Affiliation:
1. Department of Otolaryngology, Head and Neck Surgery University of Texas, Southwestern Medical Center at Dallas Dallas Texas USA
Abstract
AbstractIntroductionIn pediatric tonsillectomy management, the consistent tracking of surgical outcomes and adherence to guidelines are vital. This study explores how a surgical dashboard can serve as a tool in research analysis, translating AAO‐HNSF guidelines into measurable performance improvements.MethodsUsing a prospective registry from three pediatric hospitals, a Tableau dashboard was constructed to graphically visualize key demographic and postoperative outcomes (including intensive care unit [ICU] utilization, 30‐day emergency department (ED) visits, and postoperative bleed rates) in children undergoing tonsillectomy from 2020 to 2024. From the dashboard data, a retrospective cohort study analyzing 6767 tonsillectomies was conducted from January 2, 2020, to June 20, 2023. Patients were categorized into low‐risk, OSA‐only (by ICD‐10 codes), and high‐risk groups based on comorbidities. Logistic regression identified factors influencing ED revisits and unplanned nursing calls. Three quality initiatives were assessed: preoperative school absence notes, perioperative dexamethasone recording, and post‐tonsillectomy parental education.ResultsA total of 2122 (31%) were low‐risk, 2648 (39%) were OSA‐only, and 1997 (30%) high risk. Risk factors that increased the likelihood of ED visits were high‐risk comorbidities (OR = 1.46; 95% CI = 1.24–1.74; p < 0.001) and older age (OR = 1.05; 95% CI = 1.03–1.08; p < 0.001). Risk factors that increased the likelihood of an unplanned nursing communication were high‐risk comorbidities (OR = 1.53; 95% CI = 1.34–1.75; p < 0.001), older age (OR = 1.03, 95% CI = 1.01–1.04; p = 0.001), and Medicaid insurance (OR = 1.25; 95% CI = 1.09–1.43; p = 0.002). Postoperative bleed control was generally comparable between the groups, at 2.8% (low risk), 2.7% (OSA), 3.2 (high risk) (p = 0.651).ConclusionThe dashboard aided in data collection, data visualization, and data analysis of quality improvement initiatives, effectively translating guidelines into tangible measures to enhance care.Level of evidenceNA.