Linda Schieb

Pulmonary Hypertension Surveillance: United States, 2001 to 2010

Pulmonary hypertension (PH) is an uncommon but progressive condition, and much of what we know about it comes from specialized disease registries. With expanding research into the diagnosis and treatment of PH, it is important to provide updated surveillance on the impact of this disease on hospitalizations and mortality. This study, which builds on previous PH surveillance of mortality and hospitalization, analyzed mortality data from the National Vital Statistics System and data from the National Hospital Discharge Survey between 2001 and 2010. PH deaths were identified using International Classification of Diseases, Tenth Revision codes I27.0, I27.2, I27.8, or I27.9 as any contributing cause of death on the death certificate. Hospital discharges associated with PH were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes 416.0, 416.8, or 416.9 as one of up to seven listed medical diagnoses. The decline in death rates associated with PH among men from 1980 to 2005 has reversed and now shows a significant increasing trend. Similarly, the death rates for women with PH have continued to increase significantly during the past decade. PH-associated mortality rates for those aged 85 years and older have accelerated compared with rates for younger age groups. There have been significant declines in PH-associated mortality rates for those with pulmonary embolism and emphysema. Rates of hospitalization for PH have increased significantly for both men and women during the past decade; for those aged 85 years and older, hospitalization rates have nearly doubled. Continued surveillance helps us understand and address the evolving trends in hospitalization and mortality associated with PH and PH-associated conditions, especially regarding sex, age, and race/ethnicity disparities.

Trends and Disparities in Heart Disease Mortality Among American Indians/Alaska Natives, 1990–2009

OBJECTIVES We evaluated heart disease death rates among American Indians and Alaska Natives (AI/ANs) and Whites after improving identification of AI/AN populations. METHODS Indian Health Service (IHS) registration data were linked to the National Death Index for 1990 to 2009 to identify deaths among AI/AN persons aged 35 years and older with heart disease listed as the underlying cause of death (UCOD) or 1 of multiple causes of death (MCOD). We restricted analyses to IHS Contract Health Service Delivery Areas and to non-Hispanic populations. RESULTS Heart disease death rates were higher among AI/AN persons than Whites from 1999 to 2009 (1.21 times for UCOD, 1.30 times for MCOD). Disparities were highest in younger age groups and in the Northern Plains, but lowest in the East and Southwest. In AI/AN persons, MCOD rates were 84% higher than UCOD rates. From 1990 to 2009, UCOD rates declined among Whites, but only declined significantly among AI/AN persons after 2003. CONCLUSIONS Analysis with improved race identification indicated that AI/AN populations experienced higher heart disease death rates than Whites. Better prevention and more effective care of heart disease is needed for AI/AN populations.

Tracking Stroke Hospitalization Clusters Over Time and Associations With County-Level Socioeconomic and Healthcare Characteristics

Background and Purpose— This study evaluated clustering of stroke hospitalization rates, patterns of the clustering over time, and associations with community-level characteristics. Methods— We used Medicare hospital claims data from 1995–1996 to 2005–2006 with a principal discharge diagnosis of stroke to calculate county-level stroke hospitalization rates. We identified statistically significant clusters of high- and low-rate counties by using local indicators of spatial association, tracked cluster status over time, and assessed associations between cluster status and county-level socioeconomic and healthcare profiles. Results— Clearly defined clusters of counties with high- and low-stroke hospitalization rates were identified in each time. Approximately 75% of counties maintained their cluster status from 1995–1996 to 2005–2006. In addition, 243 counties transitioned into high-rate clusters, and 148 transitioned out of high-rate clusters. Persistently high-rate clusters were located primarily in the Southeast, whereas persistently low-rate clusters occurred mostly in New England and in the West. In general, persistently low-rate counties had the most favorable socioeconomic and healthcare profiles, followed by counties that transitioned out of or into high-rate clusters. Persistently high-rate counties experienced the least favorable socioeconomic and healthcare profiles. Conclusions— The persistence of clusters of high- and low-stroke hospitalization rates during a 10-year period suggests that the underlying causes of stroke in these areas have also persisted. The associations found between cluster status (persistently high, transitional, persistently low) and socioeconomic and healthcare profiles shed new light on the contributions of community-level characteristics to geographic disparities in stroke hospitalizations.

Changes in the Geographic Patterns of Heart Disease Mortality in the United States 1973 to 2010

Background— Although many studies have documented the dramatic declines in heart disease mortality in the United States at the national level, little attention has been given to the temporal changes in the geographic patterns of heart disease mortality. Methods and Results— Age-adjusted and spatially smoothed county-level heart disease death rates were calculated for 2-year intervals from 1973 to 1974 to 2009 to 2010 for those aged ≥35 years. Heart disease deaths were defined according to the International Classification of Diseases codes for diseases of the heart in the eighth, ninth, and tenth revisions of the International Classification of Diseases. A fully Bayesian spatiotemporal model was used to produce precise rate estimates, even in counties with small populations. A substantial shift in the concentration of high-rate counties from the Northeast to the Deep South was observed, along with a concentration of slow-decline counties in the South and a nearly 2-fold increase in the geographic inequality among counties. Conclusions— The dramatic change in the geographic patterns of heart disease mortality during 40 years highlights the importance of small-area surveillance to reveal patterns that are hidden at the national level, gives communities the historical context for understanding their current burden of heart disease, and provides important clues for understanding the determinants of the geographic disparities in heart disease mortality.

Geographic and racial patterns of preventable hospitalizations for hypertension: Medicare beneficiaries, 2004-2009.

Objectives. Hypertension as the primary reason for hospitalization is often used to indicate failure of the outpatient health-care system to prevent and control high blood pressure. Investigators have reported increased rates of these preventable hospitalizations for black people compared with white people; however, none have mapped them nationally by race. Methods. We used Medicare Part A data to estimate preventable hypertension hospitalizations from 2004–2009 using technical specifications published by the Agency for Healthcare Research and Quality. Rates per 100,000 beneficiaries were age- and sex-standardized to 2000 U.S. Census data. We mapped county-level rates by race and identified clusters of counties with extreme rates. Results. Black people had higher crude rates of these hospitalizations than white people for every year studied, and the test for an increasing linear time trend for the standardized rates was significant for both black and white people; that is, the gap between the races increased over time. For both races, clusters of high-rate counties occurred primarily in parts of Oklahoma, Texas, Southern Alabama, and Louisiana. High rates for white people were also found in parts of Appalachia. Large differences in rates among black and white people were found in a number of large urban areas and in parts of Florida and Alabama. Conclusions. Racial disparities in preventable hospitalizations for hypertension persisted through 2009. The gap between black and white people is increasing, and these inequities exist unevenly across the country. Although this study was intended to be purely descriptive, future studies should use multivariate analyses to examine reasons for these unequal distributions.

Trends and Disparities in Stroke Mortality by Region for American Indians and Alaska Natives

OBJECTIVES We evaluated trends and disparities in stroke death rates for American Indians and Alaska Natives (AI/ANs) and White people by Indian Health Service region. METHODS We identified stroke deaths among AI/AN persons and Whites (adults aged 35 years or older) using National Vital Statistics System data for 1990 to 2009. We used linkages with Indian Health Service patient registration data to adjust for misclassification of race for AI/AN persons. Analyses excluded Hispanics and focused on Contract Health Service Delivery Area (CHSDA) counties. RESULTS Stroke death rates among AI/AN individuals were higher than among Whites for both men and women in CHSDA counties and were highest in the youngest age groups. Rates and AI/AN:White rate ratios varied by region, with the highest in Alaska and the lowest in the Southwest. Stroke death rates among AI/AN persons decreased in all regions beginning in 2001. CONCLUSIONS Although stroke death rates among AI/AN populations have decreased over time, rates are still higher for AI/AN persons than for Whites. Interventions that address reducing stroke risk factors, increasing awareness of stroke symptoms, and increasing access to specialty care for stroke may be more successful at reducing disparities in stroke death rates.

Vital Signs: Recent Trends in Stroke Death Rates - United States, 2000-2015

Introduction The prominent decline in U.S. stroke death rates observed for more than 4 decades has slowed in recent years. CDC examined trends and patterns in recent stroke death rates among U.S. adults aged ≥35 years by age, sex, race/ethnicity, state, and census region. Methods Trends in the rates of stroke as the underlying cause of death during 2000–2015 were analyzed using data from the National Vital Statistics System. Joinpoint software was used to identify trends in stroke death rates, and the excess number of stroke deaths resulting from unfavorable changes in trends was estimated. Results Among adults aged ≥35 years, age-standardized stroke death rates declined 38%, from 118.4 per 100,000 persons in 2000 to 73.3 per 100,000 persons in 2015. The annual percent change (APC) in stroke death rates changed from 2000 to 2015, from a 3.4% decrease per year during 2000–2003, to a 6.6% decrease per year during 2003–2006, a 3.1% decrease per year during 2006–2013, and a 2.5% (nonsignificant) increase per year during 2013–2015. The last trend segment indicated a reversal from a decrease to a statistically significant increase among Hispanics (APC = 5.8%) and among persons in the South Census Region (APC = 4.2%). Declines in stroke death rates failed to continue in 38 states, and during 2013–2015, an estimated 32,593 excess stroke deaths might not have occurred if the previous rate of decline could have been sustained. Conclusions and Implications for Public Health Practice Prior declines in stroke death rates have not continued in recent years, and substantial variations exist in timing and magnitude of change by demographic and geographic characteristics. These findings suggest the importance of strategically identifying opportunities for prevention and intervening in vulnerable populations, especially because effective and underused interventions to prevent stroke incidence and death are known to exist.

Comparing methods of measuring geographic patterns in temporal trends: an application to county-level heart disease mortality in the United States, 1973 to 2010

PURPOSE To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010. METHODS We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty. RESULTS The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods. CONCLUSIONS The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates.

Is there an association between quality of in-hospital cardiac care and proportion of low-income patients?

Background:Process measures have been developed and implemented to evaluate the quality of care patients receive in the hospital. This study examines whether there is an association between the quality of in-hospital cardiac care and a hospitals proportion of low-income patients. Methods and Results:A retrospective analysis of 1979 hospitals submitting information on 12 quality of care (QoC) process measures for acute myocardial infarction (AMI) and congestive heart failure (CHF) patients to the Hospital Quality Alliance during 2005 and 2006 and meeting all study inclusion criteria. Mean hospital performance ranged from 84.2% (ACE inhibitor for left ventricular systolic dysfunction) to 95.9% (aspirin on arrival) for AMI QoC process measures and from 64.4% (discharge instructions) to 92.4% (left ventricular function assessment) for CHF QoC process measures. Regression analyses indicated a statistically significant negative association between the proportion of low-income patients and hospital performance for 10 of the 12 cardiac QoC process measures, after controlling for selected hospital characteristics. Conclusions:Hospital adherence to QoC process measures for AMI and CHF patients declined as the proportion of low-income patients increased. Future research is needed to examine the role of community characteristics and market forces on the ability of hospitals with a disproportionate share of low-income patients to maintain the staffing, equipment, and policies necessary to provide the recommended standards of care for AMI and CHF patients.

Putting chronic disease on the map: building GIS capacity in state and local health departments.

Techniques based on geographic information systems (GIS) have been widely adopted and applied in the fields of infectious disease and environmental epidemiology; their use in chronic disease programs is relatively new. The Centers for Disease Control and Prevention’s Division for Heart Disease and Stroke Prevention is collaborating with the National Association of Chronic Disease Directors and the University of Michigan to provide health departments with capacity to integrate GIS into daily operations, which support priorities for surveillance and prevention of chronic diseases. So far, 19 state and 7 local health departments participated in this project. On the basis of these participants’ experiences, we describe our training strategy and identify high-impact GIS skills that can be mastered and applied over a short time in support of chronic disease surveillance. We also describe the web-based resources in the Chronic Disease GIS Exchange that were produced on the basis of this training and are available to anyone interested in GIS and chronic disease (www.cdc.gov/DHDSP/maps/GISX). GIS offers diverse sets of tools that promise increased productivity for chronic disease staff of state and local health departments.