148 Predictive Model for Return to Work After Elective Surgery for Lumbar Degenerative Disease: An Analysis From National Neurosurgery Quality Outcomes Database Registry

• Published in: Neurosurgery Vol. 63; no. CN_suppl_1; p. 160
• Main Authors: Asher, Anthony L., Chotai, Silky, Devin, Clinton J., Archer-Swygert, Kristen, Parker, Scott L., Bydon, Mohamad, Hui, Nian, Harrell, Frank, Speroff, Theodore, Dittus, Robert, Philips, Sharon, Shaffrey, Christopher I., Foley, Kevin T., McGirt, Matthew J.
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.08.2016; Copyright by the Congress of Neurological Surgeons; Wolters Kluwer Health, Inc
• Subjects: Back surgery; Databases, Factual; Elective Surgical Procedures - statistics & numerical data; Humans; Liability insurance; Lumbosacral Region - surgery; Models, Statistical; Neurosurgery; Neurosurgical Procedures - statistics & numerical data; Registries; Return to Work - statistics & numerical data; Surgery; Treatment Outcome
• ISSN: 0148-396X; 1524-4040
• DOI: 10.1227/01.neu.0000489717.75196.e5

Abstract INTRODUCTION: The current costs associated with spine care are unsustainable. The productivity loss and time away from work in gainfully employed patients contributes greatly to the financial burden. Therefore, it is vital to identify the factors associated with returning to work after lumbar spine surgery. We present a predictive model of ability to return to work (RTW) after lumbar spine surgery for degenerative spine disease. METHODS: Total 4694 patients undergoing elective spine surgery for degenerative lumbar disease who were employed were entered into a prospective multicenter registry (N2QOD). Baseline and 3-month postoperative patient-reported outcomes: Oswestry Disability Index (ODI), EQ-5D, NRS back and leg pain were recorded. The time to RTW was defined as the period between operation time and date of returning to work. A multivariable Cox proportional hazards regression model, including an array of preoperative factors, was fitted for RTW. The model performance was measured by the c-index. RESULTS: Eighty-two percent of patients (n = 3855) returned to work within 3 -months postoperatively. The risk-adjusted predictors of lower likelihood of RTW were preoperatively employed but not working at the time of presentation, those occupied with manual labor, on worker's compensation, on liability insurance, baseline ODI and NRS-BP scores, female sex, African American race, history of diabetes mellitus, and higher ASA grades. The likelihood of RTW within 3 months was higher in patients with higher education level compared with those with less than high school level education. The c-index of our model performance was 0.71. CONCLUSION: We present a novel predictive model for probability of RTW after lumbar spine surgery. Spine care providers can use this model to educate patients and encourage them in shared decision making regarding the RTW outcome. This will result in better communication between patients and clinicians and improve recovery expectations, which will ultimately increase the likelihood of a positive RTW trajectory.