Predictors of home discharge after scheduled surgery for degenerative cervical myelopathy

OBJECTIVE: Degenerative cervical myelopathy (DCM) is an important public health issue. Surgery is the mainstay of treatment for moderate and severe DCM. Delayed discharge of patients after DCM surgery is associated with increased healthcare costs. There is a paucity of data regarding predictive factors for discharge destination after scheduled surgery for patients with DCM. The purpose of this study was to identify factors predictive of home versus nonhome discharge after DCM surgery. METHODS: Patients undergoing scheduled DCM surgery who had been enrolled in a prospective DCM substudy of the Canadian Spine Outcomes and Research Network registry between January 2015 and October 2020 were included in this retrospective analysis. Patient data were evaluated to identify potential factors predictive of home discharge after surgery. Logistic regression was used to identify independent factors predictive of home discharge. A multivariable model was then used as a final model. RESULTS: Overall, 639 patients were included in the initial analysis, 543 (85%) of whom were discharged home. The mean age of the entire cohort was 60 years (SD 11.8 years), with a BMI of 28.9 (SD 5.7). Overall, 61.7% of the patients were female. The mean length of stay was 2.72 days (SD 1.7 days). The final internally validated bootstrapped multivariable model revealed that younger age, higher 9-Item Patient Health Questionnaire score, lower Neck Disability Index scores, fewer operated levels, mJOA scores indicating mild disease, anterior cervical discectomy and fusion procedure, and no perioperative adverse effects were predictive of home discharge. CONCLUSIONS: Younger age, less neck-related disability, fewer operated levels, more significant depression, less severe myelopathy, anterior cervical discectomy and fusion procedure, and no perioperative adverse effects are predictive of home discharge after surgery for DCM. These factors can help to guide clinical decision-making and optimize postoperative care pathways.