• Daniel E Goltz, Billy T Baumgartner, Cary S Politzer, Marcus DiLallo, Michael P Bolognesi, and Thorsten M Seyler.
• Duke University School of Medicine, Duke University Medical Center Greenspace, Durham, North Carolina.
• J Arthroplasty. 2018 Jan 1; 33 (1): 25-29.

BackgroundPatient demand and increasing cost awareness have led to the creation of surgical risk calculators that attempt to predict the likelihood of adverse events and to facilitate risk mitigation. The American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator is an online tool available for a wide variety of surgical procedures, and has not yet been fully evaluated in total joint arthroplasty.MethodsA single-center, retrospective review was performed on 909 patients receiving a unilateral primary total knee (496) or hip (413) arthroplasty between January 2012 and December 2014. Patient characteristics were entered into the risk calculator, and predicted outcomes were compared with observed results. Discrimination was evaluated using the receiver-operator area under the curve (AUC) for 90-day readmission, return to operating room (OR), discharge to skilled nursing facility (SNF)/rehab, deep venous thrombosis (DVT), and periprosthetic joint infection (PJI).ResultsThe risk calculator demonstrated adequate performance in predicting discharge to SNF/rehab (AUC 0.72). Discrimination was relatively limited for DVT (AUC 0.70, P = .2), 90-day readmission (AUC 0.63), PJI (AUC 0.67), and return to OR (AUC 0.59). Risk score differences between those who did and did not experience discharge to SNF/rehab, 90-day readmission, and PJI reached significance (P < .01). Predicted length of stay performed adequately, only overestimating by 0.2 days on average (rho = 0.25, P < .001).ConclusionThe American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator has fair utility in predicting discharge to SNF/rehab, but limited usefulness for 90-day readmission, return to OR, DVT, and PJI. Although length of stay predictions are similar to actual outcomes, statistical correlation remains relatively weak.Copyright © 2017 Elsevier Inc. All rights reserved.

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