Abstract

Although bundled payment models are well-established in Medicare-aged individuals, private insurers are now developing bundled payment plans. The role of these plans in spine surgery has not been evaluated. Our objective was to analyze the performance of a private insurance bundled payment program for lumbar decompression and microdiskectomy. A retrospective review was conducted of all lumbar decompressions in a private payer bundled payment model at a single institution from October 2018 to December 2020. 120-day episode of care cost data were collected and reported as net profit or loss regarding set target prices. A stepwise multivariable linear regression model was developed to measure the effect of patient and surgical factors on net surplus or deficit. Overall, 151 of 468 (32.2%) resulted in a deficit. Older patients (58.6 vs. 50.9 years, P < 0.001) with diabetes (25.2% vs. 13.9%, P = 0.004), hypertension (38.4% vs. 28.4%, P = 0.038), heart disease (13.9% vs. 7.57%, P = 0.030), and hyperlipidemia (51.7% vs. 35.6%, P = 0.001) were more likely to experience a loss. Surgically, decompression of more levels (1.91 vs. 1.19, P < 0.001), posterior lumbar decompression (86.8% vs. 56.5%, P < 0.001), and performing surgery at a tertiary hospital (84.8% vs. 70.3%, P < 0.001) were more likely to result in loss. All readmissions resulted in a loss (4.64% vs. 0.0%, P < 0.001). On multivariable regression, microdiskectomy (β: $2,398, P = 0.012) and surgery in a specialty hospital (β: $1,729, P = 0.096) or ambulatory surgery center (β: $3,534, P = 0.055) were associated with cost savings. Increasing number of levels, longer length of stay, active smoking, and history of cancer, dementia, or congestive heart failure were all associated with degree of deficit. Preoperatively optimizing comorbidities and using risk stratification to identify those patients who may safely undergo surgery at a facility other than an inpatient hospital may help increase cost savings in a bundled payment model of working-age and Medicare-age individuals.

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