Big Data in Total Shoulder Arthroplasty: An In-depth Comparison of National Outcomes Databases.

Abstract

The practice of identifying trends in surgical decision-making through large-scale patient databases is commonplace. We hypothesize that notable differences exist between claims-based and prospectively collected clinical registries. We queried the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), a prospective surgical outcomes database, and PearlDiver (PD), a claims-based private insurance database, for patients undergoing primary total shoulder arthroplasties from 2007 to 2016. Comorbidities and 30-day complications were compared. Multiple regression analysis was performed for each cohort to identify notable contributors to 30-day revision surgery. Significant differences were observed in demographics, comorbidities, and postoperative complications for the age-matched groups between PD and NSQIP (P < 0.05 for all). Multiple regression analysis in PD identified morbid obesity and dyspnea to lead to an increased risk for revision surgery (P = 0.001) in the <65 cohort and dyspnea and diabetes to lead to an increased risk for revision surgery in the ≥65 cohort (P = 0.015, P < 0.001). Multiple regression did not reveal any risk factors for revision surgery in the <65 age group for the NSQIP; however, congestive heart failure was found to have an increased risk for revision surgery in the ≥65 cohort (P < 0.001). Notable differences in comorbidities and complications for patients undergoing primary total shoulder arthroplasty were present between PD and NSQIP. Retrospective cohort study, level III.