Assessing the Variation and Drivers of Cost in 1-Level Lumbar Fusion: A Time-Driven Activity-Based Costing Analysis

Background Context As value-based health care arrangements gain traction in spine care, understanding the true cost of care becomes critical. Historically, inaccurate cost proxies have been used, including negotiated reimbursement rates or list prices. However, time-driven activity-based costing (TDABC) allows for a more accurate cost assessment, including a better understanding of the primary drivers of cost in 1-level lumbar fusion. Purpose To determine the variation of total hospital cost, differences in characteristics between high-cost and non-high-cost patients, and to identify the primary drivers of total hospital cost in a sample of patients undergoing 1-level lumbar fusion. Study Design/Setting Retrospective, multicenter (one academic medical center, one community-based hospital), observational study. Patient Sample A total of 383 patients undergoing elective 1-level lumbar fusion for degenerative spine conditions between November 2, 2021 and December 2, 2022. Outcome Measures Total hospital cost of care (normalized); preoperative, intraoperative, and postoperative cost of care (normalized); ratio of most to least expensive 1-level lumbar fusion. Methods Patients undergoing a 1-level lumbar fusion between November 2, 2021 and December 2, 2022 were identified at two hospitals (one quaternary referral academic medical center and one community-based hospital) within our health system. TDABC was used to calculate total hospital cost, which was also broken up into: pre-, intra-, and postoperative timeframes. Operating surgeon and patient characteristics were also collected and compared between high- and non-high-cost patients. The correlation of surgical time and cost was determined. Multivariable linear regression was used to determine factors associated with total hospital cost. Results The most expensive 1-level lumbar fusion was 6.8x more expensive than the least expensive 1-level lumbar fusion, with the intraoperative period accounting for 88% of total cost. On average. the implant cost accounted for 30% of the total, but across the patient sample, the implant cost accounted for a range of 6% to 44% of the total cost. High-cost patients were younger (55 years [SD: 13 years] vs.63 years [SD: 13 years], p=0.0002), more likely to have commercial health insurance (24 out of 38 (63%) vs. 181 out of 345 (52%), p=0.003). There was a poor correlation between time of surgery (i.e., incision to close) and total overall cost (ρ: 0.26, p<0.0001). Increase age (RC: -0.003 [95% CI: -0.006 to -0.000007], p=0.049) was associated with decreased cost. Surgery by certain surgeons was associated with decreased total cost when accounting for other factors (p<0.05). Conclusions A large variation exists in the total hospital cost for patients undergoing 1-level lumbar fusion, which is primarily driven by surgeon-level decisions and preferences (e.g., implant and technology use). Also, being a “fast” surgeon intraoperatively does not mean your total cost is meaningfully lower. As efforts continue to optimize patient value through ensuring appropriate clinical outcomes while also reducing cost, spine surgeons must use this knowledge to lead, or at least be active participants in, any discussions that could impact patient care.