Drivers of Variability in 90-Day Cost for Elective Laminectomy and Fusion for Lumbar Degenerative Disease. Issue 5 (25th July 2018)

• Record Type: Journal Article
• Authors: Sivaganesan, Ahilan; Chotai, Silky; Parker, Scott L; McGirt, Matthew J; Devin, Clinton J
• Is Part Of: Neurosurgery. Volume 84:Issue 5(2019)
• Page Start: 1043
• Page End: 1049
• Publication Date: 2018-07-25
• Subjects: Cost -- Drivers -- Lumbar -- Laminectomy -- Fusion -- bundled payments; Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyy264
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: BACKGROUND: Considerable variability exists in the cost of surgery following spine surgery for common degenerative spine diseases. This variation in the cost of surgery can affect the payment bundling during the postoperative 90 d. OBJECTIVE: To determine the drivers of variability in total 90-d cost for laminectomy and fusion surgery. METHODS: A total of 752 patients who underwent elective laminectomy and fusion for degenerative lumbar conditions and were enrolled into a prospective longitudinal registry were included in the study. Total cost during the 90-d global period was derived as sum of cost of surgery, cost associated with postdischarge utilization. Multivariable regression models were built for total 90-d cost. RESULTS: The mean 90-d direct cost was $29 295 (range, $28 612-$29 973). Based on our regression tree analysis, the following variables were found to drive the 90-d cost: age, BMI, gender, diagnosis, postop imaging, number of operated levels, ASA grade, hypertension, arthritis, preop and postop opioid use, length of hospital stay, duration of surgery, 90-d readmission, outpatient physical/occupational therapy, inpatient rehab, postop healthcare visits, postop nonopioid pain medication use nonsteroidal antiinflammatory drug (NSAIDs), and muscle relaxant use. The R2 for tree model was 0.64. CONCLUSION: Utilizing prospectively collected data, we demonstrate that considerable variation exists in total 90-d cost, nearly 70% of which can be explained by those factors included in our modeling. Risk-adjusted payment schemes can be crafted utilizing the significant drivers presented here. Focused interventions to target some of the modifiable factors have potential to reduce cost and increase the value of care.