title: The Need to Consider Longer-term Outcomes of Care: Racial/Ethnic Disparities Among Adult and Older Adult Emergency General Surgery Patients at 30, 90, and 180 Days.
abstract: Following calls from the National Institutes of Health and American College of Surgeons for "urgently needed" research, the objectives of the present study were to (1) ascertain whether differences in 30/90/180-day mortality, major morbidity, and unplanned readmissions exist among adult (18-64 yr) and older adult (≥65 yr) emergency general surgery (EGS) patients; (2) vary by diagnostic category; and (3) are explained by variations in insurance, income, teaching status, hospital EGS volume, and a hospital's proportion of minority patients.
  
  
  
  Racial/ethnic disparities have been described in in-hospital and 30-day settings. How longer-term outcomes compare-a critical consideration for the lived experience of patients-has, however, only been limitedly considered.
  
  
  
  Survival analysis of 2007 to 2011 California State Inpatient Database using Cox proportional hazards models.
  
  
  
  A total of 737,092 adults and 552,845 older adults were included. In both cohorts, significant differences in 30/90/180-day mortality, major morbidity, and unplanned readmissions were found, pointing to persistently worse outcomes between non-Hispanic Black and White patients [180-d readmission hazard ratio (95% confidence interval):1.04 (1.03-1.06)] and paradoxically better outcomes among Hispanic adults [0.85 (0.84-0.86)] that were not encountered among Hispanic older adults [1.06 (1.04-1.07)]. Stratified results demonstrated robust morbidity and readmission trends between non-Hispanic Black and White patients for the majority of diagnostic categories, whereas variations in insurance/income/teaching status/EGS volume/proportion of minority patients all significantly altered the effect-combined accounting for up to 80% of risk-adjusted differences between racial/ethnic groups.
  
  
  
  Racial/ethnic disparities exist in longer-term outcomes of EGS patients and are, in part, determined by differences in factors associated with emergency care. Efforts such as these are needed to understand the interplay of influences-both in-hospital and during the equally critical, postacute phase-that underlie disparities' occurrence among surgical patients.
authors.affiliation: *Center for Surgery and Public Health: Department of Surgery: Brigham and Women's Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA †Yale School of Medicine, New Haven, CT ‡Division of Trauma, Burn, and Surgical Critical Care, Brigham and Women's Hospital, Boston, MA §Department of Surgery, Baylor and Scott White Health, Dallas, TX ¶Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, MA.
authors.forename: Cheryl K
authors.initials: CK
authors.lastname: Zogg
authors.forename: Olubode A
authors.initials: OA
authors.lastname: Olufajo
authors.forename: Wei
authors.initials: W
authors.lastname: Jiang
authors.forename: Anna
authors.initials: A
authors.lastname: Bystricky
authors.forename: John W
authors.initials: JW
authors.lastname: Scott
authors.forename: Shahid
authors.initials: S
authors.lastname: Shafi
authors.forename: Joaquim M
authors.initials: JM
authors.lastname: Havens
authors.forename: Ali
authors.initials: A
authors.lastname: Salim
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Schoenfeld
authors.forename: Adil H
authors.initials: AH
authors.lastname: Haider
mesh_terms: D000293:Adolescent; D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D002140:California; D004636:Emergency Service, Hospital / Q000592:standards* / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000208:ethnology*; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D017052:Hospital Mortality; D006801:Humans; D007182:Income; D019458:Insurance Coverage; D007348:Insurance, Health; D008137:Longitudinal Studies; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010359:Patient Readmission / Q000706:statistics & numerical data; D011183:Postoperative Complications / Q000208:ethnology*; D016016:Proportional Hazards Models; D013514:Surgical Procedures, Operative / Q000009:adverse effects*; D016019:Survival Analysis; D044465:White People / Q000706:statistics & numerical data; D055815:Young Adult