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## Quality Outcomes Database Spine Care Project 2012–2020: milestones achieved in a collaborative North American outcomes registry to advance value-based spine care and evolution to the American Spine Registry

The Quality Outcomes Database (QOD), formerly known as the National Neurosurgery Quality Outcomes Database (N2QOD), was established by the NeuroPoint Alliance (NPA) in collaboration with relevant national stakeholders and experts. The overarching goal of this project was to develop a centralized, nationally coordinated effort to allow individual surgeons and practice groups to collect, measure, and analyze practice patterns and neurosurgical outcomes. Specific objectives of this registry program were as follows: “1) to establish risk-adjusted national benchmarks for both the safety and effectiveness of neurosurgical procedures, 2) to allow practice groups and hospitals to analyze their individual morbidity and clinical outcomes in real time, 3) to generate both quality and efficiency data to support claims made to public and private payers and objectively demonstrate the value of care to other stakeholders, 4) to demonstrate the comparative effectiveness of neurosurgical and spine procedures, 5) to develop sophisticated ‘risk models’ to determine which subpopulations of patients are most likely to benefit from specific surgical interventions, and 6) to facilitate essential multicenter trials and other cooperative clinical studies.” The NPA has launched several neurosurgical specialty modules in the QOD program in the 7 years since its inception including lumbar spine, cervical spine, and spinal deformity and cerebrovascular and intracranial tumor. The QOD Spine modules, which are the primary subject of this paper, have evolved into the largest North American spine registries yet created and have resulted in unprecedented cooperative activities within our specialty and among affiliated spine care practitioners. Herein, the authors discuss the experience of QOD Spine programs to date, with a brief description of their inception, some of the key achievements and milestones, as well as the recent transition of the spine modules to the American Spine Registry (ASR), a collaboration between the American Association of Neurological Surgeons and the American Academy of Orthopaedic Surgeons (AAOS).

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## A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery: an analysis from the Quality Outcomes Database

### OBJECTIVE

Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery.

### METHODS

The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model.

### RESULTS

A total of 4689 patients were analyzed, of whom 82.2% (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3% (n = 3443) returned to work compared to 52.3% (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56–65 years: OR 0.69, 95% CI 0.57–0.85, p < 0.001; age > 65 years: OR 0.65, 95% CI 0.43–0.97, p = 0.02); were employed but not working (OR 0.24, 95% CI 0.20–0.29, p < 0.001); were employed part time (OR 0.56, 95% CI 0.42–0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95% CI 0.32–0.54, p < 0.001) or medium-intensity (OR 0.59, 95% CI 0.46–0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers’ compensation (OR 0.38, 95% CI 0.28–0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95% CI 0.51–0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95% CI 0.42–0.63, p < 0.001); and had more levels fused (3–5 levels: OR 0.46, 95% CI 0.35–0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity.

### CONCLUSIONS

Return to work is a crucial outcome that is being increasingly prioritized for employed patients undergoing spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.

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## Development and validation of a predictive model for 90-day readmission following elective spine surgery

### OBJECTIVE

Hospital readmissions lead to a significant increase in the total cost of care in patients undergoing elective spine surgery. Understanding factors associated with an increased risk of postoperative readmission could facilitate a reduction in such occurrences. The aims of this study were to develop and validate a predictive model for 90-day hospital readmission following elective spine surgery.

### METHODS

All patients undergoing elective spine surgery for degenerative disease were enrolled in a prospective longitudinal registry. All 90-day readmissions were prospectively recorded. For predictive modeling, all covariates were selected by choosing those variables that were significantly associated with readmission and by incorporating other relevant variables based on clinical intuition and the Akaike information criterion. Eighty percent of the sample was randomly selected for model development and 20% for model validation. Multiple logistic regression analysis was performed with Bayesian model averaging (BMA) to model the odds of 90-day readmission. Goodness of fit was assessed via the C-statistic, that is, the area under the receiver operating characteristic curve (AUC), using the training data set. Discrimination (predictive performance) was assessed using the C-statistic, as applied to the 20% validation data set.

### RESULTS

A total of 2803 consecutive patients were enrolled in the registry, and their data were analyzed for this study. Of this cohort, 227 (8.1%) patients were readmitted to the hospital (for any cause) within 90 days postoperatively. Variables significantly associated with an increased risk of readmission were as follows (OR [95% CI]): lumbar surgery 1.8 [1.1–2.8], government-issued insurance 2.0 [1.4–3.0], hypertension 2.1 [1.4–3.3], prior myocardial infarction 2.2 [1.2–3.8], diabetes 2.5 [1.7–3.7], and coagulation disorder 3.1 [1.6–5.8]. These variables, in addition to others determined a priori to be clinically relevant, comprised 32 inputs in the predictive model constructed using BMA. The AUC value for the training data set was 0.77 for model development and 0.76 for model validation.

### CONCLUSIONS

Identification of high-risk patients is feasible with the novel predictive model presented herein. Appropriate allocation of resources to reduce the postoperative incidence of readmission may reduce the readmission rate and the associated health care costs.

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## An analysis from the Quality Outcomes Database, Part 1. Disability, quality of life, and pain outcomes following lumbar spine surgery: predicting likely individual patient outcomes for shared decision-making

### OBJECTIVE

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.

### METHODS

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.

### RESULTS

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).

### CONCLUSIONS

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.

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## An analysis from the Quality Outcomes Database, Part 2. Predictive model for return to work after elective surgery for lumbar degenerative disease

### OBJECTIVE

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.

### METHODS

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).

### RESULTS

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.

### CONCLUSIONS

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.

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## Predictors of extended length of stay, discharge to inpatient rehab, and hospital readmission following elective lumbar spine surgery: introduction of the Carolina-Semmes Grading Scale

### OBJECTIVE

Extended hospital length of stay (LOS), unplanned hospital readmission, and need for inpatient rehabilitation after elective spine surgery contribute significantly to the variation in surgical health care costs. As novel payment models shift the risk of cost overruns from payers to providers, understanding patient-level risk of LOS, readmission, and inpatient rehabilitation is critical. The authors set out to develop a grading scale that effectively stratifies risk of these costly events after elective surgery for degenerative lumbar pathologies.

### METHODS

The Quality and Outcomes Database (QOD) registry prospectively enrolls patients undergoing surgery for degenerative lumbar spine disease. This registry was queried for patients who had undergone elective 1- to 3-level lumbar surgery for degenerative spine pathology. The association between preoperative patient variables and extended postoperative hospital LOS (LOS ≥ 7 days), discharge status (inpatient facility vs home), and 90-day hospital readmission was assessed using stepwise multivariate logistic regression. The Carolina-Semmes grading scale was constructed using the independent predictors for LOS (0–12 points), discharge to inpatient facility (0–18 points), and 90-day readmission (0–6 points), and its performance was assessed using the QOD data set. The performance of the grading scale was then confirmed separately after using it in 2 separate neurosurgery practice sites (Carolina Neurosurgery & Spine Associates [CNSA] and Semmes Murphey Clinic).

### RESULTS

A total of 6921 patients were analyzed. Overall, 290 (4.2%) patients required extended LOS, 654 (9.4%) required inpatient facility care/rehabilitation on hospital discharge, and 474 (6.8%) were readmitted to the hospital within 90 days postdischarge. Variables that remained as independently associated with these unplanned events in multivariate analysis included age ≥ 70 years, American Society of Anesthesiologists Physical Classification System class > III, Oswestry Disability Index score ≥ 70, diabetes, Medicare/Medicaid, nonindependent ambulation, and fusion. Increasing point totals in the Carolina-Semmes scale effectively stratified the incidence of extended LOS, discharge to facility, and readmission in a stepwise fashion in both the aggregate QOD data set and when subsequently applied to the CNSA/Semmes Murphey practice groups.

### CONCLUSIONS

The authors introduce the Carolina-Semmes grading scale that effectively stratifies the risk of prolonged hospital stay, need for postdischarge inpatient facility care, and 90-day hospital readmission for patients undergoing first-time elective 1- to 3-level degenerative lumbar spine surgery. This grading scale may be helpful in identifying patients who may require additional resource utilization within a global period after surgery.

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## Inadequacy of 3-month Oswestry Disability Index outcome for assessing individual longer-term patient experience after lumbar spine surgery

### OBJECTIVE

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.

### METHODS

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.

### RESULTS

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.

### CONCLUSIONS

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.

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## Anterior cervical discectomy and fusion in the outpatient ambulatory surgery setting compared with the inpatient hospital setting: analysis of 1000 consecutive cases

### OBJECTIVE

In an era of escalating health care costs and pressure to improve efficiency and cost of care, ambulatory surgery centers (ASCs) have emerged as lower-cost options for many surgical therapies. Anterior cervical discectomy and fusion (ACDF) is one of the most prevalent spine surgeries performed, and the frequency of its performance is rapidly increasing as the aging population grows. Although ASCs offer significant cost advantages over hospital-based surgical centers, concern over the safety of outpatient ACDF has slowed its adoption. The authors intended to 1) determine the safety of the first 1000 consecutive ACDF surgeries performed in their outpatient ASC, and 2) compare the safety of these outpatient ACDFs with that of consecutive ACDFs performed during the same time period in the hospital setting.

### METHODS

A total of 1000 consecutive patients who underwent ACDF in an ACS (outpatient ACDF) and 484 consecutive patients who underwent ACDF at Vanderbilt University Hospital (inpatient ACDF) from 2006 to 2013 were included in this retrospective study of patients' medical records. Data were collected on patient demographics, comorbidities, operative details, and perioperative and 90-day morbidity. Perioperative morbidity and hospital readmission were compared between the outpatient and inpatient ACDF groups.

### RESULTS

Of the first 1000 outpatient ACDF cases performed in the authors' ASC, 629 (62.9%) were 1-level and 365 (36.5%) were 2-level ACDFs. Mean patient age was 49.5 ± 8.6, and 484 (48.4%) were males. All patients were observed postoperatively at the ASC postanesthesia care unit (PACU) for 4 hours before being discharged home. Eight patients (0.8%) were transferred from the surgery center to the hospital postoperatively (for pain control [n = 3], chest pain and electrocardiogram changes [n = 2], intraoperative CSF leak [n = 1], postoperative hematoma [n = 1], and profound postoperative weakness and surgical reexploration [n = 1]). No perioperative deaths occurred. The 30-day hospital readmission rate was 2.2%. All 90-day surgical morbidity was similar between outpatient and inpatient cohorts for both 1-level and 2-level ACDFs.

### CONCLUSIONS

An analysis of 1000 consecutive patients who underwent ACDF in an outpatient setting demonstrates that surgical complications occur at a low rate (1%) and can be appropriately diagnosed and managed in a 4-hour ASC PACU window. Comparison with an inpatient ACDF surgery cohort demonstrated similar results, highlighting that ACDF can be safely performed in the outpatient ambulatory surgery setting without compromising surgical safety. In an effort to decrease costs of care, surgeons can safely perform 1- and 2-level ACDFs in an ASC environment.

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## Modeled cost-effectiveness of transforaminal lumbar interbody fusion compared with posterolateral fusion for spondylolisthesis using N2QOD data

### OBJECTIVE

Transforaminal lumbar interbody fusion (TLIF) has become the most commonly used fusion technique for lumbar degenerative disorders. This suggests an expectation of better clinical outcomes with this technique, but this has not been validated consistently. How surgical variables and choice of health utility measures drive the cost-effectiveness of TLIF relative to posterolateral fusion (PSF) has not been established. The authors used health utility values derived from Short Form-6D (SF-6D) and EQ-5D and different cost-effectiveness thresholds to evaluate the relative cost-effectiveness of TLIF compared with PSF.

### METHODS

From the National Neurosurgery Quality and Outcomes Database (N2QOD), 101 patients with spondylolisthesis who underwent PSF were propensity matched to patients who underwent TLIF. Health-related quality of life measures and perioperative parameters were compared. Because health utility values derived from the SF-6D and EQ-5D questionnaires have been shown to vary in patients with low-back pain, quality-adjusted life years (QALYs) were derived from both measures. On the basis of these matched cases, a sensitivity analysis for the relative cost per QALY of TLIF versus PSF was performed in a series of cost-assumption models.

### RESULTS

Operative time, blood loss, hospital stay, and 30-day and 90-day readmission rates were similar for the TLIF and PSF groups. Both TLIF and PSF significantly improved back and leg pain, Oswestry Disability Index (ODI) scores, and EQ-5D and SF-6D scores at 3 and 12 months postoperatively. At 12 months postoperatively, patients who had undergone TLIF had greater improvements in mean ODI scores (30.4 vs 21.1, p = 0.001) and mean SF-6D scores (0.16 vs 0.11, p = 0.001) but similar improvements in mean EQ-5D scores (0.25 vs 0.22, p = 0.415) as patients treated with PSF. At a cost per QALY threshold of $100,000 and using SF-6D–based QALYs, the authors found that TLIF would be cost-prohibitive compared with PSF at a surgical cost of$4830 above that of PSF. However, with EQ-5D–based QALYs, TLIF would become cost-prohibitive at an increased surgical cost of $2960 relative to that of PSF. With the 2014 US per capita gross domestic product of$53,042 as a more stringent cost-effectiveness threshold, TLIF would become cost-prohibitive at surgical costs $2562 above that of PSF with SF-6D–based QALYs or at a surgical cost exceeding that of PSF by$1570 with EQ-5D–derived QALYs.

### CONCLUSIONS

As with all cost-effectiveness studies, cost per QALY depended on the measure of health utility selected, durability of the intervention, readmission rates, and the accuracy of the cost assumptions.