title: Racial Disparities in Access and Outcomes of Cholecystectomy in the United States.
abstract: Disparities in access to health care between white and minority patients are well described. We aimed to analyze the trends and outcomes of cholecystectomy based on racial classification. The Nationwide Inpatient Sample database was reviewed for all patients undergoing cholecystectomy from 2009 to 2012. Patients were stratified as white or non-white. A total of 243,536 patients were analyzed: 159,901 white and 83,635 non-white. Non-white patients had significantly higher proportions of Medicaid (25% vs 9.3%), self-pay (14% vs 7.1%), and no-charge (1.8% vs 0.64%). Non-white patients had significantly higher rates of emergent admission (84% vs 78%) compared with the white patients. Multivariate analysis revealed that non-whites had a significantly longer length of stay [mean difference of 0.14 days, 95% confidence interval (CI) 0.08-0.20] and higher total hospital charges (mean difference of $6748.00, 95% CI 5994.19-7501.81) than whites, despite a lower morbidity (odds ratio 0.94, 95% CI 0.90-0.98). Use of laparoscopy and mortality were not different. These differences persisted on subgroup analysis by insurance type. These findings suggest a gap in access to and outcomes of cholecystectomy in the minority population nationwide.
authors: Department of Surgery, University of California, Irvine School of Medicine, Irvine, California, USA.
authors: John V
authors: JV
authors: Gahagan
authors: Mark H
authors: MH
authors: Hanna
authors: Matthew D
authors: MD
authors: Whealon
authors: Steven
authors: S
authors: Maximus
authors: Michael J
authors: MJ
authors: Phelan
authors: Michael
authors: M
authors: Lekawa
authors: Cristobal
authors: C
authors: Barrios
authors: Nicole P
authors: NP
authors: Bernal
mesh_terms: D000328:Adult; D000368:Aged; D044383:Black People / Q000706:statistics & numerical data; D002763:Cholecystectomy / Q000191:economics* / Q000379:methods / Q000706:statistics & numerical data; D016208:Databases, Factual; D005260:Female; D017048:Health Care Costs; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008484:Medicaid / Q000191:economics*; D008875:Middle Aged; D015999:Multivariate Analysis; D020380:Needs Assessment; D017063:Outcome Assessment, Health Care; D063505:Racism / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D018570:Risk Assessment; D014481:United States; D044465:White People / Q000706:statistics & numerical data; D001741:Black or African American