Breast Resection Weight Prediction and Insurance Reimbursement in Reduction Mammaplasty: Which Scale Is Reliable?

[BACKGROUND] Many insurance companies in the United States rely on the Schnur sliding scale to predict resection weights to determine medical necessity for breast reduction surgery. Accurate methods to predict resection weights are needed to avoid insurance denials. The authors compared the accuracy of formulas such as the Schnur, Appel, Descamps, and Galveston scales in predicting resection weights, and assessed whether they influence insurance coverage decision.

[METHODS] A retrospective review of bilateral reduction mammaplasty procedures from June of 2017 to June of 2019 was performed at the Mayo Clinic, Rochester. Oncoplastic reduction operations were excluded. The accuracy of each formula-based estimate was evaluated with linear regression analysis.

[RESULTS] One hundred fifty-four patients (308 breasts) were reviewed. The Schnur scale had low correlation with actual resection weight ( r2 = 0.381; b1 = 1.153; p < 0.001). The Appel scale was the most accurate ( r2 = 0.642; b1 = 1.01; p < 0.001), followed by the Descamps ( r2 = 0.572, b1 = 0.934, p < 0.001) and Galveston ( r2 = 0.672; b 1 = 0.654; p < 0.001) scales. The Appel, Descamps, and Galveston scales were more accurate for resection weights of 500 g or greater, body mass index greater than 30 kg/m², and patients younger than 50 years. For resection weights of 500 g or greater, the median difference between the estimated and actual resection weight for the Schnur, Appel, Descamps, and Galveston scales was -211.4 ± 272.3, -17.5 ± 272.3, -9.6 ± 229.5, and -99.2 ± 238.5 g, respectively. No scale was accurate for resection weights less than 500 g. Insurance reimbursement was denied in 15.56 percent of patients; of these, 23 percent had resection weights less than 500 g. The Schnur scale overestimated the resection weights in 28.9 percent of patients.

[CONCLUSIONS] The Schnur scale is a poor predictor of breast resection weight. The Appel scale is the most accurate estimator, especially in the young and obese population with larger resections.

[CLINICAL QUESTION/LEVEL OF EVIDENCE] Diagnostic, I.