Toward a Candidate Endoscopic Spine Surgery Registry Framework: Lessons From Global Spine Registry Models.

OBJECTIVE: Endoscopic spine surgery (ESS) has expanded rapidly, but existing spine registries do not consistently capture ESS-specific technical variables, ultra-early recovery trajectories, selective imaging validation, or dissemination-related learning-curve effects. This review synthesizes established spine registry models, contemporary consensus initiatives, and digital follow-up approaches to propose a candidate ESS-specific registry framework and preliminary Minimum Data Set (MDS) for future validation. METHODS: A structured narrative review was conducted on national and multinational spine registries, relevant consensus initiatives, and digital follow-up models. Sources were reviewed with emphasis on governance, data architecture, workflow design, patient-reported outcome measures (PROMs) integration, follow-up structure, data linkage, validation strategies, and implementation feasibility. RESULTS: Established registries provide a methodological foundation for benchmarking, complication surveillance, longitudinal PROM capture, and real-world evidence generation. However, ESS requires modular augmentation of existing registry infrastructures to capture approach-specific operative details, early recovery, selective imaging phenotypes, and governance-controlled maturity indicators. The proposed candidate MDS is organized into 4 domains: (1) baseline case-mix and phenotyping, (2) procedure-specific technical and perioperative variables, (3) selective quantitative imaging and morphometric validation, and (4) structured longitudinal outcome surveillance. The framework prioritizes an essential core dataset while separating recommended, optional, research-oriented, and governance-controlled modules, including digitally enabled early follow-up, opioid-related outcomes, radiation exposure, advanced imaging, and learning-curve variables. CONCLUSION: A candidate ESS-specific registry framework may support harmonized data capture, real-world evidence generation, quality feedback, and future registry-based research. Formal Delphi consensus, multicenter feasibility testing, and staged integration into existing spine registry infrastructures are required before broader implementation.