Study design: Retrospective review of a prospective cohort.
Objective: To determine the incidence, causes, and risk factors for 30-day unplanned readmissions after lumbar spine surgery.
Summary of background data: The rising costs associated with lumbar spinal surgery have received national attention. Recently, the government has chosen to target 30-day readmissions as a quality measure. Few studies have specifically analyzed the incidence, causes, and risk factors for readmission in a multicenter patient cohort.
Methods: A large, multicenter clinical registry was queried for all patients undergoing lumbar spine surgery in 2012. Current Procedural Terminology codes were used to select patients undergoing lumbar discectomy, laminectomy, anterior and posterior fusions, and multilevel deformity surgery. Thirty-day readmissions rates and causes were identified and analyzed. Univariate and multivariate logistic regression analyses were used to identify patient characteristics, comorbidities, and operative variables predictive of readmission.
Results: Overall, 695 of 15,668 patients undergoing lumbar spine surgery had unplanned 30-day hospital readmissions (4.4%). When separated by procedure type, readmissions were lowest after discectomy, 3.3%, and highest after deformity surgery, 9.0% (P < 0.001). The top causes for readmission were wound-related (38.6%), pain-related (22.4%), thromboembolic (9.4%), and systemic infections (8.0%). Predictors of readmission included advanced patient age more than 80 years (P = 0.03), African American race (P = 0.03), recent weight loss (P = 0.04), chronic obstructive pulmonary disorder (P < 0.01), history of cancer (P = 0.04), creatinine more than 1.2 (P < 0.01), elevated ASA class (P = 0.01), operative time more than 4 hours (P = 0.01), and prolonged hospital length of stay more than 4 days (P < 0.01).
Conclusion: Thirty-day unplanned readmission rates increased with procedure invasiveness. Both medical and surgical reasons contributed to readmission, many unavoidable. Surgeons should explore optimization measures for those at risk of early, unplanned readmission.
Level of evidence: 3.