The national neurosurgery quality and outcomes database (N2QOD): General overview and pilot-year project description

Abstract

Given the unsustainable costs of US health care, universal agreement exists among payers, regulatory agencies, and other health care stakeholders that reform must include substantial improvements in the quality, effectiveness, and value of health care delivery. The Institute of Medicine and the American Recovery and Reinvestment Act of 2009 have called for the establishment of prospective registries to capture patient-centered data from real-world practice as a high priority to guide evidence-based reform. As a result, the American Association of Neurological Surgeons launched the National Neurosurgery Quality and Outcomes Database (N2QOD) and began enrolling patients in March 2012 into its initial pilot project: a web-based lumbar spine module. As a nationwide, prospective longitudinal registry utilizing patient reported outcome instruments, the N2QOD lumbar spine surgery pilot aims to systematically measure and aggregate surgical safety and 1-year postoperative outcome data from approximately 30 neurosurgical practices across the US with the primary aim of demonstrating the feasibility and validity of standardized 1-year outcome measurement from everyday real-world practice. At the end of the pilot year, 1) risk-adjusted modeling will be developed for the safety, quality, and effectiveness of lumbar surgical care (morbidity, readmission, improvements in pain, disability, quality of life, and return to work); 2) data integrity and validation will be demonstrated via internal quality control analyses and auditing, and 3) the feasibility of obtaining a high level of follow-up (~80%) of nationwide 1-year outcome measurement will be established. N2QOD will use only prospective clinical data, will avoid the use of administrative data proxies, and will rely on neurosurgically relevant risk factors for risk adjustment. Once national benchmarks of quality and effectiveness are accurately established and validated utilizing practice-based data extractors in the pilot year, N2QOD aims to introduce non-full-time employee (FTE)-dependent methodologies such as electronic medical record auto-extraction. N2QOD's non-FTE-dependent methodologies can then be validated against practice-based data extractor-derived measures of safety and effectiveness with the aim of more rapid expansion into the majority of US practice groups. The general overview, methods, and registry design of the N2QOD pilot year (lumbar module) are presented here. © AANS, 2013.