title: Neighborhoods matter: use of hospitals with worse outcomes following total knee replacement by patients from vulnerable populations.
abstract: BACKGROUND
  Neighborhood sociodemographic characteristics are associated with health care utilization across many conditions. There has been little study of whether total knee replacement (TKR) recipients from vulnerable populations, including racial and ethnic minorities, the poor, the elderly, and the less well educated, are more likely to use low-volume hospitals (LVHs).
  
  
  METHODS
  We used Medicare claims and census data to identify a national cohort of Medicare beneficiaries who had elective TKR. We defined an LVH as a center performing fewer than 26 TKRs per year, and we used geocoding to identify "bypassers" (patients who had a high-volume hospital closer to their residence than the one where they had TKR). We used multivariate logistic regression to examine the association of patient and neighborhood characteristics with utilization of LVHs and bypassing. We derived a summative measure of neighborhood vulnerability that included 4 high-risk characteristics (factors were high proportions of residents who are minority individuals, who have foreign-born status, with low income, and with low education).
  
  
  RESULTS
  Of 113 015 TKR recipients, 13 120 (11.6%) used LVHs. Of all the TKR recipients, 9815 (8.7%) bypassed a center with a higher TKR volume than the one they used. Multivariate analyses showed that nonwhite (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.16-1.33), poor (OR, 1.94; 95% CI, 1.83-2.08), and nonurban (OR, 1.94; 95% CI, 1.87-2.01) subjects were more likely to use LVHs. The TKR recipients from neighborhoods with 3 or 4 vulnerability factors were more likely than patients in neighborhoods with no vulnerability factors to use an LVH and bypass a high-volume hospital.
  
  
  CONCLUSIONS
  Efforts to inform patients about the association of volume with TKR outcomes should target rural areas and vulnerable populations in urban settings.
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA. lenal@bu.edu
authors.forename: Elena
authors.initials: E
authors.lastname: Losina
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Wright
authors.forename: Courtenay L
authors.initials: CL
authors.lastname: Kessler
authors.forename: Jane A
authors.initials: JA
authors.lastname: Barrett
authors.forename: Anne H
authors.initials: AH
authors.lastname: Fossel
authors.forename: Alisha H
authors.initials: AH
authors.lastname: Creel
authors.forename: Nizar N
authors.initials: NN
authors.lastname: Mahomed
authors.forename: John A
authors.initials: JA
authors.lastname: Baron
authors.forename: Jeffrey N
authors.initials: JN
authors.lastname: Katz
mesh_terms: D000368:Aged; D019645:Arthroplasty, Replacement, Knee / Q000706:statistics & numerical data*; D002755:Choice Behavior; D015331:Cohort Studies; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D006278:Medicare / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D012111:Residence Characteristics; D012959:Socioeconomic Factors; D014505:Urban Population; D035862:Vulnerable Populations / Q000706:statistics & numerical data*