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.
Matthew J. McGirt, Theodore Speroff, Robert S. Dittus, Frank E. Harrell Jr. and Anthony L. Asher
Matthew J. McGirt, Mohamad Bydon, Kristin R. Archer, Clinton J. Devin, Silky Chotai, Scott L. Parker, Hui Nian, Frank E. Harrell Jr., Theodore Speroff, Robert S. Dittus, Sharon E. Philips, Christopher I. Shaffrey, Kevin T. Foley and Anthony L. Asher
Quality and outcomes registry platforms lie at the center of many emerging evidence-driven reform models. Specifically, clinical registry data are progressively informing health care decision-making. In this analysis, the authors used data from a national prospective outcomes registry (the Quality Outcomes Database) to develop a predictive model for 12-month postoperative pain, disability, and quality of life (QOL) in patients undergoing elective lumbar spine surgery.
Included in this analysis were 7618 patients who had completed 12 months of follow-up. The authors prospectively assessed baseline and 12-month patient-reported outcomes (PROs) via telephone interviews. The PROs assessed were those ascertained using the Oswestry Disability Index (ODI), EQ-5D, and numeric rating scale (NRS) for back pain (BP) and leg pain (LP). Variables analyzed for the predictive model included age, gender, body mass index, race, education level, history of prior surgery, smoking status, comorbid conditions, American Society of Anesthesiologists (ASA) score, symptom duration, indication for surgery, number of levels surgically treated, history of fusion surgery, surgical approach, receipt of workers’ compensation, liability insurance, insurance status, and ambulatory ability. To create a predictive model, each 12-month PRO was treated as an ordinal dependent variable and a separate proportional-odds ordinal logistic regression model was fitted for each PRO.
There was a significant improvement in all PROs (p < 0.0001) at 12 months following lumbar spine surgery. The most important predictors of overall disability, QOL, and pain outcomes following lumbar spine surgery were employment status, baseline NRS-BP scores, psychological distress, baseline ODI scores, level of education, workers’ compensation status, symptom duration, race, baseline NRS-LP scores, ASA score, age, predominant symptom, smoking status, and insurance status. The prediction discrimination of the 4 separate novel predictive models was good, with a c-index of 0.69 for ODI, 0.69 for EQ-5D, 0.67 for NRS-BP, and 0.64 for NRS-LP (i.e., good concordance between predicted outcomes and observed outcomes).
This study found that preoperative patient-specific factors derived from a prospective national outcomes registry significantly influence PRO measures of treatment effectiveness at 12 months after lumbar surgery. Novel predictive models constructed with these data hold the potential to improve surgical effectiveness and the overall value of spine surgery by optimizing patient selection and identifying important modifiable factors before a surgery even takes place. Furthermore, these models can advance patient-focused care when used as shared decision-making tools during preoperative patient counseling.
Anthony L. Asher, Clinton J. Devin, Kristin R. Archer, Silky Chotai, Scott L. Parker, Mohamad Bydon, Hui Nian, Frank E. Harrell Jr., Theodore Speroff, Robert S. Dittus, Sharon E. Philips, Christopher I. Shaffrey, Kevin T. Foley and Matthew J. McGirt
Current costs associated with spine care are unsustainable. Productivity loss and time away from work for patients who were once gainfully employed contributes greatly to the financial burden experienced by individuals and, more broadly, society. Therefore, it is vital to identify the factors associated with return to work (RTW) after lumbar spine surgery. In this analysis, the authors used data from a national prospective outcomes registry to create a predictive model of patients’ ability to RTW after undergoing lumbar spine surgery for degenerative spine disease.
Data from 4694 patients who underwent elective spine surgery for degenerative lumbar disease, who had been employed preoperatively, and who had completed a 3-month follow-up evaluation, were entered into a prospective, multicenter registry. Patient-reported outcomes—Oswestry Disability Index (ODI), numeric rating scale (NRS) for back pain (BP) and leg pain (LP), and EQ-5D scores—were recorded at baseline and at 3 months postoperatively. The time to RTW was defined as the period between operation and date of returning to work. A multivariable Cox proportional hazards regression model, including an array of preoperative factors, was fitted for RTW. The model performance was measured using the concordance index (c-index).
Eighty-two percent of patients (n = 3855) returned to work within 3 months postoperatively. The risk-adjusted predictors of a lower likelihood of RTW were being preoperatively employed but not working at the time of presentation, manual labor as an occupation, worker’s compensation, liability insurance for disability, higher preoperative ODI score, higher preoperative NRS-BP score, and demographic factors such as female sex, African American race, history of diabetes, and higher American Society of Anesthesiologists score. The likelihood of a RTW within 3 months was higher in patients with higher education level than in those with less than high school–level education. The c-index of the model’s performance was 0.71.
This study presents a novel predictive model for the probability of returning to work after lumbar spine surgery. Spine care providers can use this model to educate patients and encourage them in shared decision-making regarding the RTW outcome. This evidence-based decision support will result in better communication between patients and clinicians and improve postoperative recovery expectations, which will ultimately increase the likelihood of a positive RTW trajectory.
Anthony L. Asher, Silky Chotai, Clinton J. Devin, Theodore Speroff, Frank E. Harrell Jr., Hui Nian, Robert S. Dittus, Praveen V. Mummaneni, John J. Knightly, Steven D. Glassman, Mohamad Bydon, Kristin R. Archer, Kevin T. Foley and Matthew J. McGirt
Prospective longitudinal outcomes registries are at the center of evidence-driven health care reform. Obtaining real-world outcomes data at 12 months can be costly and challenging. In the present study, the authors analyzed whether 3-month outcome measurements sufficiently represent 12-month outcomes for patients with degenerative lumbar disease undergoing surgery.
Data from 3073 patients undergoing elective spine surgery for degenerative lumbar disease were entered into a prospective multicenter registry (N2QOD). Baseline, 3-month, and 12-month follow-up Oswestry Disability Index (ODI) scores were recorded. The absolute differences between actual 12- and 3-month ODI scores was evaluated. Additionally, the authors analyzed the absolute difference between actual 12-month ODI scores and a model-predicted 12-month ODI score (the model used patients' baseline characteristics and actual 3-month scores). The minimal clinically important difference (MCID) for ODI of 12.8 points and the substantial clinical benefit (SCB) for ODI of 18.8 points were used based on the previously published values. The concordance rate of achieving MCID and SCB for ODI at 3-and 12-months was computed.
The 3-month ODI scores differed from 12-month scores by an absolute difference of 11.9 ± 10.8, and predictive modeling estimations of 12-month ODI scores differed from actual 12-month scores by a mean (± SD) of 10.7 ± 9.0 points (p = 0.001). Sixty-four percent of patients (n = 1982) achieved an MCID for ODI at 3 months in comparison with 67% of patients (n = 2088) by 12 months; 51% (n = 1731) and 61% (n = 1860) of patients achieved SCB for ODI at 3 months and 12 months, respectively. Almost 20% of patients had ODI scores that varied at least 20 points (the point span of an ODI functional category) between actual 3- and 12-month values. In the aggregate analysis of achieving MCID, 77% of patients were concordant and 23% were discordant in achieving or not achieving MCID at 3 and 12 months. The discordance rates of achieving or not achieving MCID for ODI were in the range of 19% to 27% for all diagnoses and treatments (decompression with and without fusion). The positive and negative predictive value of 3-months ODI to predict 12-month ODI was 86% and 60% for MCID and 82% and 67% for SCB.
Based on their findings, the authors conclude the following: 1) Predictive methods for functional outcome based on early patient experience (i.e., baseline and/or 3-month data) should be used to help evaluate the effectiveness of procedures in patient populations, rather than serving as a proxy for long-term individual patient experience. 2) Prospective longitudinal registries need to span at least 12 months to determine the effectiveness of spine care at the individual patient and practitioner level.