site Infections Using National Surgical Quality Improvement Program Pediatric Data.

BACKGROUND: Surgical site infections (SSIs) are common, but data related to these infections maybe difficult to capture. We developed an electronic surveillance algorithm to identify patients with SSIs. Our objective was to validate our algorithm by comparing it with our institutional National Surgical Quality Improvement Program Pediatric (NSQIP Peds) data. METHODS: We applied our algorithm to our institutional NSQIP Peds 2015-2017 cohort. The algorithm consisted of the presence of a diagnosis code for post-operative infection or the presence of 4 criteria: diagnosis code for infection, antibiotic administration, positive culture, and readmission/surgery related to infection. We compared the algorithm's SSI rate to the NSQIP Peds identified SSI. Algorithm performance was assessed using sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and Cohen's kappa. The charts of discordant patients were reviewed to understand limitations of the algorithm. RESULTS: Of 3879 patients included, 2.5% had SSIs by NSQIP Peds definition and 1.9% had SSIs by our algorithm. Our algorithm achieved a sensitivity of 44%, specificity of 99%, NPV of 99%, PPV of 59%, and Cohen's kappa of 0.5. Of the 54 false negatives, 37% were diagnosed/treated as outpatients, 31% had tracheitis, and 17% developed SSIs during their post-operative admission. Of the 30 false positives, 33% had an infection at index surgery and 33% had SSIs related to other surgeries/procedures. CONCLUSIONS: Our algorithm achieved high specificity and NPV compared with NSQIP Peds reported SSIs and may be useful when identifying SSIs in patient populations that are not actively monitored for SSIs.