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Previous research suggests that relatively few hospitalized patients with opioid-related conditions receive substance use treatment during their inpatient stay. Without treatment, these individuals may be more likely to have subsequent hospitalizations for continued opioid use disorder.To evaluate the relationship between receipt of inpatient drug detoxification and/or rehabilitation services and subsequent opioid-related readmission.This study used combined hospital inpatient discharge and emergency department visit data from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. Our sample consisted of 329,037 patients from seven states with an opioid-related index hospitalization occurring between March 2010 and September 2013. Multivariate analysis was conducted to examine the relationship between opioid-related readmission and the receipt of inpatient drug detoxification and/or rehabilitation during the index visit.A relatively small percentage (19.4%) of patients with identified opioid-related conditions received treatment for drug use during their hospital inpatient stay. Patients who received drug rehabilitation, but not drug detoxification, during an opioid-related index hospitalization had lower odds of an opioid-related readmission within 90 days of discharge (odds ratio = 0.60, 95% confidence interval = 0.54-0.67) compared with patients with no inpatient drug detoxification or rehabilitation. Conclusions/Importance: A low percentage of patients receive inpatient services for drug use during an index stay involving an opioid-related diagnosis. Our findings indicate that receipt of drug rehabilitation services in acute care hospitals is associated with a lower 90-day readmission rate. Further research is needed to understand factors associated with the receipt of inpatient services and readmissions.

Objective In 2006, the American College of Surgeons’ Committee on Trauma and the Center for Disease Control released field triage guidelines with special consideration for older adults. Additional considerations for direct transport to a Level I or II trauma center (TC) were added in 2011, reflecting perceived undertriage to TCs for older adults. We examined whether age-based disparities in TC care for severe head injury decreased following introduction of the 2011 revisions. Methods A pre-post design analyzing the 2009 and 2012 Healthcare Cost and Utilization Project State Emergency Department Databases (SEDD) and State Inpatient Databases (SID) with multivariable logistic regressions considered changes in (1) the trauma designation of the emergency department where treatment was initiated and (2) transfer to a TC following initial treatment at a non-TC. Results Compared with adults aged 18–44 years, after multivariable adjustment, in both years TC care was less likely for adults aged 45–64 years (OR: 0.76 in 2009 and 0.74 in 2012), aged 65–84 years (OR: 0.61 and 0.59), and aged 85+ years (OR: 0.53 and 0.56). Between 2009 and 2012, the likelihood of TC care increased for all age groups, with the largest increase among those aged 85+ years (OR = 1.18), which was statistically different (p = .02) from the increase among adults aged 18–44 years (OR = 1.12). The analysis of transfers yielded similar results. Conclusions Although patterns of increased TC treatment for all groups with severe head trauma indicate improvements, age-based disparities persisted. This article is protected by copyright. All rights reserved.

Background: Readmission rates following total hip arthroplasty (THA) and total knee arthroplasty (TKA) are increasingly used to measure hospital performance. Readmission rates that are not adjusted for race/ethnicity and socioeconomic status, patient risk factors beyond a hospital’s control, may not accurately reflect a hospital’s performance. In this study, we examined the extent to which risk-adjusting for race/ethnicity and socioeconomic status affected hospital performance in terms of readmission rates following THA and TKA. Methods: We calculated 2 sets of risk-adjusted readmission rates by (1) using the Centers for Medicare & Medicaid Services standard risk-adjustment algorithm that incorporates patient age, sex, comorbidities, and hospital effects and (2) adding race/ethnicity and socioeconomic status to the model. Using data from the Healthcare Cost and Utilization Project, 2011 State Inpatient Databases, we compared the relative performances of 1,194 hospitals across the 2 methods. Results: Addition of race/ethnicity and socioeconomic status to the risk-adjustment algorithm resulted in (1) little or no change in the risk-adjusted readmission rates at nearly all hospitals; (2) no change in the designation of the readmission rate as better, worse, or not different from the population mean at >99% of the hospitals; and (3) no change in the excess readmission ratio at >97% of the hospitals. Conclusions: Inclusion of race/ethnicity and socioeconomic status in the risk-adjustment algorithm led to a relative-performance change in readmission rates following THA and TKA at

EXECUTIVE SUMMARY There has been ongoing concern regarding the viability of safety-net hospitals (SNHs), which care for vulnerable populations. The authors examined payer mix at SNHs and non-SNHs during a period covering the Great Recession using data from the 2006 to 2012 Healthcare Cost and Utilization Project State Inpatient Databases from 38 states. The number of privately insured stays decreased at both SNHs and non-SNHs. Non-SNHs increasingly served Medicaid-enrolled and uninsured patients; in SNHs, the number of Medicaid stays decreased and uninsured stays remained stable. These study findings suggest that SNHs were losing Medicaid-enrolled patients relative to non-SNHs before the Medicaid expansion under the Affordable Care Act (ACA). Postexpansion, Medicaid stays will likely increase for both SNHs and non-SNHs, but the increase at SNHs may not be as large as expected if competition increases. Because hospital stays with private insurance and Medicaid help SNHs offset uncompensated care, a lower-than-expected increase could affect SNHs' ability to care for the remaining uninsured population. Continued monitoring is needed once post-ACA data become available.

As sepsis hospitalizations have increased, in-hospital sepsis deaths have declined. However, reported rates may remain higher among racial/ethnic minorities. Most previous studies have adjusted primarily for age and sex. The effect of other patient and hospital characteristics on disparities in sepsis mortality is not yet well-known. Furthermore, coding practices in claims data may influence findings. The objective of this study was to use a broad method of capturing sepsis cases to estimate 2004-2013 trends in risk-adjusted in-hospital sepsis mortality rates by race/ethnicity to inform efforts to reduce disparities in sepsis deaths.Retrospective, repeated cross-sectional study.Acute care hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases for 18 states with consistent race/ethnicity reporting.Patients diagnosed with septicemia, sepsis, organ dysfunction plus infection, severe sepsis, or septic shock.In-hospital sepsis mortality rates adjusted for patient and hospital factors by race/ethnicity were calculated. From 2004 to 2013, sepsis hospitalizations for all racial/ethnic groups increased, and mortality rates decreased by 5-7% annually. Mortality rates adjusted for patient characteristics were higher for all minority groups than for white patients. After adjusting for hospital characteristics, sepsis mortality rates in 2013 were similar for white (92.0 per 1,000 sepsis hospitalizations), black (94.0), and Hispanic (93.5) patients but remained elevated for Asian/Pacific Islander (106.4) and "other" (104.7; p0.001) racial/ethnic patients.Our results indicate that hospital characteristics contribute to higher rates of sepsis mortality for blacks and Hispanics. These findings underscore the importance of ensuring that improved sepsis identification and management is implemented across all hospitals, especially those serving diverse populations.

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.

Goals were to describe funding for specialty behavioral health providers in 1986 and 2005 and examine how the recession, parity law, and Affordable Care Act (ACA) may affect future funding.Numerous public data sets and actuarial methods were used to estimate spending for services from specialty behavioral health providers (general hospital specialty units; specialty hospitals; psychiatrists; other behavioral health professionals; and specialty mental health and substance abuse treatment centers).Between 1986 and 2005, hospitals-which had received the largest share of behavioral health spending-declined in importance, and spending shares trended away from specialty hospitals that were largely funded by state and local governments. Hospitals' share of funding from private insurance decreased from 25% in 1986 to 12% in 2005, and the Medicaid share increased from 11% to 23%. Office-based specialty providers continued to be largely dependent on private insurance and out-of-pocket payments, with psychiatrists receiving increased Medicaid funding. Specialty centers received increased funding shares from Medicaid (from 11% to 29%), and shares from other state and local government sources fell (from 64% to 46%).With ACA's full implementation, spending on behavioral health will likely increase under private insurance and Medicaid. Parity in private plans will also push a larger share of payments for office-based professionals from out-of-pocket payments to private insurance. As ACA provides insurance for formerly uninsured individuals, funding by state behavioral health authorities of center-based treatment will likely refocus on recovery and support services. Federal Medicaid rules will increase in importance as more people needing behavioral health treatment become covered.

The 2007-09 recession had a dramatic effect on behavioral health spending, with the effect most prominent for private, state, and local payers. During the recession behavioral health spending increased at a 4.6 percent average annual rate, down from 6.1 percent in 2004-07. Average annual growth in private behavioral health spending during the recession slowed to 2.7 percent from 7.2 percent in 2004-07. State and local behavioral health spending showed negative average annual growth, -1.2 percent, during the recession, compared with 3.7 percent increases in 2004-07. In contrast, federal behavioral health spending growth accelerated to 11.1 percent during the recession, up from 7.2 percent in 2004-07. These behavioral health spending trends were driven largely by increased federal spending in Medicaid, declining private insurance enrollment, and severe state budget constraints. An increased federal Medicaid match reduced the state share of Medicaid spending, which prevented more drastic cuts in state-funded behavioral health programs during the recession. Federal Medicaid served as a critical safety net for people with behavioral health treatment needs during the recession.

Research suggests that individuals with Medicaid or no insurance receive fewer evidence-based treatments and have worse outcomes than those with private insurance for a broad range of conditions. These differences may be due to patients' receiving care in hospitals of different quality.We used the Healthcare Cost and Utilization Project State Inpatient Databases 2009-2010 data to identify patients aged 18-64 years with private insurance, Medicaid, or no insurance who were hospitalized with acute myocardial infarction, heart failure, pneumonia, stroke, or gastrointestinal hemorrhage. Multinomial logit regressions estimated the probability of admissions to hospitals classified as high, medium, or low quality on the basis of risk-adjusted, in-hospital mortality.Compared with patients who have private insurance, those with Medicaid or no insurance were more likely to be minorities and to reside in areas with low-socioeconomic status. The probability of admission to high-quality hospitals was similar for patients with Medicaid (23.3%) and private insurance (23.0%) but was significantly lower for patients without insurance (19.8%, P0.01) compared with the other 2 insurance groups. Accounting for demographic, socioeconomic, and clinical characteristics did not influence the results.Previously noted disparities in hospital quality of care for Medicaid recipients are not explained by differences in the quality of hospitals they use. Patients without insurance have lower use of high-quality hospitals, a finding that needs exploration with data after 2013 in light of the Affordable Care Act, which is designed to improve access to medical care for patients without insurance.

Background: Linkage of US state hospital discharge records to state death certificate records offers the possibility of tracking long-term mortality outcomes across large, diverse patient populations, which may be useful for comparative effective analyses. Aim: To demonstrate the value of linking state community hospital discharge data to vital statistics death files for research by conducting a comparative effectiveness analysis. Methods: Linked Patient Discharge Data and Vital Statistics Death Files from the California Office of Statewide Health Planning and Development were used to compare survival rates for patients with an elective repair for abdominal aortic aneurysm who received open aneurysm repair (OAR) versus endovascular aneurysm repair (EVAR). The sample consisted of 13,652 hospitalized patients who underwent an OAR or EVAR for abdominal aortic aneurysm between 1 July 2000 and 31 January 2006. Patients were matched using propensity scores (8966 patients in the matched sample). In-hospital, 30-day, 1-year and 5-year mortality rates were compared between the OAR and EVAR populations, before and after propensity score matching. Results: We found a few data anomalies (92 out of 13,652), primarily in patients’ sex and date of death. The analysis revealed that in the matched cohort, in-hospital and 30-day postdischarge mortality rates were significantly lower following EVAR than OAR; however, consistent with previous clinical trials, differences in the 1- and 5-year rates were not statistically significant. Conclusion: The study demonstrates that linked US state discharge and mortality data can be a valuable resource for comparative effectiveness analyses. In particular, this approach may be useful when generally available data sets such as Medicare claims data limit the generalizability of findings. Policy-makers and others should consider greater investments in these data.

The United States invests a sizable amount of money on treatments for mental health and substance abuse: $135 billion in 2005, or 1.07 percent of the gross domestic product. We provide treatment spending estimates from the period 1986-2005 to build understanding of past trends and consider future possibilities. We find that the growth rate in spending on mental health medications-a major driver of mental health expenditures in prior years-declined dramatically. As a result, mental health and substance abuse spending grew at a slightly slower rate than gross domestic product in 2004 and 2005, and it continued to shrink as a share of all health spending. Of note, we also find that Medicaid's share of total spending on mental health grew from 17 percent in 1986 to 27 percent in 2002 to 28 percent in 2005. The recent recession, the full implementation of federal parity law, and such health reform-related actions as the planned expansion of Medicaid all have the potential to improve access to mental health and substance abuse treatment and to alter spending patterns further. Our spending estimates provide an important context for evaluating the effect of those policies.

Objective: This study sought to describe the extent to which community hospitals, in a sample of states, are caring for patients with psychiatric disorders in medical-surgical beds (scatter beds) and to compare the characteristics of patients treated in scatter beds with those of patients treated in psychiatric units in community hospitals. Methods: Information on hospital discharges in 12 states for patients with a principal psychiatric diagnosis was gathered from the Healthcare Cost and Utilization Project State Inpatient Databases. Discharges of patients who were treated in community hospital psychiatric units (N=370,984) were compared with those of patients who were treated in scatter beds (N=26,969). Results: Overall, only 6.8% of discharges were from scatter beds. The rate of total psychiatric discharges per 10,000 total state population ranged from a high of 62.3 in one study state to a low of 9.6 in another. The average rate of scatter bed discharges per 10,000 state population ranged from 1.6 to 5.8, whereas the average rate of psychiatric unit discharges ranged from 7.4 to 58.9. A comparison of discharges of patients treated in scatter beds with discharges of patients treated in psychiatric units indicated that patients in scatter beds were more likely to have somatic conditions and were half as likely to have an accompanying substance use disorder. Discharge codes indicated that almost 40% of patients from scatter beds had a diagnosis of schizophrenia, episodic mood disorder, or depression; about two-thirds were admitted from emergency rooms; and about one-fifth were transferred to another facility. Conclusions: More research is needed to determine the optimal supply of psychiatric unit beds across regions and whether and how scatter beds should be used to address the lack of psychiatric beds. (Psychiatric Services 61:562–568, 2010)

State efforts to improve mental health and substance abuse service systems cannot overlook the fragmented data systems that reinforce the historical separateness of systems of care. These separate systems have discrete approaches to treatment, and there are distinct funding streams for state mental health, substance abuse, and Medicaid agencies. Transforming mental health and substance abuse services in the United States depends on resolving issues that underlie separate treatment systems--access barriers, uneven quality, disjointed coordination, and information silos across agencies and providers. This article discusses one aspect of transformation--the need for interoperable information systems. It describes current federal and state initiatives for improving data interoperability and the special issue of confidentiality associated with mental health and substance abuse treatment data. Some achievable steps for states to consider in reforming their behavioral health data systems are outlined. The steps include collecting encounter-level data; using coding that is compliant with the Health Insurance Portability and Accountability Act, including national provider identifiers; forging linkages with other state data systems and developing unique client identifiers among systems; investing in flexible and adaptable data systems and business processes; and finding innovative solutions to the difficult confidentiality restrictions on use of behavioral health data. Changing data systems will not in itself transform the delivery of care; however, it will enable agencies to exchange information about shared clients, to understand coordination problems better, and to track successes and failures of policy decisions.

We reviewed 39 national government- and nongovernment-sponsored data sets related to substance addiction policy. These data sets describe patients with substance use disorders (SUDs), treatment providers and the services they offer, and/or expenditures on treatment. Findings indicate the availability of reliable data on the prevalence of SUD and the characteristics of specialty treatment facilities, but meager data on financing and services. Gaps in information might be filled through agency collaboration to redesign, coordinate, and augment existing substance abuse and general health surveys. Despite noted gaps, these data sets represent an unusually rich set of resources for health services and policy research.

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.

Few systematic studies have examined the characteristics of substance abuse treatment programs serving adolescents. An expert panel recently identified nine key elements of effective adolescent substance abuse treatment. We measured the percentage of treatment programs in the United States with at least 10 adolescent clients on a given day that reported these elements using data from the 2003 National Survey of Substance Abuse Treatment Services. This first look into the characteristics of facilities serving significant numbers of adolescents indicates that many facilities may be lacking in components considered important. The most significant measured potential areas for improvement occurred in the areas of including mental health as well as medical issues in comprehensive assessments and developing curricula to meet the developmental and cultural needs of clients. On a more encouraging note, many facilities were conducting discharge planning and providing aftercare, although the specifics of these services were not determined.

Trends in MH/SA treatment spending from 1992 to 1999 were examined using employer claims data from approximately 1.7 million covered lives in each year. The analysis finds that employer-based private insurance spending on MH/SA treatment did not keep pace with total employer-based private insurance spending or general price inflation. MH/SA spending dropped from 7.2 percent of total private insurance spending in 1992 to 5.1 percent in 1999. The decline was attributable to a dramatic decrease in inpatient MH/SA treatment--specifically, the probability of admissions and average length-of-stay.

The paper examines trends in the use of inpatient substance abuse detoxification provided at general hospitals using data from the Healthcare Utilization and Cost Project - National Inpatient Survey. Most persons who received inpatient detoxification did not also receive rehabilitation while an inpatient. The percentage receiving rehabilitation declined between 1992 and 1997 from 38.9% to 21.1%. The decrease in the probability of receiving rehabilitation occurred across gender, age, region, insurance status, income levels, diagnoses, admission source, and discharge destination. Two other notable trends are that average length of stay for detoxification dropped by one third over the six-year period, from 7.7 days to 5.2 days and the percentage of admissions through the emergency room increased from 35.6% to 40.1%. Detoxification offers an opportunity to link patients with rehabilitation. This analysis indicates that those opportunities may be missed.

Study objective Duration of a stay in an emergency department (ED) is considered a measure of quality, but current measures average lengths of stay across all conditions. Previous research on ED length of stay has been limited to a single condition or a few hospitals. We use a census of one state's data to measure length of ED stays by patients' conditions and dispositions and explore differences between means and medians as quality metrics. Methods The data source was the Healthcare Cost and Utilization Project 2011 State Emergency Department Databases and State Inpatient Databases for Florida. Florida is unique in collecting ED length of stay for both released and admitted patients. Clinical Classifications Software was used to group visits based on first-listed International Classification of Disease, Ninth Edition, Clinical Modification , diagnoses. Results For the 10 most common diagnoses, patients with relatively minor injuries typically required the shortest mean stay (3 hours or less); conditions resulting in admission or transfer tended to be more serious, resulting in longer stays. Patients requiring the longest stays, by disposition, had discharge diagnoses of nonspecific chest pain (mean 7.4 hours among discharged patients), urinary tract infections (4.8 hours among admissions), and schizophrenia (9.6 hours among transfers) among the top 10 diagnoses. Conclusion Emergency department length of stay as a measure of ED quality should take into account the considerable variation by condition and disposition of the patient. Emergency department length of stay measurement could be improved in the United States by standardizing its definition; distinguishing visits involving treatment, observation, and boarding; and incorporating more distributional information.

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...

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 This study determined spending on mental health treatment in the United States over time by provider and payer relative to all health spending. Methods Estimates were developed to be consistent with the National Health Expenditure Accounts. Numerous public data sources were used. Results Mental health treatment expenditures grew from $33 billion in 1986 to $100 billion in 2003. In real 2003 dollars, spending per capita on mental health treatment rose from $205 to $345. The average annual nominal total mental health growth rate was 6.7%. In comparison, total health care expenditures increased by 8.0%. As a result of the slower growth rate of mental health expenditures compared with all health spending, mental health fell from 8% of all health expenditures in 1986 to 6% in 2003. Total national health spending increased by approximately $1.175 trillion from 1986 to 2003; of this, 6% is attributed to an increase in mental health spending. The mix of services has changed, with more care being provided through prescription drugs and in outpatient settings and less in inpatient settings. Payer mix has also shifted, with Medicaid taking a more prominent role. Conclusions Spending on mental health treatment has increased over the past decade, reflecting increases in the number of individuals receiving mental health treatment, particularly prescription drugs and outpatient treatment. Changes in payer and provider mix raise new challenges for ensuring quality and access.

Since 1987, public and private investment in substance abuse (SA) treatment has not kept pace with other health spending. SA treatment spending in the United States grew from $9.3 billion in 1986 to $20.7 billion in 2003. The average annual total growth rate was 4.8 percent. In comparison, total U.S. health care spending grew by 8.0 percent. As a result of the slower growth of SA spending compared to that for all health care, SA spending fell as a share of all health spending from 2.1 percent in 1986 to 1.3 percent in 2003.

Using data from a special supplement to the 2006 Kaiser/HRET Employer Health Benefits Survey, this study examines the state of employer-sponsored insurance substance abuse benefits in 2006 and how benefits compare to coverage for medical-surgical services. In 2006, 88 percent of insured workers had some coverage for substance abuse services. Current substance abuse benefits, however, do not provide the same protection afforded under medical-surgical benefits. Instead, substance abuse benefits are characterized by higher cost sharing and annual limits and lifetime limits on inpatient and outpatient care. These limits generally do not exist for other medical conditions and have increased since 1990.

Spending for mental health and substance abuse (MHSA) treatment in the United States totaled dollar 104 billion in 2001, representing 7.6 percent of all health care spending. The nominal MHSA annual spending growth rate from 1991 to 2001 was 5.6 percent, almost one percentage point below the growth rate for all health care (6.5 percent). During this period, Medicaid has increased to be the largest payer of mental health care, with prescription drugs the fastest-growing spending component. Private insurance payment for substance abuse actually dropped in real dollars, increasing the public share of substance abuse spending.

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.

This article examines 1997 national expenditures on mental health and substance abuse (MH/SA) treatment by 3 major age groups: 0–17, 18–64, and 65 and older. Of the total $82.4 billion in MH/SA expenditures, 13% went to children, 72% to adults, and 15% to older adults. MH/SA treatment expenditures made up 9% of total health care expenditures on children, 11% of total health care expenditures on adults, and 3% of total health care expenditures on older adults. Across the 3 age groups, distinct differences emerged in the distribution of MH/SA expenditures by provider-type. For example, about 85% of spending for youth was for specialty MH/SA providers, compared to 76% for adults and 51% for older adults. In addition, 33% of MH/SA spending for older adults went to nursing home care, while other age groups had almost no expenditures in nursing homes. Age-specific estimates enable policymakers, providers, and researchers to design programs and studies more appropriately tailored to specific age groups.

This paper examines the determinants of whether an individual received continuing treatment/rehabilitation services 30 days after receiving inpatient substance abuse detoxification. Data came from 1997-1999 employer health insurance claims. Only 49.4% of detoxification episodes were followed by continuing mental health or substance abuse treatment within 30 days after discharge. Some of the factors positively associated with receiving continuing treatment after receiving detoxification included: female gender, being in a behavioral health carve-out plan, and lower cost-sharing requirements for an outpatient substance abuse visit.

OBJECTIVE: The authors reviewed studies of Medicaid spending on mental health and substance abuse services. METHODS: Studies were identified through a search of MEDLINE and bibliographies of known articles on mental health and substance abuse spending and by searching Web sites of or contacting key government and private organizations. Of 448 studies identified, the 14 that included Medicaid expenditure percentages for 1984 or later were compared. RESULTS AND CONCLUSIONS: The most comprehensive studies of such spending suggest that between 9.3 and 13 percent of all Medicaid dollars are spent on behavioral health services. The most comprehensive estimates came from claims-based studies or studies based on the National Health Accounts. Studies based on provider or consumer surveys missed large portions of Medicaid spending. Policy makers need to ensure that they use the most accurate data to track mental health and substance abuse spending, an important part of total Medicaid expenditures.

Insurance benefits can have a large effect on whether one is able to access health care services. Mental health and substance abuse (MHSA) insurance coverage has typically been less generous than that of general health services.This paper examines trends in the generosity of private insurance benefits for mental health (MH) services in the United States from 1987 to 1996. The paper estimates the benefit-induced change in insurance payments for MH services that would have been made by typical health plans between 1987 and 1996 holding constant utilization of individuals at the 1987 level so that the changes in effective benefits could be isolated.Trends in mental health benefits were measured using two nationally representative household surveys of the U.S. civilian non-institutionalized population, the 1987 National Medical Expenditure Survey (NMES) and the 1996 Medical Expenditure Panel Survey (MEPS). Data on utilization and expenditures from the NMES/MEPS were used to simulate what the average person would have paid out-of-pocket under typical insurance plans in 1987 and in 1996.The study finds that limits on MH coverage, such as limits on reimbursed days of care, became more prevalent from 1987 to 1996, but that consumer cost-sharing rates declined. The simulations indicate that private insurance would have paid for a lower proportion of total spending in 1996 (60.1 percent) as compared to 1987 (65.8 percent).Despite the fact that limits on mental health services became more prevalent over the time-period evaluated, out-of-pocket expenditures did not increase as significantly because there was a corresponding increase in coinsurance covered by health plans.Trends in plan design negatively affected those with high costs who are likely to surpass their limits and positively affected coverage for those with minimal use due to lower cost-sharing. These trends also indicate that persons in the most need, those with high utilization, particularly of inpatient care, experienced a decline in coverage while those with less intensive needs may have experienced a slight increase.Out-of-pocket spending in both years of the study was substantial suggesting that improved health care coverage, such as that mandated in parity legislation, could improve access to care for persons needing mental health treatment.Additional research is needed to understand how trends in out-of-pocket spending and insurance benefits have influenced access to care.

Beginning October 1, 1983, Medicare began reimbursing many hospitals on the basis of a set of fixed fees tied to Diagnosis-Related Groups (DRGs). Using 1979-1981 Maryland data for Medicare patients, this paper compares the DRG system with the Disease Staging patient classification system in terms of structure, explanation of resource consumption (length of stay) of hospital patients, and impact on reimbursement by type of hospital. The two systems are conceptually and empirically different in classifying patients. Further, Disease Staging and DRGs perform similarly in explaining length-of-stay variation among Maryland patients. However, the two systems generate substantially different reimbursements by type of hospital. Surprisingly, large hospitals (including urban, not-for-profit, teaching hospitals) fare better under a DRG-based reimbursement system than under Disease Staging, a severity-of-illness system that excludes procedures as a basis of classification. These results imply that reimbursement policy based on Disease Staging would create disincentives to perform surgery compared with the current DRGs.

Background The presence of multiple chronic conditions (MCCs) complicates inpatient hospital care, leading to higher costs and utilization. Multimorbidity also complicates primary care, increasing the likelihood of hospitalization for ambulatory care sensitive conditions. The purpose of this study was to evaluate how MCCs relate to inpatient hospitalization costs and utilization for ambulatory care sensitive conditions. Methods The 2012 Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) provided data to carry out a cross-sectional analysis of 1.43 million claims related to potentially preventable hospitalizations classified by the AHRQ Prevention Quality Indicator (PQI) composites. Categories of MCCs (0–1, 2–3, 4–5, and 6+) were examined in sets of acute, chronic, and overall PQIs. Multivariate models determined associations between categories of MCCs and 1) inpatient costs per stay, 2) inpatient costs per day, and 3) length of inpatient hospitalization. Negative binomial was used to model costs per stay and costs per day. Results The most common category observed was 2 or 3 chronic conditions (37.8 % of patients), followed by 4 or 5 chronic conditions (30.1 % of patients) and by 6+ chronic conditions (10.1 %). Compared with costs for patients with 0 or 1 chronic condition, hospitalization costs per stay for overall ambulatory care sensitive conditions were 19 % higher for those with 2 or 3 (95 % confidence interval [CI] 1.19–1.20), 32 % higher for those with 4 or 5 (95 % CI 1.31–1.32), and 31 % higher (95 % CI 1.30–3.32) for those with 6+ conditions. Acute condition stays were 11 % longer when 2 or 3 chronic conditions were present (95 % CI 1.11–1.12), 21 % longer when 4 or 5 were present (95 % CI 1.20–1.22), and 27 % longer when 6+ were present (95 % CI 1.26–1.28) compared with those with 0 or 1 chronic condition. Similar results were seen within chronic conditions. Associations between MCCs and total costs were driven by longer stays among those with more chronic conditions rather than by higher costs per day. Conclusions The presence of MCCs increased inpatient costs for ambulatory care sensitive conditions via longer hospital stays.

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.