Hospitalization cost after spine surgery in the United States of America.

The objective of this study was to develop and validate a predictive model of hospitalization costs after spine surgery. Several initiatives have been put in place to minimize healthcare expenditures but there are limited data on the magnitude of the contribution of procedure-specific drivers of cost. We performed a retrospective cohort study involving 672,591 patients who underwent spine surgery and were registered in the National Inpatient Sample from 2005-2010. The cohort underwent 1:1 randomization to create derivation and validation subsamples. Regression techniques were used for the creation of a parsimonious predictive model of total hospitalization cost after spine surgery. Included were 356,783 patients (53.1%) who underwent fusions, and 315,808 (46.9%) non-fusion surgeries. The median hospitalization cost was $14,202 (interquartile range $4772-23,632). Common drivers of cost identified in the multivariate analysis included the length of stay, number of admission diagnoses and procedures, hospital size and region, patient income, fusion surgery, acute renal failure, sex, and coagulopathy. The model was validated in an independent cohort and demonstrated a final coefficient of determination that was very similar to the initial model. The predicted and observed values in the validation cohort demonstrated good correlations. This national study quantified the magnitude of significant drivers of hospitalization cost after spine surgery. We developed a predictive model that can be utilized as an adjunct in the cost containment debate and the creation of data driven policies.