Utilization of Predictive Modeling to Determine Episode of Care Costs and to Accurately Identify Catastrophic Cost Nonwarranty Outlier Patients in Adult Spinal Deformity Surgery: A Step Toward Bundled Payments and Risk Sharing.

Abstract

Retrospective review of prospectively-collected, multicenter adult spinal deformity (ASD) database. The aim of this study was to evaluate the rate of patients who accrue catastrophic cost (CC) with ASD surgery utilizing direct, actual costs, and determine the feasibility of predicting these outliers. Cost outliers or surgeries resulting in CC are a major concern for ASD surgery as some question the sustainability of these surgical treatments. Generalized linear regression models were used to explain the determinants of direct costs. Regression tree and random forest models were used to predict which patients would have CC (>$100,000). A total of 210 ASD patients were included (mean age of 59.3 years, 83% women). The mean index episode of care direct cost was $70,766 (SD = $24,422). By 90 days and 2 years following surgery, mean direct costs increased to $74,073 and $77,765, respectively. Within 90 days of the index surgery, 11 (5.2%) patients underwent 13 revisions procedures, and by 2 years, 26 (12.4%) patients had undergone 36 revision procedures. The CC threshold at the index surgery and 90-day and 2-year follow-up time points was exceeded by 11.9%, 14.8%, and 19.1% of patients, respectively. Top predictors of cost included number of levels fused, surgeon, surgical approach, interbody fusion (IBF), and length of hospital stay (LOS). At 90 days and 2 years, a total of 80.6% and 64.0% of variance in direct cost, respectively, was explained in the generalized linear regression models. Predictors of CC were number of fused levels, surgical approach, surgeon, IBF, and LOS. The present study demonstrates that direct cost in ASD surgery can be accurately predicted. Collectively, these findings may not only prove useful for bundled care initiatives, but also may provide insight into means to reduce and better predict cost of ASD surgery outside of bundled payment plans. 3.