Socioeconomic Influence on Cervical Fusion Outcomes

Study Design: A retrospective observational study. Objective: The aim of this study was to compare postoperative outcomes following cervical fusion based on socioeconomic status (SES) variables including race, education, net worth, and homeownership status. Summary of Background Data: Previous studies have demonstrated the effects of patient race and income on outcomes following cervical fusion procedures. However, no study to date has comprehensively examined the impact of multiple SES variables. We hypothesized that race, education, net worth, and homeownership influence important outcomes following cervical fusion. Materials and Methods: Optum's de-identified Clinformatics Data Mart (CDM) database was queried for patients undergoing first-time inpatient cervical fusion from 2003 to 2021. Patient demographics, SES variables, and the Charlson comorbidity index were obtained. Primary outcomes were hospital length of stay and 30-day rates of reoperation, readmission, and postoperative complications. Secondary outcomes included postoperative emergency room visits, discharge status, and total hospital charges. Results: A total of 111,914 patients underwent cervical spinal fusion from 2003 to 2021. Multivariate analysis revealed that after controlling for age, sex, and Charlson comorbidity index, Black race was associated with a higher rate of 30-day readmissions [odds ratio (OR): 1.11, 95% CI: 1.03-1.20]. Lower net worth (vs. >$500K) and renting (vs. owning a home) were significantly associated with both higher rates of 30-day readmissions (OR: 1.29, 95% CI: 1.17-1.41; OR: 1.34, 95% CI: 1.22-1.49), and emergency room visits (OR: 1.29, 95% CI: 1.18-1.42; OR: 1.11, 95% CI: 1.00-1.23). Lower net worth (vs. >$500K) was also associated with increased complications (OR: 1.22, 95% CI: 1.14-1.31). Conclusion: Socioeconomic variables, including patient race, education, and net worth, influence postoperative metrics in cervical spinal fusion surgery. Future studies should focus on developing and implementing targeted interventions based on patient SES to reduce disparity.