Multidisciplinary Approaches to the Management of Spinal Care: A Narrative Review

Abstract

For patients with spinal care conditions including degenerative disease, deformity, traumatic injury, and complex pain syndromes, care is frequently fragmented across multiple specialists. This process can delay diagnosis, create complexity in communication, and result in inconsistencies in treatment decisions. Multidisciplinary spine clinics have been proposed as one approach to these challenges by bringing key providers together in a coordinated setting. In this narrative review, we examine recent studies comparing multidisciplinary models with traditional fragmented approaches to spine care. Integrated clinics are frequently associated with more consistent decision-making, improved coordination of care, and earlier access to both conservative treatment and surgical evaluation. Several studies indicate lower complication or reoperation rates, although findings vary by patient population and study design. Patient-reported measures of pain, function, satisfaction, and quality of life are generally similar or modestly improved in multidisciplinary settings. Practical advantages include shorter wait times for imaging, improved provider-to-provider communication, and more efficient preoperative preparation. This review addresses a timely gap in the literature by synthesizing evidence within the current context of AI-assisted decision support, value-based care reform, and evolving ERAS protocols, providing an actionable framework for institutions seeking to implement or expand integrated spine care. Clinic infrastructure barriers, reimbursement issues, scheduling demands, and inequitable access continue to limit broader adoption. Future research should prioritize prospective and multicenter studies and explore how tools such as telehealth and artificial intelligence may support and expand multidisciplinary spine care. Multidisciplinary spine clinics reduce complication rates, unnecessary surgeries, and delays to care compared with fragmented delivery models. Integrated teams including surgeons, physiatrists, pain specialists, PT/OT, psychologists, pulmonologists, and cardiologists improve perioperative optimization and patient-centered outcomes. Artificial intelligence and machine learning hold promise for surgical outcome prediction, patient stratification, and imaging-based deformity analysis, but bias and external validity concerns must be addressed before widespread adoption. Value-based reimbursement models, including bundled payments, are essential policy levers for sustaining and expanding multidisciplinary spine care. Health equity remains a critical gap: geographic, insurance-related, and socioeconomic barriers disproportionately limit access to integrated spine care, and future research must prioritize underserved populations. Multidisciplinary spine clinics reduce complication rates, unnecessary surgeries, and delays to care compared with fragmented delivery models. Integrated teams including surgeons, physiatrists, pain specialists, PT/OT, psychologists, pulmonologists, and cardiologists improve perioperative optimization and patient-centered outcomes. Artificial intelligence and machine learning hold promise for surgical outcome prediction, patient stratification, and imaging-based deformity analysis, but bias and external validity concerns must be addressed before widespread adoption. Value-based reimbursement models, including bundled payments, are essential policy levers for sustaining and expanding multidisciplinary spine care. Health equity remains a critical gap: geographic, insurance-related, and socioeconomic barriers disproportionately limit access to integrated spine care, and future research must prioritize underserved populations.