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Meng Huang, Avery Buchholz, Anshit Goyal, Erica Bisson, Zoher Ghogawala, Eric Potts, John Knightly, Domagoj Coric, Anthony Asher, Kevin Foley, Praveen V. Mummaneni, Paul Park, Mark Shaffrey, Kai-Ming Fu, Jonathan Slotkin, Steven Glassman, Mohamad Bydon, and Michael Wang

Disability Index (ODI) was obtained from a preoperative patient interview. We separately queried the surgeon module of the QOD to obtain surgeon characteristics such as surgeon age, sex, race, fellowship training, and type of practice. Hospital-level information such as hospital location, ownership, and teaching status were also obtained from the NPA. The primary outcome of interest was type of surgery performed (decompression alone vs decompression with fusion). Statistical Analysis Continuous variables were displayed as means with standard deviations and were compared

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Siddhartha Singh, Rodney Sparapani, and Marjorie C. Wang

code was used alone in the lumbosacral spine (without any other procedure code denoting surgical approach), the procedure was classified as posterior. Surgeon and Hospital Characteristics Surgeon characteristics were obtained from the American Medical Association’s Physician Professional Database. Surgeons were included if they were orthopedic surgeons or neurosurgeons and had hospital claims associated with the admission for lumbar spine surgery in our defined cohort. Year of training was defined as years from completing residency to the hospital admission. Surgeon

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Anthony L. Asher, Clinton J. Devin, Panagiotis Kerezoudis, Hui Nian, Mohammed Ali Alvi, Inamullah Khan, Ahilan Sivaganesan, Frank E. Harrell Jr., Kristin R. Archer, and Mohamad Bydon

deficit, principal diagnosis, cervical instability). The following baseline patient-reported outcomes (PROs) were collected by an independent data coordinator (via phone or direct interview) not involved with clinical care and entered into the Research Electronic Data Capture: Neck Disability Index (NDI) 35 and numeric rating scale (NRS) for neck and arm pain. 21 We documented surgeon characteristics, such as profession (orthopedic vs neurological surgeon) and fellowship training ( Supplemental Table 1 ). We also recorded the institution where the patient underwent

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Mark P. Arts, Wilco C. Peul, Bart W. Koes, Ralph T. W. M. Thomeer, and for the Leiden–The Hague Spine Intervention Prognostic Study (SIPS) Group

orthopedic members of the Dutch Spine Society were sent a questionnaire by mail. The questionnaire referred to various aspects of surgical and postsurgical management of lumbar disc herniation, as follows: 1) surgeons' characteristics–age, sex, years of clinical experience, number of lumbar discectomies performed annually; 2) standard procedure; 3) expectations for clinical results of various surgical approaches in the short term (8 weeks) and long term (2 years) regarding leg pain and low-back pain, recurrence rate, and complication rate; 4) period of conservative

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William E. Whitehead, Jay Riva-Cambrin, John C. Wellons III, Abhaya V. Kulkarni, Richard Holubkov, Anna Illner, W. Jerry Oakes, Thomas G. Luerssen, Marion L. Walker, James M. Drake, and John R. W. Kestle

the foramen of Monro. Surgeon characteristics are detailed in Table 1 . The average number of years of experience was greater in the conventional surgeon group. TABLE 1: Surgeon characteristics * Parameter Novice w/ US Experienced w/ US Conventional Shunt Surgery no. of surgeons 2 † 10 6 ‡ surgeon experience in yrs  mean ± SD 17 ± 15.6 9.4 ± 6.9 17 ± 12.0  median (range) 17 (6–28) 6 (1.5–20) 12 (7–33) prestudy experience w/ ultrasound  >50 cases 0 9 surgeons NA  15

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Elyne N. Kahn, Chandy Ellimoottil, James M. Dupree, Paul Park, and Andrew M. Ryan

.1) Surgeon characteristics (n = 195)  No. of procedures, median (IQR) 68 (31–132) Hospital characteristics (n = 50)  No. of procedures, median (IQR) 292 (102–458) Mean price-standardized 90-day episode payments in the highest spending quintile exceeded mean payments for episodes in the lowest cost quintile by $42,953 (p < 0.001) ( Table 2 ). When evaluating the individual components of each 90-day episode, facility payments for the index admission and post-discharge payments were the greatest contributors to total variation (39.4% and 32.5%, respectively; Table 2 and

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Emad N. Eskandar, Alice Flaherty, G. Rees Cosgrove, Leslie A. Shinobu, and Fred G. Barker II

: Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy. Neurology 55 : 773 – 781 , 2000 O'Neill L, Lanska DJ, Hartz A: Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy. Neurology 55: 773–781, 2000 57. Pahwa R , Wilkinson S , Smith D , et al : High-frequency stimulation of the globus pallidus for the treatment of Parkinson's disease. Neurology 49 : 249 – 253 , 1997 Pahwa R, Wilkinson S, Smith D, et al: High

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Christine Park, Rasheedat T. Zakare-Fagbamila, Wes Dickson, Alessandra N. Garcia, and Oren N. Gottfried

used to summarize the surgeon characteristics at baseline. For the outcome measure, OHR, the degree of influence of a variable or survey item on the OHR was calculated as the odds ratio of receiving a top-box OHR given a specific value for that variable or a top-box score for that item. The odds ratios were derived from multivariate logistic regressions with OHR as the outcome. The first regression looked at the hospital admission variables (i.e., admitting hospital, department, subspecialty, patient sex, and month) as predictors of OHR in order to determine baseline

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Ashwin G. Ramayya, H. Isaac Chen, Paul J. Marcotte, Steven Brem, Eric L. Zager, Benjamin Osiemo, Matthew Piazza, Nikhil Sharma, Scott D. McClintock, James M. Schuster, Zarina S. Ali, Patrick Connolly, Gregory G. Heuer, M. Sean Grady, David K. Kung, Ali K. Ozturk, Donald M. O’Rourke, and Neil R. Malhotra

agreement). Although variables such as patient age and medical comorbidities are known to be important factors for surgical decision making, we did not find that general patient characteristics (including sex) predicted NFS score for surgery. We also found that surgeon characteristics had a limited impact on surgeon decision making/NFS scores. We speculate that our data set had limited variability in these factors for a given surgical category, and as such our study was not powered to detect these differences. When interpreting NFS and IRR scores in our study, it is

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Scott L. Parker, Matthew J. McGirt, Jeffrey A. Murphy, J. Thomas Megerian, Michael Stout, and Luella Engelhart

antibiotics. 1 , 46 Analyses of large administrative databases such as this one can provide valuable information but have inherent limitations with regard to determination of causality. As with all retrospective analyses, it was not possible to completely control for all patient and surgeon characteristics that may affect the selection of treatment or the risk of infection. It is possible that confounders not measured may have resulted in a bias of the data, and this should be kept in mind when interpreting our results. The observational design and potential unobserved