title: Racial, ethnic, and socioeconomic disparities in estimates of AHRQ patient safety indicators.
abstract: BACKGROUND
  Patient safety events that result from the happenstance of mistakes and errors should not occur systematically across racial, ethnic, or socioeconomic subgroups.
  
  
  OBJECTIVE
  To determine whether racial and ethnic differences in patient safety events disappear when income (a proxy for socioeconomic status) is taken into account.
  
  
  METHODS
  This study analyzes administrative data from community hospitals in 16 states with reliable race/ethnicity measures in the 2000 Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality (AHRQ), using the publicly available AHRQ patient safety indicators (PSIs).
  
  
  RESULTS
  Different indicators show different results for different racial/ethnic subgroups. Many events with higher rates for non-Hispanic blacks (compared with non-Hispanic whites) remain higher when income is taken into account, although such differences for Hispanics or Asian/Pacific Islanders (APIs) tend to disappear. Many events with lower rates for Hispanics and APIs remain lower than whites when income is taken into account, but for blacks, they disappear.
  
  
  CONCLUSIONS
  The higher rates for minorities that reflect the way health care is delivered raise troubling questions about potential racial/ethnic bias and discrimination in the US health care system, problems with cultural sensitivity and effective communication, and access to high-quality health care providers.
  
  
  CONCLUSIONS
  The AHRQ PSIs are a broad screen for potential safety events that point to needed improvement in the quality of care for specific populations.
authors.affiliation: The Medstat Group, Inc., Washington, DC 20008, USA. rosanna.coffey@thomson.com
authors.forename: Rosanna M
authors.initials: RM
authors.lastname: Coffey
authors.forename: Roxanne M
authors.initials: RM
authors.lastname: Andrews
authors.forename: Ernest
authors.initials: E
authors.lastname: Moy
mesh_terms: D000328:Adult; D000465:Algorithms; D000847:Annual Reports as Topic; D015982:Bias; D003466:Cultural Characteristics; D005006:Ethnicity; D005260:Female; D006801:Humans; D007049:Iatrogenic Disease; D007182:Income; D007231:Infant, Newborn; D008297:Male; D019300:Medical Errors; D010361:Patients; D011183:Postoperative Complications; D011247:Pregnancy; D019984:Quality Indicators, Health Care; D011787:Quality of Health Care; D044469:Racial Groups; D012449:Safety; D012959:Socioeconomic Factors; D014481:United States; D016270:United States Agency for Healthcare Research and Quality