Admissions after discharge from an emergency department for chest symptoms

BACKGROUND

Often patients who present to the emergency department (ED) with chest symptoms return to the hospital within 30 days with the same or closely related symptoms and are admitted, raising questions about quality of care, timeliness of diagnosis, and patient safety. This study examined the frequency of and patient characteristics associated with subsequent inpatient admissions for related symptoms after discharge from an ED for chest symptoms.

METHODS

We used data from the 2012 and 2013 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) and State Emergency Department Databases (SEDD) from eight states to identify over 1.8 million ED discharges for chest symptoms.

RESULTS

Approximately 3% of ED discharges experienced potentially related subsequent admissions within 30 days - 0.2% for acute myocardial infarction (AMI), 1.7% for other cardiovascular conditions, 0.5% for respiratory conditions, and 0.6% for mental disorders. Logistic regression results showed higher odds of subsequent admission for older patients and those residing in low-income areas, and lower odds for females and non White racial/ethnic groups. Privately insured patients had lower odds of subsequent admission than did those who were uninsured or covered by other programs.

CONCLUSIONS

Because we included multiple diagnostic categories of subsequent admissions, our results show a more complete picture of patients presenting to the ED with chest symptoms compared with previous studies. In particular, we show a lower rate of subsequent admission for AMI versus other diagnoses. ED physicians and administrators can use the results to identify characteristics associated with increased odds of subsequent admission to target at-risk populations.

Differences in severity at admission for heart failure between rural and urban patients: the value of adding laboratory results to administrative data

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.

Understanding Racial and Ethnic Disparities in Postsurgical Complications Occurring in U.S. Hospitals

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.

Impact of Race/Ethnicity and Socioeconomic Status on Risk-Adjusted Readmission Rates

Under the Hospital Readmissions Reduction Program (HRRP) of the Centers for Medicare & Medicaid Services (CMS), hospitals with excess readmissions for select conditions and procedures are penalized. However, readmission rates are not risk adjusted for socioeconomic status (SES) or race/ethnicity. We examined how adding SES and race/ethnicity to the CMS risk-adjustment algorithm would affect hospitals’ excess readmission ratios and potential penalties under the HRRP. For each HRRP measure, we compared excess readmission ratios with and without SES and race/ethnicity included in the CMS standard risk-adjustment algorithm and estimated the resulting effects on overall penalties across a number of hospital characteristics. For the 5 HRRP measures (heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and total hip or knee arthroplasty), we used data from the Healthcare Cost and Utilization Project’s State Inpatient Databases for 2011-2012 to calculate the excess readmission ratio with and without SES and race/ethnicity included in the model. With these ratios, we estimated the impact on HRRP penalties and found that risk adjusting for SES and race/ethnicity would affect Medicare payments for 83.8% of hospitals. The effect on the size of HRRP penalties ranged from −14.4% to 25.6%, but the impact on overall Medicare base payments was small—ranging from −0.09% to 0.06%. Including SES and race/ethnicity in the calculation had a disproportionately favorable effect on safety-net and rural hospitals. Any financial effects on hospitals and on the Medicare program of adding SES and race/ethnicity to the HRRP risk-adjustment calculation likely would be small.

Length of stay in EDs: variation across classifications of clinical condition and patient discharge disposition

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.

Disparities in rates of inpatient mortality and adverse events: race/ethnicity and language as independent contributors

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.

Federal spending on behavioral health accelerated during recession as individuals lost employer insurance

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.

Current and future funding sources for specialty mental health and substance abuse treatment providers

OBJECTIVES

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.

METHODS

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).

RESULTS

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%).

CONCLUSIONS

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 value of linking hospital discharge and mortality data for comparative effectiveness research

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.

Congestive heart failure: who is likely to be readmitted?

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.

Psychiatric discharges in community hospitals with and without psychiatric units: how many and for whom?

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.

Evidence for substance abuse services and policy research: a systematic review of national databases

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.

Transforming mental health and substance abuse data systems in the United States

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.

Future funding for mental health and substance abuse: increasing burdens for the public sector

Spending on mental health (MH) and substance abuse (SA) treatment is expected to double between 2003 and 2014, to $239 billion, and is anticipated to continue falling as a share of all health spending. By 2014, our projections of SA spending show increasing responsibility for state and local governments (45 percent); deteriorating shares financed by private insurance (7 percent); and 42 percent of SA spending going to specialty SA centers. For MH, Medicaid is forecasted to fund an increasingly larger share of treatment costs (27 percent), and prescription medications are expected to capture 30 percent of MH spending by 2014.

Mental health treatment expenditure trends, 1986-2003

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.

Trends In Spending For Substance Abuse Treatment, 1986–2003

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.

Substance abuse benefits: still limited after all these years

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.

U.S. spending for mental health and substance abuse treatment, 1991-2001

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.

Racial, ethnic, and socioeconomic disparities in estimates of AHRQ patient safety indicators

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.

The Decline In Receipt Of Substance Abuse Treatment By The Privately Insured, 1992–2001

This study examines underlying trends in substance abuse services financed by private insurance. Analyses are based on the 1992 and 2001 Medstat MarketScan database, a claims database from large employers. The percentage of beneficiaries using any substance abuse services declined by 23 percent from 1992 to 2001 (from 0.64 percent of enrollees to 0.49 percent of enrollees). This decline was evident in all categories: inpatient, outpatient, and pharmaceutical usage. Substance abuse spending per covered life (in constant dollars) dropped from about $21.16 in 1992 to about $5.58 in 2001 [corrected]

National spending on mental health and substance abuse treatment by age of clients, 1997

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.

Medicaid expenditures on behavioral health care

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.

What drove private health insurance spending on mental health and substance abuse care, 1992-1999?

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.

Trends in inpatient detoxification services, 1992-1997

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.

Trends in mental health insurance benefits and out-of-pocket spending

BACKGROUND

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.

AIMS OF THE STUDY

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.

METHODS

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.

RESULTS

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).

DISCUSSION

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.

IMPLICATIONS FOR HEALTH CARE PROVISION AND USE

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.

IMPLICATIONS FOR HEALTH POLICIES

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.

IMPLICATION FOR FURTHER RESEARCH

Additional research is needed to understand how trends in out-of-pocket spending and insurance benefits have influenced access to care.

Studying the effects of health plan competition: are available data resources up to the task?

OBJECTIVES

To review the availability of data sources to study health plan competition in the United States.

DATA SOURCES

The literature on health plan competition was reviewed. Possible data sources to study health plan competition were evaluated. Experts in the field of health plan competition were contacted about their knowledge of existing data sources. Principal Findings. There is much more quantitative data available on HMO plans than on other types of health plans that are growing in popularity, such as PPOs. A key source for health plan data, state health insurance filings, lacks information on beneficiaries in non-HMO plans. Data on health plan quality is growing. In addition, case studies of particular markets is providing useful qualitative information on the dynamics of the health plan industry.

CONCLUSIONS

The fragmentation of the health care market and the hesitancy of governments and private organizations to provide detailed information across markets and providers creates serious obstacles to the study of health plan competition.

Recent trends in the financing of substance abuse treatment: implications for the future

OBJECTIVE

This article focuses on the implications of a recent study of substance abuse (SA) and mental health treatment expenditures for substance abuse treatment policy. Public and private expenditures for SA treatment are estimated and compared with those for mental health and all health care in the period between 1987 and 1997.

METHODS/DATA SOURCES

Estimates of SA treatment expenditures were segregated from the Health Care Financing Administration's National Health Accounts across the ten-year period. Information about use, charges, and payments by provider type, payer, and diagnosis was obtained from numerous nationally representative data sets and large claims databases. Those data were used to estimate SA treatment expenditures in the general service sector. For the specialty sector two specialty facility surveys were used to estimate SA treatment expenditures. Information from the two sectors was combined and reconciled to the National Health Accounts. PRINCIPAL FINDINGS. A dramatic shift in SA expenditures away from private financing and toward public payers, as well as a shift away from hospital treatment settings, occurred between 1987 and 1997.

CONCLUSIONS

Evidence from this article and other research suggests that growth in SA expenditures has been contained relative to growth in all health spending. How savings from SA treatment are being invested and whether expenditure levels are appropriate to supply treatment of acceptable quality needs further study.

Spending on mental health and substance abuse treatment, 1987-1997

This paper is the result of an ongoing effort to track spending on mental health and substance abuse (MH/SA) treatment nationwide. Spending for MH/SA treatment was $85.3 billion in 1997: $73.4 billion for mental illness and $11.9 billion for substance abuse. MH/SA spending growth averaged 6.8 percent a year between 1987 and 1997, while national health expenditures grew by 8.2 percent.

Comorbidity measures for use with administrative data

OBJECTIVES

This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets.

METHODS

The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogeneous patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital death.

RESULTS

A comprehensive set of 30 comorbidity measures was developed. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders.

CONCLUSIONS

The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.

The case for national health data standards

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) contains groundbreaking provisions to encourage the development of a national health information system through the establishment of standards. This paper compares statewide inpatient data systems to one standard--the Uniform Bill (UB)--to understand how standards have been used and how they can be improved. We recommend changes to the UB, note the need for better compliance, and suggest new standards for common, derived elements.

Trauma systems and the costs of trauma care

OBJECTIVE

This study examines the cost of providing trauma services in trauma centers organized by publicly administered trauma systems, compared to hospitals not part of a formal trauma system.

DATA SOURCES AND STUDY SETTING

Secondary administrative discharge abstracts for a national sample of severely injured trauma patients in 44 trauma centers and 60 matched control hospitals for the year 1987 were used.

STUDY DESIGN

Retrospective univariate and multivariate analyses were conducted to examine the impact of formal trauma systems and trauma center designation on the costs of treating trauma patients. Key dependent variables included length of stay, charge per day per patient, and charge per hospital stay. Key impact variables were type of trauma system and level of trauma designation. Control variables included patient, hospital, and community characteristics.

DATA COLLECTION/EXTRACTION METHODS

Data were selected for hospitals based on (1) a large national hospital discharge database, the Hospital Cost and Utilization Project, 1980-1987 (HCUP-2) and (2) a special survey of trauma systems and trauma designation undertaken by the Hospital Research and Educational Trust of the American Hospital Association.

PRINCIPAL FINDINGS

The results show that publicly designated Level I trauma centers, which are the focal point of most trauma systems, have the highest charge per case, the highest average charge per day, and similar or longer average lengths of stay than other hospitals. These findings persist after controlling for patient injury and health status, and for demographic characteristics and hospital and community characteristics.

CONCLUSIONS

Prior research shows that severely injured trauma patients have greater chances of survival when treated in specialized trauma centers. However, findings here should be of concern to the many states developing trauma systems since the high costs of Level I centers support limiting the number of centers designated at this level and/or reconsidering the requirements placed on these centers.

Treating early-stage breast cancer: hospital characteristics associated with breast-conserving surgery

Despite growing acceptance of the fact that women with early-stage breast cancer have similar outcomes with lumpectomy plus radiation as with mastectomy, many studies have revealed the uneven adoption of such breast-conserving surgery. Discharge data from the Hospital Cost and Utilization Project, representing multiple payers, locations, and hospital types, demonstrate increasing trends in breast-conserving surgery as a proportion of breast cancer surgeries from 1981 to 1987. Women with axillary node involvement were less likely to have a lumpectomy, even though consensus recommendations do not preclude this form of treatment when local metastases are present. Non-White race, urban hospital location, and hospital teaching were associated with an increased likelihood of having breast-conserving surgery.

Change in the Medicare case-mix index in the 1980s and the effect of the prospective payment system

Persistent increases in the Medicare case-mix index over the 1980s have been ascribed to changes both in medical treatment ("real changes") and in the way medical information is recorded ("coding changes") in hospitals. These changes have been attributed, in the absence of appropriate data and analyses, to the incentives of the Medicare prospective payment system (PPS). Using data for 1980-1986 from 235 hospitals, we estimate the effect on the Medicare case-mix index of a series of variables that reflect medical treatments and coding practices. Each of these underlying real or coding variables was changing prior to PPS and would likely have continued to change even in the absence of PPS. Furthermore, PPS may have had a distinct effect on these variables. These underlying trends and the PPS effects must each be estimated. Thus, the analysis begins by developing separate estimates for each of these real and coding variables (1) in the absence of PPS (autonomous effects) and (2) as a result of PPS (induced effects). Then, changes in the case-mix index are regressed against all of these variables to determine the degree to which specific autonomous real or coding variables or induced real or coding variables actually influenced measured case mix. Results show that real and coding changes each accounted for about half of the change in the Medicare case-mix index between 1980 and 1986, with the influence of coding starting to wane by 1986. PPS-induced factors explain about 80 percent of the change in measured case mix over time, autonomous factors about 20 percent. Especially powerful determinants of case-mix change included PPS-induced substitution of surgical for medical care and PPS-induced improvements in the accuracy of coding that led to assignment of patients to higher-weighted DRGs. Also, stringent Medicare peer review organizations appeared to restrain rises in case-mix indexes for their hospitals. Outpatient substitution for inpatient treatment, which others attributed to PPS, was well underway before PPS was announced.

DRGs and disease staging for reimbursing Medicare patients

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.

Hospital DRGs and the need for long-term care services: an empirical analysis

The Medicare DRG-based Prospective Payment System (PPS) encourages hospitals to reduce length of stay for elderly patients. Thus, discharges to long-term care services are expected to increase. Maryland hospital data for 1980 are used to identify those DRGs which most frequently represent patients discharged to nursing home and home health care services; explores the incentive to discharge earlier under PPS those patients needing long-term care versus short-term care; and describes characteristics of patients most likely to face increased pressure of earlier discharge to nursing homes and home health programs. Because only a limited set of patient characteristics are available from Maryland hospitals, data from a study of San Diego nursing homes are used to explore further the sociodemographic and health status measures associated with unusually long stays in a hospital prior to nursing home placement. This research suggests that the DRG reimbursement system gives hospitals a strong incentive for earlier discharge of patients needing long-term care services. However, hospitals that target only long-term care patients for early discharge will not substantially gain under PPS because these patients represent a small portion of the cases treated in the hospital and a small percentage of unreimbursed days.