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Ryan G. Chiu, Blake E. Murphy, David M. Rosenberg, Amy Q. Zhu, and Ankit I. Mehta

nonprofit hospitals in the setting of ICH. Methods Data Source The National Inpatient Sample (NIS) is the largest all-payer inpatient care database in the United States, containing data from approximately 8 million unique hospitalizations annually across a 20% sample of US hospitals. 14 , 21 NIS core files (containing variables associated with inpatient care) and severity measures files (patient morbidity information) for the years 2012 to 2016 were merged and then combined with hospital weights files, which contained information regarding hospital ownership. Discharges

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Shenae Samuels, Rebekah Kimball, Vivian Hagerty, Tamar Levene, Howard B. Levene, and Heather Spader

categorized based on ownership type, primarily falling into one of 3 categories: state/local government, nonprofit, and for-profit hospitals. Hospital ownership type has been associated with outcome, length of stay (LOS), and cost for many conditions. 7–11 Hospitals can also be categorized based on children's hospital status. In addition to freestanding children's hospitals, pediatric patients can be treated in a children's unit within a general hospital or in a general hospital without a dedicated children's unit. The goal of this study was to compare inpatient outcomes

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Whitney E. Muhlestein, Dallin S. Akagi, Amy R. McManus, and Lola B. Chambless

as a variable. Analysis of ensemble 2 showed that nonelective admission, non-Southern hospital geography, the presence of any postoperative complication, non-white race, and surgery at private investor hospital most strongly predict higher total charges. Given their importance in ensemble 1, it is likely that admission type, hospital region, and patient race exert their influence on ensemble predictions at least partially independent of their influence on LOS. Hospital ownership type was the 6th most important variable in ensemble 1, so we were also unsurprised to

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.3171/2017.4.FOC-LSRSabstracts 2017.4.FOC-LSRSABSTRACTS Abstract Poster 07. Hospital Ownership and Teaching Status Affects Perioperative Outcomes Following Lumbar Spinal Fusion Wesley Durand , ScB 1 , Joseph Johnson , ScB (2018) 2 , Neill Li , BS, MD 3 , JaeWon Yang , BA 1 , Adam Eltorai , BA 4 , J. Mason DePasse , MD 5 , and Alan Daniels , MD 6 1 Brown University, Warren Alpert Medical School, Providence, RI 2 Brown University, Providence, RI 3 Department of Orthopaedics, Warren

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Jonathan Dallas, Chevis N. Shannon, and Christopher M. Bonfield

Collection After the study cohort was identified, data pertaining to each patient were collected. Available sociodemographic characteristics included age, sex, race, primary insurance, income quartile, and National Center for Health Statistics (NCHS) status (a system that details the urban/rural classification of a patient’s household). Baseline hospital characteristics included bedsize, urban/rural and teaching status, US census region, and hospital ownership; annual NMS fusion volume was subsequently calculated based on the number of times an individual hospital was

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Ashish Sonig, Imad Saeed Khan, Rishi Wadhwa, Jai Deep Thakur, and Anil Nanda

in various regions. 2) Hospital ownership. The data were analyzed based on the following parameters: government, private and non-profit, private, and investor owned. We collapsed the categories into government and private. 3) Hospital location. The location of a hospital was divided into rural and urban areas. 4) Hospital bedsize. In the NIS database, hospitals are classified on the basis of bedsize as small, medium, and large. The details are provided in Table 1 . Different regions have different definitions of hospital bedsize. 5) Teaching status of the hospital

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Nathan J. Lee, Michael W. Fields, Venkat Boddapati, Meghan Cerpa, Jalen Dansby, James D. Lin, Zeeshan M. Sardar, Ronald Lehman Jr., and Lawrence Lenke

, sex, insurance type, and income level; comorbidities, including anemia, coagulopathy, chronic pulmonary disease, depression, diabetes, hypothyroidism, hypertension, liver disease, fluid and electrolyte disorders, pulmonary circulation disorders, renal failure, valvular disease, obesity, and weight loss; and hospital characteristics, including teaching status, hospital ownership, discharge disposition, and length of stay (LOS). Additional predictor variables were queried based on the following ICD-9 diagnosis and procedure codes: smoker (305.1, v158.2), chronic

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Oliver Y. Tang, Krissia M. Rivera Perla, Rachel K. Lim, James S. Yoon, Robert J. Weil, and Steven A. Toms

surgical outcomes after hospital consolidation: implications for local health care delivery . Surgery . 2016 ; 160 ( 5 ): 1155 – 1161 . 30 Baker LC , Bundorf MK , Kessler DP . Vertical integration: hospital ownership of physician practices is associated with higher prices and spending . Health Aff (Millwood) . 2014 ; 33 ( 5 ): 756 – 763 . 31 Huppertz JW , Bowman RA , Bizer GY , Hospital advertising, competition, and HCAHPS: does it pay to advertise? Health Serv Res . 2017 ; 52 ( 4 ): 1590 – 1611 . 32 Clyde AT , Bockstedt L , Farkas JA

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Oliver Y. Tang, James S. Yoon, Anna R. Kimata, and Michael T. Lawton

.4%)  Black 11,625 (14.2%)  Hispanic 16,062 (19.7%)  Asian 1,979 (2.4%)  Native American 868 (1.1%)  Other 4,192 (5.1%) Insurance status  Medicaid 40,376 (38.2%)  Private insurance 53,925 (51.0%)  Self-pay 5,493 (5.2%)  No charge 238 (0.2%)  Other 5,729 (5.4%) Income level of zip code  Quartile 1 (bottom) 28,359 (29.8%)  Quartile 2 24,940 (26.2%)  Quartile 3 22,744 (23.9%)  Quartile 4 (top) 19,231 (20.2%) Hospital ownership  Government, nonfederal 21,012 (20.3%)  Private, nonprofit 76,673 (74.1%)  Private, for-profit 5,759 (5.6%) Hospital location & teaching status  Rural 2

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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

1,019 (53.2) 6,312 (62.7) 7,331 (61.2)  Rural 169 (8.8) 979 (9.7) 1,148 (9.6)  Suburban 729 (38.0) 2,780 (27.6) 3,509 (29.3) Hospital teaching status, no. (%) <0.001  No. missing data 63 247 310  Teaching 1,325 (68.8) 6,142 (60.9) 7,467 (62.2)  Nonteaching 600 (31.2) 3,945 (39.1) 4,545 (37.8) Hospital ownership, no. (%) 0.001  No. missing data 71 263 334  Private, nonprofit 1,500 (78.2) 7,570 (75.2) 9,070 (75.7)  Government