Examining and Understanding Value: The Cost of Preoperative Characteristics, Intraoperative Variables and Postoperative Complications of Minimally Invasive Partial Nephrectomy

Abstract

INTRODUCTION: As value based health care gains favor and reimbursement models move toward quality rather than quantity of care, a better understanding of cost and its predictors becomes increasingly important. We identified how preoperative characteristics, intraoperative variables and postoperative complications impact the cost of partial nephrectomy. METHODS: Our institution's ACS NSQIP® (American College of Surgeons National Surgical Quality Improvement Program) database was accessed for minimally invasive partial nephrectomy performed from January 2012 to March 2017. Perioperative and financial data were collected through retrospective chart review. Total cost and direct cost were analyzed relative to clinical variables. RESULTS: A total of 215 minimally invasive partial nephrectomies were included in the study. Median total cost was $17,000 and median direct cost was $11,500. Among preoperative characteristics age 56 to 65 years and diabetes were associated with an increased median direct cost of $2,000 and $800, respectively. ASA® (American Society of Anesthesiologists®) class III was associated with an increased direct cost of $1,400 compared to ASA class I-II. Among intraoperative variables increased operative duration was associated with increased direct cost. Robot-assisted cases increased direct cost by $3,000. Estimated blood loss greater than 250 cc was associated with an increased direct cost of $800. R.E.N.A.L. score did not affect cost parameters. Patients who experienced any postoperative complications had an increased direct cost compared to those who did not. Blood transfusions were associated with an increased direct cost of $3,700 and unplanned reintubation $14,500. On multivariable analysis age, operative duration, robot use and complications retained significance. CONCLUSIONS: Age, diabetes, ASA class, operative duration, estimated blood loss, robot use and postoperative complications are associated with increased cost. Increased understanding of cost predictors can be used to optimize perioperative care and value, and contribute to improved alternative reimbursement models.