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Patients with limited English proficiency have known limitations accessing health care, but differences in hospital outcomes once access is obtained are unknown. We investigate inpatient mortality rates and obstetric trauma for self-reported speakers of English, Spanish, and languages of Asia and the Pacific Islands (API) and compare quality of care by language with patterns by race/ethnicity. Data were from the United States Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, 2009 State Inpatient Databases for California. There were 3,757,218 records. Speaking a non-English principal language and having a non-White race/ethnicity did not place patients at higher risk for inpatient mortality, the exception was significantly higher stroke mortality for Japanese-speaking patients. Patients who spoke API languages or had API race/ethnicity had higher risk for obstetric trauma than English-speaking White patients. Spanish-speaking Hispanic patients had more obstetric trauma than English-speaking Hispanic patients. The influence of language on obstetric trauma and the potential effects of interpretation services on inpatient care are discussed. The broader context of policy implications for collection and reporting of language data is also presented. Results from other countries with and without English as a primary language are needed for the broadest interpretation and generalization of outcomes.

Article-at-a-Glance Background The literature indicates that health information technology (IT) use may lead to some gains in the quality and safety of care in some situations but provides little insight into this variability in the results that has been found. The inconsistent findings point to the need for a conceptual model that will guide research in sorting out the complex relationships between health IT and the quality and safety of care. Methods A conceptual model was developed that describes how specific health IT functions could affect different types of inpatient safety errors and that include contextual factors that influence successful health IT implementation. The model was applied to a readily available patient safety measure and nationwide data (2009 AHA Annual Survey Information Technology Supplement and 2009 Healthcare Cost and Utilization Project State Inpatient Databases). Findings The model was difficult to operationalize because (1) available health IT adoption data did not characterize health IT features and extent of usage, and (2) patient safety measures did not elucidate the process failures leading to safety-related outcomes. The sample patient safety measure—Postoperative Physiologic and Metabolic Derangement Rate—was not significantly related to self-reported health IT capabilities when adjusted for hospital structural characteristics. Conclusion These findings illustrate the critical need for collecting data that are germane to health IT and the possible mechanisms by which health IT may affect inpatient safety. Well-defined and sufficiently granular measures of provider's correct use of health IT functions, the contextual factors surrounding health IT use, and patient safety errors leading to health care–associated conditions are needed to illuminate the impact of health IT on patient safety.

Background Because managed care is increasingly prevalent in health care finance and delivery, it is important to ascertain its effects on health care quality relative to that of fee-for-service plans. Some stakeholders are concerned that basing gatekeeping, provider selection, and utilization management on cost may lower quality of care. To date, research on this topic has been inconclusive, largely because of variation in research methods and covariates. Patient age has been the only consistently evaluated outcome predictor. This study provides a comprehensive assessment of the association between managed care and inpatient mortality for Medicare and privately insured patients. Methods A cross-sectional design was used to examine the association between managed care and inpatient mortality for four common inpatient conditions. Data from the 2009 Healthcare Cost and Utilization Project State Inpatient Databases for 11 states were linked to data from the American Hospital Association Annual Survey Database. Hospital discharges were categorized as managed care or fee for service. A phased approach to multivariate logistic modeling examined the likelihood of inpatient mortality when adjusting for individual patient and hospital characteristics and for county fixed effects. Results Results showed different effects of managed care for Medicare and privately insured patients. Privately insured patients in managed care had an advantage over their fee-for-service counterparts in inpatient mortality for acute myocardial infarction, stroke, pneumonia, and congestive heart failure; no such advantage was found for the Medicare managed care population. To the extent that the study showed a protective effect of privately insured managed care, it was driven by individuals aged 65 years and older, who had consistently better outcomes than their non-managed care counterparts. Conclusions Privately insured patients in managed care plans, especially older adults, had better outcomes than those in fee-for-service plans. Patients in Medicare managed care had outcomes similar to those in Medicare FFS. Additional research is needed to understand the role of patient selection, hospital quality, and differences among county populations in the decreased odds of inpatient mortality among patients in private managed care and to determine why this result does not hold for Medicare.

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.

Prologue: “Knowledge,” observed Samuel Johnson, “is of two kinds. We know a subject ourselves, or we know where we can find information upon it.” By this definition, many key players in health care might have to admit to some ignorance on the subject, particularly those who depend on the disparate data sources that constitute the “system” of health care information. A number of promising efforts are now under way that would standardize data collection and reporting, thereby improving the usefulness of health information. However, Rosanna Coffey and colleagues urge caution: They note that the development of standards is but one step in a much longer journey. The authors should know as well as anyone what challenges He ahead. All were deeply involved in the design and implementation of the Healthcare Cost and Utilization Project, a national database developed by the Agency for Health Care Policy and Research (AHCPR) that assembles information on hospital inpatient services from state governments and private...

Despite improvements in health care, disparities in care still exist and are widening for some health measures. This study examined postsurgical outcomes for patients from low-income areas as compared to outcomes for those from high-income areas in the United States from 2000 to 2009. We found that postsurgical outcomes improved in general, with significant decreases in nine of twelve mortality and patient safety measures and an increase in one measure. Patients from low-income areas had worse surgical outcomes than those from high-income areas for nine of twelve measures in both 2000 and 2009. The disparities in outcomes between low- and high-income groups did not change significantly for nine of the twelve measures. For the three measures that did change significantly, in only two of the cases was the change favorable for patients from low-income areas. These findings have implications for efforts to improve surgical outcomes and health policy and indicate the need for research on the cause of continued disparities in postsurgical outcomes.

Readmission for congestive heart failure (CHF) is the most common reason for readmission among Medicare fee-for-service patients. Yet CHF readmissions are not just a Medicare problem. This study examined who is likely to be readmitted for CHF, using all-payer hospital discharges from 14 of the states participating in the Healthcare Cost and Utilization Project. Patients with the strongest positive association with readmission were discharged against medical advice, covered by Medicaid, and had more severe loss of function and certain comorbidities such as drug abuse, renal failure, or psychoses. Weak negative relationship between readmission and cost of index admission provides some evidence that hospitals with higher readmission rates do not systematically use fewer resources in treating patients in initial encounters. High readmission rate for Medicaid patients suggests that state and federal governments should target Medicaid populations and drug abuse treatment for better care coordination to reduce readmissions and health care costs.

Objective The aim of this study was to describe selected trends in hospital inpatient care for children between 2000 and 2007. Study Design Analysis was conducted of administrative data from annual nationwide databases of hospital discharges from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project, along with survey data from a nationally representative random sample of children from the Medical Expenditure Panel Survey. Hospital utilization rates and expenses, risk-adjusted rates of potentially avoidable hospitalization, and safety indicators in the hospital are calculated and tracked with established and downloadable software. Results The rate of hospital discharges for children aged 15 to 17 years declined significantly, mainly due to fewer maternity-related discharges. The leading principal conditions by age group were similar to the report for 1995 to 2000; however, the rate of admissions for skin infections doubled to 9 per 10 000. Hospital cost per discharge increased by an annual average of 4.5% per year compared with 2.6% annual growth in the gross domestic product deflator. Medicaid is increasingly important relative to private insurance as a payer for hospital care for children. The rate of potentially preventable hospitalizations for both acute and chronic conditions declined substantially (18%, adjusted for age and gender). Several measures of patient safety improved—the rates of postoperative sepsis, iatrogenic pneumothorax, and selected infections due to medical care declined by 14.2%, 17.8%, and 23.5%, respectively. However, the rate of accidental punctures and lacerations and the rate of decubitus ulcer increased by 25.6% and 34.5%, respectively. The trends in safety indicators varied somewhat by age group, income quartile of zip codes, insurance, region, and type of location without a consistent pattern. Conclusions/Implications Although teenage pregnancy rates were declining, there was a worsening trend in skin infections. The latter may eventually be impacted by recent publication of new guidelines for treatment by office-based physicians. A gradually increasing role of Medicaid as a payer for hospital care for children will likely put an increasing strain on public resources in advance of the full implementation of the health insurance reforms recently enacted. The decline in potentially avoidable admissions reduces the use of the most expensive resources. For asthma and diabetes, children in the lowest income zip codes had persistently higher rates of admission, but the rate fell by one third during the period. Children in the South and West regions had substantial and significant declines in preventable admissions. Particular indicators of safety were improving, whereas others were worsening. Trends were not the same in all types of hospitals, all regions, and income categories. This is already a rich area for further research on the impact of quality improvement strategies; however, attention is needed to developing more tools to more thoroughly track quality of care for children.

Study objective Emergency departments (EDs) are an integral part of the US health care system, and yet national data sources on the care received in the ED are poorly understood, thereby limiting their usefulness for analyses. We provide a comparison of data sources that can be used to examine utilization and quality of care in the ED nationally. Data sources and comparisons This article compares 7 data sources available in 2005 for conducting analyses of ED encounters: the American Hospital Association Annual Survey Database ™ , Hospital Market Profiling Solution©, National Emergency Department Inventory, Nationwide Emergency Department Sample, National Hospital Ambulatory Medical Care Survey, National Electronic Injury Surveillance System–All-Injury Program, and the National Health Interview Survey. In addition to describing the type and scope of data collection, available characteristics, and sponsor of the ED data sources, we compare (where possible) estimates of the total number of EDs, national and regional volume of ED visits, national and regional admission rates (percentage of ED visits resulting in hospital admission), patient characteristics, hospital characteristics, and reasons for visit generated by the various data sources. Major findings The different data sources yielded estimates of the number of EDs that ranged from 4,609 to 4,884 and the number of ED encounters from more than 109 million to more than 116 million. Admission rates across data sources varied from 12.0% to 15.3%. Although comparisons of the 7 data sources were somewhat limited by differences in available information and operational definitions, variation in estimates of utilization and patterns of care existed by region, expected payer, and patient and hospital characteristics. The rankings and estimates of the top 5 first-listed conditions seen in the ED are relatively consistent between the 2 data sources with diagnoses, although the Nationwide Emergency Department Sample estimates 1.3 to 5.8 times more ED visits for each chronic and acute all-listed condition examined relative to the National Hospital Ambulatory Medical Care Survey. Conclusion Each of the data sources described in this article has unique advantages and disadvantages when used to examine patterns of ED care, making the different data sources appropriate for different applications. Analysts should select a data source according to its construction and should bear in mind its strengths and weaknesses in drawing conclusions based on the estimates it yields.

The aim of this study was to identify and quantify gaps in health care data for American Indians and Alaska Natives. Findings indicate that only 42% of measures of health care quality and access tracked in the National Healthcare Disparities Report could be used to assess disparities among American Indians and Alaska Natives. Patient safety data was especially limited. Data from American Indians and Alaska Natives need to be improved to allow better targeting of interventions to reduce health care disparities and monitoring the success of these activities. Language: en

Objectives. Considerable differences in prevalence of diabetes and management of the disease exist among racial/ethnic groups. We examined the relationship between race/ethnicity and hospital readmissions for diabetes-related conditions. Methods. Nonmaternal adult patients with Medicare, Medicaid, or private insurance coverage hospitalized for diabetes-related conditions in 5 states were identified from the 1999 State Inpatient Databases of the Healthcare Cost and Utilization Project. Racial/ethnic differences in the likelihood of readmission were estimated by logistic regression with adjustment for patient demographic, clinical, and socioeconomic characteristics and hospital attributes. Results. The risk-adjusted likelihood of 180-day readmission was significantly lower for non-Hispanic Whites than for Hispanics across all 3 payers or for non-Hispanic Blacks among Medicare enrollees. Within each payer, Hispanics from low-income communities had the highest risk of readmission. Among Medicare beneficiaries, Blacks and Hispanics had higher percentages of readmission for acute complications and microvascular disease, while Whites had higher percentages of readmission for macrovascular conditions. Conclusions. Racial/ethnic disparities are more evident in 180-day than in 30-day readmission rates, and greatest among the Medicare population. Readmission diagnoses vary by race/ethnicity, with Blacks and Hispanics at higher risk for those complications more likely preventable with effective postdischarge care.

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.

Objective To provide an overview of inpatient operating room (OR) procedures in the United States. Design, Setting, and Patients Healthcare Cost and Utilization Project 2007 Nationwide Inpatient Sample discharge data from a sample of US short-term, acute-care, nonfederal hospitals. Main Outcome Measures National volume of OR procedures overall and by type of procedure, resource use and costs, most frequent and expensive procedures, and trends. Results Fifteen million OR procedures were performed in 2007 (495 procedures/10 000 population). Only 26.4% of hospitalizations involved an OR procedure; however, OR-related stays were responsible for 46.8% of hospital costs ($161 billion). Patients aged 65 years and older were 2 to 3 times more likely to experience OR procedures (eg, 1327 procedures/10 000 persons among those aged 65-84 years vs 626 procedures/10 000 persons for those aged 45-64 years). Compared with non-OR inpatients, OR patients were less severely ill (20.5% had the highest severity of illness vs 24.6% for non-OR patients) and used more resources ($2900/day for OR patients vs $1400/day for non-OR patients). The 15 most expensive procedures accounted for half of all procedure-related hospitalization costs and one-fourth of total hospital costs. Volumes for 4 of the most expensive procedures increased between 1997 and 2007: 20% for percutaneous transluminal coronary angioplasty, 46% for cesarean delivery, 46% for knee replacement, and 45% for spinal fusion. The volume of percutaneous transluminal coronary angioplasty declined 20% from 2006 to 2007, compared with a 56% increase in the prior decade. Conclusions Procedures in the OR represent a large portion of hospital costs, and these costs are concentrated in few procedure types.

Background 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. Objectives 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. Findings : 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. Conclusions 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 Rural/urban variations in admissions for heart failure may be influenced by severity at hospital presentation and local practice patterns. Laboratory data reflect clinical severity and guide hospital admission decisions and treatment for heart failure, a costly chronic illness and a leading cause of hospitalization among the elderly. Our main objective was to examine the role of laboratory test results in measuring disease severity at the time of admission for inpatients who reside in rural and urban areas. Methods We retrospectively analyzed discharge data on 13,998 hospital discharges for heart failure from three states, Hawai’i, Minnesota, and Virginia. Hospital discharge records from 2008 to 2012 were derived from the State Inpatient Databases of the Healthcare Cost and Utilization Project, and were merged with results of laboratory tests performed on the admission day or up to two days before admission. Regression models evaluated the relationship between clinical severity at admission and patient urban/rural residence. Models were estimated with and without use of laboratory data. Results Patients residing in rural areas were more likely to have missing laboratory data on admission and less likely to have abnormal or severely abnormal tests. Rural patients were also less likely to be admitted with high levels of severity as measured by the All Patient Refined Diagnosis Related Groups (APR-DRG) severity subclass, derivable from discharge data. Adding laboratory data to discharge data improved model fit. Also, in models without laboratory data, the association between urban compared to rural residence and APR-DRG severity subclass was significant for major and extreme levels of severity (OR 1.22, 95 % CI 1.03–1.43 and 1.55, 95 % CI 1.26–1.92, respectively). After adding laboratory data, this association became non-significant for major severity and was attenuated for extreme severity (OR 1.12, 95 % CI 0.94–1.32 and 1.43, 95 % CI 1.15–1.78, respectively). Conclusion Heart failure patients from rural areas are hospitalized at lower severity levels than their urban counterparts. Laboratory test data provide insight on clinical severity and practice patterns beyond what is available in administrative discharge data.