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Objective To examine the role of patient, hospital, and community characteristics on racial and ethnic disparities in in-hospital postsurgical complications. Data Sources Healthcare Cost and Utilization Project, 2011 State Inpatient Databases; American Hospital Association Annual Survey of Hospitals; Area Health Resources Files; Centers for Medicare & Medicaid Services Hospital Compare database. Methods Nonlinear hierarchical modeling was conducted to examine the odds of patients experiencing any in-hospital postsurgical complication, as defined by Agency for Healthcare Research and Quality Patient Safety Indicators. Principal Findings A total of 5,474,067 inpatient surgical discharges were assessed using multivariable logistic regression. Clinical risk, payer coverage, and community-level characteristics (especially income) completely attenuated the effect of race on the odds of postsurgical complications. Patients without private insurance were 30 to 50 percent more likely to have a complication; patients from low-income communities were nearly 12 percent more likely to experience a complication. Private, not-for-profit hospitals in small metropolitan or micropolitan areas and higher nurse-to-patient ratios led to fewer postsurgical complications. Conclusions Race does not appear to be an important determinant of in-hospital postsurgical complications, but insurance and community characteristics have an effect. A population-based approach that includes improving the socioeconomic context may help reduce disparities in these outcomes.

Objectives To provide an overview of statewide hospital discharge databases (HDD), including their uses in health services research and limitations, and to describe Agency for Healthcare Research and Quality (AHRQ) Enhanced State Data grants to address clinical and race–ethnicity data limitations. Principal Findings Almost all states have statewide HDD collected by public or private data organizations. Statewide HDD, based on the hospital claim with state variations, contain useful core variables and require minimal collection burden. AHRQ's Healthcare Cost and Utilization Project builds uniform state and national research files using statewide HDD. States, hospitals, and researchers use statewide HDD for many purposes. Illustrating researchers' use, during 2012–2014, HSR published 26 HDD-based articles on health policy, access, quality, clinical aspects of care, race–ethnicity and insurance impacts, economics, financing, and research methods. HDD have limitations affecting their use. Five AHRQ grants focused on enhancing clinical data and three grants aimed at improving race–ethnicity data. Conclusion ICD-10 implementation will significantly affect the HDD. The AHRQ grants, information technology advances, payment policy changes, and the need for outpatient information may stimulate other statewide HDD changes. To remain a mainstay of health services research, statewide HDD need to keep pace with changing user needs while minimizing collection burdens.

Efforts to quantify, monitor, understand, and reduce disparities in health care are critically dependent on the collection of high-quality data that support such analyses. In producing the first National Healthcare Disparities Report (NHDR), a number of gaps in data were encountered that limited the ability to assess racial, ethnic, and socioeconomic disparities in health care.The objectives of this study were to identify and quantify gaps in data related to disparities in health care and discuss efforts to fill these gaps in future NHDRs.: Data on specific racial, ethnic, and socioeconomic groups were often not collected or collected in formats that differed from federal standards. When collected, data were often insufficient to generate reliable estimates for specific racial, ethnic, and socioeconomic groups. These effects were magnified when attempting to assess disparities within many of the agency's priority populations such as women, children, the elderly, low-income populations, and rural residents. Future NHDRs begin to fill some of these gaps in data, but some gaps will likely persist and new gaps will likely arise as the availability of data for specific populations vary from year to year.Gaps in data limit the ability to address racial, ethnic, and socioeconomic disparities in health care. Although many federal efforts are underway to improve data collection, some groups and populations pose unique challenges for data collection that will be difficult to overcome.

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. Research Design: 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. Discussion: 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.

OBJECTIVE—To describe the extent to which hospitalizations for patients with diabetes reflect multiple stays by the same individuals and to examine how multiple hospitalizations vary by patient demographic and socioeconomic characteristics. RESEARCH DESIGN AND METHODS—Using the Healthcare Cost and Utilization Project complete discharge data for five states (California, Missouri, New York, Tennessee, and Virginia) in 1999, we identified 648,748 nonneonatal, nonmaternal patients who had one or more hospitalizations listing diabetes. Multiple hospitalizations were measured as percent of patients with multiple stays, percent of total stays represented by multiple stays, and average number of stays per patient. Total hospital costs were also examined. Stratified analysis and regression were performed to assess differences by age, sex, race/ethnicity, payer, location, and income. RESULTS—Among patients with diabetes who had been hospitalized, 30% had two or more stays accounting for >50% of total hospitalizations and hospital costs. Controlled for patient age, sex, and clinical characteristics, the likelihood of having multiple hospitalizations was higher for Hispanics and non-Hispanic blacks compared with non-Hispanic whites, as well as for patients covered by Medicare or Medicaid and those living in low-income areas. The prevalence of diabetes complications and multiple conditions differed by age, race/ethnicity, and payer among patients with multiple stays. CONCLUSIONS—Multiple hospitalizations are common among patients with diabetes but vary by age, race/ethnicity, payer, and income, with those populations traditionally considered to be more vulnerable experiencing higher likelihoods of multiple stays. Significant opportunities exist to reduce the proportion of multiple hospitalizations for patients with diabetes. Clinical and policy interventions to improve the quality of care and outcomes for these patients should be designed accordingly and have the potential to pay major dividends.