Drivers of Cost Associated With Minimally Invasive Esophagectomy

Abstract

Background: In this era of value-based healthcare, costs must be measured alongside patient outcomes to prioritize quality improvement and inform performance-based reimbursement strategies. We sought to identify drivers of costs for patients undergoing minimally invasive esophagectomy for esophageal cancer.

Methods: Patients who underwent minimally invasive esophagectomy for esophageal cancer from December 2008 to March 2020 were included. Our institutional Society of Thoracic Surgeons database was merged with financial data to determine inpatient direct accounting costs in 2020 US dollars for total, operative (surgery and anesthesia), and postoperative (intensive care, floor, radiology, laboratory, etc) services. A supervised machine learning quantitative method, the lasso estimator with 10-fold cross-validation, was applied to identify predictors of costs.

Results: In the study cohort (n = 240) most had ≥cT2 pathology (82%), adenocarcinoma histology (90%), and received neoadjuvant therapy (78%). Mean length of stay was 8.00 days (SD, 4.13) with 45% inpatient morbidity rate and no deaths. The largest proportions of cost were from the operating room (30%), inpatient floor (30%), and postanesthesia care/intensive care units (20%). Preoperative predictors of operative costs were age (-5.18% per decade [95% confidence interval {CI}, -9.95 to -0.27], P = .039), body mass index ≥ 30 (+12.9% [95% CI, 0.00-27.5], P = .050), forced expiratory volume in 1 second (-3.24% per 10% forced expiratory volume in 1 second [95% CI, -5.80 to -0.61], P = .017), and year of surgery (+2.55% [95% CI, 0.97-4.15], P = .002). Predictors of postoperative costs were postoperative renal failure (+91.6% [95% CI, 9.93-233.8], P = .022), respiratory failure (+414.6% [95% CI, 158.7-923.6], P < .001), pneumonia (+136.1% [95% CI, 71.1-225.8], P < .001), and reoperation (+60.5% [95% CI, 21.5-111.9], P = .001).

Conclusions: Costs associated with minimally invasive esophagectomy are driven by preoperative risk factors and postoperative outcomes. These data enable surgeons and policymakers to reduce cost variation, improve quality through standardization, and ultimately provide greater value to patients.