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Differences in Prevalence, Treatment, and Outcomes of Asthma Among a Diverse Population of Children With Equal Access to Care:  Findings From a Study in the Military Health System FREE

Kate A. Stewart, PhD; Patricia C. Higgins, PhD; Catherine G. McLaughlin, PhD; Thomas V. Williams, PhD; Elder Granger, MD; Thomas W. Croghan, MD
[+] Author Affiliations

Author Affiliations: Mathematica Policy Research, Inc (Drs Stewart, Higgins, and Croghan) and Departments of Medicine and Psychiatry, Georgetown University School of Medicine (Dr Croghan), Washington, DC; Mathematica Policy Research, Inc, Ann Arbor, Michigan (Dr McLaughlin); and Center for Health Care Management Studies, TRICARE Management Activity, Falls Church, Virginia (Drs Williams and Granger). Dr Stewart is now at Mathematica Policy Research, Inc, Chicago, Illinois. Dr Granger has now retired.


Arch Pediatr Adolesc Med. 2010;164(8):720-726. doi:10.1001/archpediatrics.2010.100.
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Objective  To assess racial and ethnic differences in asthma prevalence, treatment patterns, and outcomes among a diverse population of children with equal access to health care.

Design  Retrospective cohort analysis.

Setting  The Military Health System.

Participants  A total of 822 900 children aged 2 through 17 years continuously enrolled throughout 2007 in TRICARE Prime, a health maintenance organization–type benefit provided by the Department of Defense.

Main Outcome Measures  Prevalence of diagnosed asthma, potentially avoidable asthma hospitalizations, asthma-related emergency department visits, visits to asthma specialists, and use of asthma medications among children aged 2 to 4, 5 to 10, and 11 to 17 years.

Results  Black and Hispanic children in all age groups were significantly more likely to have an asthma diagnosis than white children (ranging from odds ratio [OR] = 1.16; 95% confidence interval [CI], 1.09-1.24; to OR = 2.00; 95% CI, 1.93-2.07). Black children in all age groups and Hispanic children aged 5 to 10 years were significantly more likely to have any potentially avoidable asthma hospitalizations and asthma-related emergency department visits (ranging from OR = 1.24; 95% CI, 1.11-1.37; to OR = 1.99; 95% CI, 1.37-2.88) and were significantly less likely to visit a specialist (ranging from OR = 0.71; 95% CI, 0.61-0.82; to OR = 0.88; 95% CI, 0.79-0.98) compared with white children. Black children in all age categories were significantly more likely to have filled any prescriptions for inhaled corticosteroids compared with white children (ranging from OR = 1.11; 95% CI, 1.02-1.21; to OR = 1.11; 95% CI, 1.04-1.19).

Conclusions  Despite universal health insurance coverage, we found evidence of racial and ethnic differences in asthma prevalence, treatment, and outcomes.Published online June 7, 2010 (doi:10.1001/archpediatrics.2010.100).

Racial and ethnic disparities in children's access to health care and health status are well documented. While many factors contribute to these disparities, universal coverage is widely considered to be a necessary component of strategies to reduce them.13 A growing literature on the impacts of Medicare, Medicaid, and Children's Health Insurance Program enrollment suggests that access to appropriate health care services is improved with coverage, but less is known about the effect of this coverage on disparities.47 Because the Military Health System (MHS) provides comprehensive health insurance to a racially and ethnically diverse population of beneficiaries, studying disparities in health care treatments and outcomes among this population could add significantly to our understanding of the potential effect of universal coverage on reducing disparities in health care.

In addition to comprehensive coverage, several other characteristics suggest a priori that fewer racial and ethnic disparities would occur among MHS enrollees, including relatively low or no cost-sharing requirements for many services and access to treatment both from direct care providers at military treatment facilities and from civilian, purchased care providers. Compared with other health care systems, the MHS may also more easily measure and set standards for quality of care provided by its direct care providers.8

Previous studies have reported racial and ethnic disparities in asthma prevalence, treatment, and outcomes among children in the general population.916 In this study, we evaluate differences by race and ethnicity in the probability of having an asthma diagnosis and, conditional on having asthma, the probability of having a potentially avoidable hospitalization (PAH) or emergency department (ED) visit among children enrolled in the MHS in 2007. Because asthma outcomes are closely tied to appropriate management,17,18 we also examine patterns of asthma-related prescription drug use and specialist visits to understand whether differences in outpatient care may be associated with observed differences in rates of asthma-related PAHs and ED use. Our primary research question was whether similar access to medical care through the MHS among a diverse population minimized racial and ethnic differences in prevalence of diagnosed asthma, treatment, and outcomes observed in previous studies.

STUDY DESIGN AND ANALYTIC COHORTS

We conducted a retrospective cohort analysis of children continuously enrolled throughout 2007 in TRICARE Prime, a voluntary health maintenance organization–type benefit option in which military treatment facilities are intended to be the principal source of care. More than 75% of children in the MHS are enrolled in Prime and about 60% are dependents of active duty personnel (Eric Schone, PhD, unpublished data, December 1, 2009). Our final analysis cohort includes 822 900 children aged 2 through 17 years after excluding those whom we could not match to a parent (n = 22), who were missing data on race and ethnicity (n = 11 568), who were not classified as Hispanic, non-Hispanic black, or non-Hispanic white (n = 84 322), or who did not have any inpatient or outpatient claims during the year (n = 127 874). We established the lower age limit owing to difficulties diagnosing asthma in children younger than 2 years and because quality and outcome measures have not been established for them.19 We excluded those without claims to develop a standard definition of asthma prevalence among health care users, as children without claims likely included both those with well-controlled asthma and those without asthma. We limited the analysis of racial and ethnic groups owing to the extreme heterogeneity among those not classified as Hispanic, non-Hispanic black, or non-Hispanic white. For analyses of asthma care and asthma-related outcomes, we identified the subsample of 59 266 children with at least 1 inpatient or 2 outpatient claims with a diagnosis for asthma (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 493.XX) in either primary or secondary diagnosis fields during the year, excluding those with cystic fibrosis (ICD-9-CM code 277.0x) and anomalies of the respiratory system (ICD-9-CM codes 747.21, 748.3, 748.4, 748.5, 7486.6x, 748.8, 748.9, 750.3, 50.3, and 770.7).

DATA SOURCES

We used data from the TRICARE Defense Enrollment Eligibility Reporting System (DEERS) to obtain information on demographic characteristics (race, ethnicity, age, sex, marital status, and region of residence) and military-related characteristics (service branch, pay grade, and rank) of children and their policy-holding parents (ie, sponsors). We linked DEERS data to information on treatment and outcomes from 5 claims databases for services provided by inpatient and outpatient direct care providers (Standard Inpatient Data Record and Standard Ambulatory Data Record), services from purchased care providers (TRICARE Encounter Data–Institutional and TRICARE Encounter Data–Noninstitutional databases), and prescriptions filled at military, community, or mail-order pharmacies (pharmacy data transaction service).

MEASURES
Race and Ethnicity

Race and ethnicity were characterized as Hispanic, non-Hispanic black (black), or non-Hispanic white (white). Because dependents are not required to report their race and ethnicity when enrolling in the MHS, the quality of children's race and ethnicity data in DEERS is poor. However, military personnel are required to self-report their race and ethnicity at the time of employment. Therefore, we used a proxy measure of race and ethnicity for the children in our cohort by matching each child to his or her sponsor parent and using this parent's reported race and ethnicity. Although this proxy measure potentially introduces measurement error for biracial children who are categorized according to their sponsor parent's race and ethnicity only, the effect is likely to make our racial and ethnic groups more similar to each other and our analyses more conservative.

To assess the concordance of sponsor race and ethnicity as reported in DEERS with parent-reported race and ethnicity of their children, we obtained survey response data from the 2002 through 2007 waves of the children's Health Care Survey of Department of Defense Beneficiaries (HCSDB).20 The HCSDB contains race and ethnicity data reported by the parent or guardian that we used to test the accuracy of the race and ethnicity data recorded in DEERS for the subset of children who participated in the survey. The children's HCSDB is conducted yearly on a random sample of approximately 35 000 beneficiaries. The response rate for the survey is approximately 20%. By searching across 5 years of survey responses, we were able to match 23 442 children from our analytic cohort to responses from the children's HCSDB.

Outcomes and Treatment

We created variables for asthma-related PAHs and ED visits from the claims data using the Agency for Healthcare Research and Quality definitions of pediatric preventable hospitalizations.21 Our measure of ED visits excluded visits associated with injuries or accidents (ICD-9-CM codes 800-999 and ICD-9-CM E-codes). For analyses of asthma treatment, we created variables to identify any prescription filled for any type of asthma medication, including short-acting β-agonists, inhaled corticosteroids (ICSs), long-acting β-agonists, and other types of asthma treatments (ie, IgE blockers, methylxanthine, antileukotrienes, anticholinergics, and mast-cell stabilizers), as well as any prescriptions for ICS, the most commonly recommended treatment for control of asthma symptoms.22 We flagged any visit to an allergist or pulmonary specialist with a diagnosis of asthma.

Control Variables

We constructed variables from DEERS for children's age on January 1, 2007 (categorized as ages 2-4, 5-10, and 11-17 years), sex, and census region of residence based on zip code (New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain, and Pacific). We included several characteristics of the sponsor/parent, including sex, marital status, the interaction between sex and marital status, pay grade (a linear variable from 1-10), and rank (enlisted or cadet, warrant officer, or officer) to proxy for socioeconomic status. We also calculated the number of siblings covered by the same parent (0, 1-2, or ≥3). In addition, we created a variable to categorize children by whether they used only direct care, only purchased care, or both direct and purchased care.

To assess comorbidity, we created categorical variables (0-1, 2-4, 5-8, and ≥9) of the number of unique nonasthma compounds (determined by the 8-digit national drug code on pharmacy claims) filled during the year based on the pharmacy claims-based pediatric comorbidity scale developed by Fishman and Shay.23

STATISTICAL ANALYSIS

To test the accuracy of our proxy race and ethnicity measure, we evaluated concordance between the proxy measure and self-reported race and ethnicity from the subset of 23 442 children who responded to the HCSDB between 2002 and 2007.

We examined the distribution of demographic and military-related characteristics, PAHs, and non-injury-related ED use overall and by race and ethnicity for the full study population and for the cohort diagnosed with asthma. We used the full cohort of children with at least 1 medical claim during the year (N = 822 900) to test for differences in the prevalence of asthma diagnoses, and we used the cohort of asthmatic children (n = 59 266) to test for differences in asthma-related outcomes (asthma-related PAHs or ED visits), specialist visits, and asthma prescription drug fills (any fills and any fills for ICS) across race and ethnic groups using χ2 tests of independence.

To test whether any racial and ethnic disparities in asthma diagnoses, outcomes, and treatments observed in bivariate analyses persisted after adjusting for differences in individual demographic and military-related characteristics and comorbidity, we fit 6 separate logistic regression models with the control variables listed above for the following: (1) diagnosed asthma, (2) any asthma-related PAH, (3) any asthma-related ED visit, (4) any specialist visit, (5) any asthma-related prescription drug fill, and (6) any fill for ICS medications. The model for diagnosed asthma, model 1, was estimated on the entire study population, whereas models 2 through 6 were estimated only on children with an observed asthma diagnosis. In addition, the models for any asthma-related PAHs and ED visits included control variables for any specialist visits, any asthma-related prescription drug fill, and any fill for ICS medications to minimize bias on the race and ethnicity coefficients due to differential rates of treatment.

The association between race/ethnicity and the outcomes of interest may vary by demographic and military-related characteristics. To test for potentially important interactions, we first estimated separate logistic regression models for each subgroup (ie, Hispanic, black, and white) for each outcome. We then compared the direction, magnitude, and statistical significance of the coefficients across models to identify any important interactions between race/ethnicity and demographic and military-related characteristics on outcomes. We found evidence of interactions between race/ethnicity and age (data not shown). It is difficult to accurately interpret the association between race/ethnicity and the outcomes of interest in logistic regression models with interactions between 3 age categories and 3 race and ethnicity categories.24,25 We therefore estimated separate models for each outcome by age group. These models allow us to interpret the association between race/ethnicity by age on each outcome.

This study was approved by the Human Subjects Protection Program of the Department of Health Affairs, TRICARE Management Activity.

For the subset of children participating in the HCSDB, there was high concordance between self-reported race and ethnicity of the sponsor parent from the DEERS and race and ethnicity reported for the child in the survey; agreement was found in 86.9%, 89.4%, and 83.4% of the cases for Hispanic, black, and white children, respectively (data not shown).

Table 1 describes demographic and military-related characteristics among all children with at least 1 medical claim and among those diagnosed with asthma. Hispanic children were younger on average compared with black and white children. Compared with the full population, a higher proportion of asthmatic children were aged 2 to 4 and 5 to 10 years and a smaller proportion were aged 11 to 17 years. Within both the full cohort and the asthmatic cohort, white children were more likely to live in the East North Central and West North Central regions, while black children were more likely to live in the South Atlantic region and Hispanic children were more likely to live in the West South Central and Pacific regions. Among all children and those with asthma, white sponsors were more likely to be officers and less likely to be enlisted or cadets. Compared with the full cohort, sponsors of children with asthma were more likely to be in the enlisted or cadet category. Compared with those without asthma, children with asthma were more likely to be seen by civilian providers. Among children with asthma, white children were less likely than Hispanic or black children to receive care only from direct care providers and more likely to receive care only from civilian providers.

Table Graphic Jump LocationTable 1. Demographic and Military-Related Characteristics Among the Full Cohort of Children and Children With Asthma

The prevalence of asthma varied significantly by race and ethnicity, with black children more likely to be diagnosed with asthma than either Hispanic or white children (9.6% vs 8.0% and 6.3%, respectively; P < .001) (Table 2). We found negligible but statistically significant differences among children with asthma in the number of unique nonasthma drugs, with white children slightly more likely to use 9 or more. There were also significant differences in unadjusted outcomes and treatment of asthma by race and ethnicity. Black children with an asthma diagnosis were more likely than Hispanic and white children to have a PAH for any reason (2.9% vs 2.2% and 1.6%, respectively; P < .001) and for asthma (2.6% vs 2.0% and 1.3%, respectively; P < .001). Similarly, black and Hispanic children were both more likely than white children to have an ED visit for any reason (45.8% and 45.3% vs 42.3%, respectively; P < .001) and for asthma (24.9% and 21.2% vs 18.0%, respectively; P < .001). White children with an asthma diagnosis were more likely than black or Hispanic children with an asthma diagnosis to see an asthma specialist (12.9% vs 9.6% and 9.6%, respectively; P < .001). Black children were significantly more likely than Hispanic or white children to fill any asthma drug prescription and any ICS prescription (P < .001 for both comparisons).

Table Graphic Jump LocationTable 2. Asthma Prevalence, Outcomes, and Treatments by Race and Ethnicitya

After adjusting for differences in demographic characteristics, military-related characteristics, and comorbidity, black and Hispanic children in all age groups were significantly more likely to have an asthma diagnosis than white children (Table 3). Black children in all age groups and Hispanic children aged 5 to 10 years were significantly more likely to have any asthma-related PAHs and ED visits and significantly less likely to visit a specialist compared with white children. Black children in all age categories were significantly more likely to have filled any prescriptions for ICSs compared with white children. Black children aged 5 to 10 years were also significantly more likely than white children to fill any asthma-related prescription, while Hispanic children aged 11 to 17 years were significantly less likely to have a prescription filled.

Table Graphic Jump LocationTable 3. Odds Ratios and 95% Confidence Intervals From Logistic Regression Models by Age for Diagnosed Asthma, Asthma-Related Outcomes, and Treatments

Despite universal health insurance coverage and access to military treatment facilities, we found evidence of racial and ethnic differences in asthma prevalence and outcomes after adjusting for differences in demographic characteristics and socioeconomic status. Compared with white children in the MHS, the prevalence of asthma among black and Hispanic children was significantly higher and their outcomes were often worse. Black children of all ages and Hispanic children between the ages of 5 and 10 years were significantly more likely to have any asthma PAH and any asthma-related ED visit. Thus, in this cohort of children enrolled in the MHS, racial and ethnic disparities remained present within a universal comprehensive health insurance system.

Our findings with regard to treatment patterns were mixed. Black children, who at all ages were more likely to have a diagnosis of asthma and to have poorer outcomes than white children, were also more likely to receive recommended asthma medications, especially ICSs. However, the higher rates of asthma medication use and asthma-related ED visits and PAHs among black children may be correlated if patients were more likely to receive and fill prescriptions for asthma medications during and after the ED visit or PAH. Black children were less likely to receive care from an asthma specialist. Several studies suggest that pediatric asthma specialty care is associated with greater use of guideline-recommended care, including more appropriate use of controller medications.2628 Among adults, specialist care was associated with lower rates of ED use and hospitalizations.29,30 Thus, even though black children filled more prescriptions for asthma medications, they may have been less likely than white children who visited specialists to control their asthma and use the medications appropriately. Among Hispanic children, only those aged 5 to 10 years had worse outcomes than white children. Like black children, Hispanic children in this age group were less likely than white children to receive care from an asthma specialist, again emphasizing the potential importance of specialty care.

The Institute of Medicine draws an important distinction between differences in treatment that result from variations in need and preferences for health care and those that result from systematic factors within the health care system or discrimination.31 Our results suggest that the differences in treatment and outcomes observed in the MHS could result from both need- and preference-based factors. For example, as one might hope, black children with asthma were more likely to receive ICSs, reflecting their increased need (a difference), but they were also less likely to receive care from specialists (a potential disparity if unrelated to preferences). Unlike black children, we did not find differences in outcomes compared with white children for Hispanic children aged 11 to 17 years, even though the latter were less likely to receive medications.

Our findings on racial and ethnic differences in asthma-related ED use and PAHs echo previous results from national surveillance data showing minority children having a higher prevalence of asthma913 and other studies reporting that minority children with asthma are 2 to 3 times more likely than white children to seek urgent care in the ED and to experience asthma-related PAHs.14,15,32,33 They are not consistent with the results of a previous study of children with asthma treated in military treatment facilities, which found no significant differences across race and ethnicity for ED use or hospitalizations for asthma.34 However, the previous study's small sample size, limited number of clinics studied, and nonrandom sample preclude definitive conclusions.

Additional medical and nonmedical factors could contribute to the observed differences in asthma-related PAHs and ED use, including differences in patient trust in health care providers and differences in quality of care provided to minority children within the MHS. Many environmental and social factors contribute to the prevalence, severity, and outcomes of asthma among children, including exposure to air pollution, secondhand cigarette smoke, cockroaches and other pests, household pets, mold, and combustion by-products.35,36 If black and Hispanic children were more likely to be exposed to these environmental factors, this may also partially explain our results. However, given the frequency with which military families relocate, it is unclear how relatively short-term exposures to air pollution affect asthma prevalence and outcomes. In addition, recent surveys of military service personnel suggest that white adults are more likely to smoke than black or Hispanic adults.37 Genetic differences across racial and ethnic groups may also play some role in our findings, although the extent to which that is likely remains unclear.38 These findings suggest promising avenues for future research on potential causes of asthma disparities in the MHS, including evaluation of differences in trust in the medical care system and health care providers, medical care quality (including differences in training and resources between direct and purchased care providers), and home environments across racial and ethnic groups.

The results of our study should be taken in the context of its limitations. Most importantly, by using parents' race and ethnicity as a proxy for children's race and ethnicity, we likely misclassified a proportion of the study population's race and ethnicity and could not identify biracial children in the sample. The impact of this misclassification is likely to make our estimates more conservative. All children of black and Hispanic parents working in the military were characterized as minorities, but some children of white parents working in the military likely had a Hispanic or black other parent, and these children were included as white children in the reference group. Therefore, there may be overlap in the racial and ethnic composition of our study groups. Because these analyses were based on claims data, we may also have excluded well-controlled asthmatic children (ie, those who did not use health care services in 2007) from our analyses. If more black and Hispanic children had well-controlled asthma relative to white children, we may have overestimated observed differences. In addition, this study was based on a population of children with at least 1 parent serving in the military, and these results may differ for a population of children of civilian parents. Our analyses were cross-sectional, and we cannot make any statements about the causal impact of universal health insurance on racial and ethnic disparities in the MHS or the causal impact of asthma medications and specialist visits on PAH and ED outcomes. Finally, we had no data on home environments and characteristics of the health care providers seen, which may have contributed to the differences we observed.

Even with these limitations, our study provides critical information about the presence of racial and ethnic disparities among a diverse population of children enrolled in a national health insurance system. Our findings suggest that eliminating racial and ethnic disparities in health care likely requires a multifaceted approach beyond universal health insurance coverage.

Correspondence: Kate A. Stewart, PhD, Mathematica Policy Research, Inc, 111 E Wacker Dr, Ste 920, Chicago, IL 60601 (kstewart@mathematica-mpr.com).

Accepted for Publication: January 27, 2010.

Published Online: June 7, 2010 (doi:10.1001/archpediatrics.2010.100).

Author Contributions: Drs Stewart and McLaughlin had full access to all of the data in this study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Stewart, Higgins, McLaughlin, Williams, and Croghan. Acquisition of data: Stewart, Williams, Granger, and Croghan. Analysis and interpretation of data: Stewart, Higgins, McLaughlin, Williams, Granger, and Croghan. Drafting of the manuscript: Stewart and Higgins. Critical revision of the manuscript for important intellectual content: Stewart, Higgins, McLaughlin, Williams, Granger, and Croghan. Statistical analysis: Stewart and McLaughlin. Obtained funding: McLaughlin and Croghan. Administrative, technical, and material support: Williams and Granger. Study supervision: McLaughlin, Williams, Granger, and Croghan.

Financial Disclosure: None reported.

Funding/Support: The analyses on which this article is based were performed under contract 233-02-0086/HHSP233200700006T funded by the US Department of Defense.

Role of the Sponsor: The US Department of Defense reviewed and approved the use of its data for this work and approved submission of the manuscript.

Disclaimer: The content of this article does not necessarily reflect the views or policies of the US Department of Defense, nor does mention of commercial products imply endorsement by the US government.

Previous Presentation: This work was presented in part at the AcademyHealth Annual Research Meeting; June 23, 2009; Chicago, Illinois.

Starfield  BShi  L The medical home, access to care, and insurance: a review of evidence. Pediatrics 2004;113 (5) ((suppl)) 1493- 1498
PubMed
Beal  AC Policies to reduce racial and ethnic disparities in child health and health care. Health Aff (Millwood) 2004;23 (5) 171- 179
PubMed
Cooper  LAHill  MNPowe  NR Designing and evaluating interventions to eliminate racial and ethnic disparities in health care. J Gen Intern Med 2002;17 (6) 477- 486
PubMed
McWilliams  JMMeara  EZaslavsky  AMAyanian  JZ Differences in control of cardiovascular disease and diabetes by race, ethnicity, and education: US trends from 1999 to 2006 and effects of Medicare coverage. Ann Intern Med 2009;150 (8) 505- 515
PubMed
Sehgal  AR Universal health care as a health disparity intervention. Ann Intern Med 2009;150 (8) 561- 562
PubMed
Shone  LPDick  AWKlein  JDZwanziger  JSzilagyi  PG Reduction in racial and ethnic disparities after enrollment in the State Children's Health Insurance Program. Pediatrics 2005;115 (6) e697- e705
PubMed
Institute of Medicine, America's Uninsured Crisis: Consequences for Health and Health Care.  Washington, DC Institute of Medicine2009;
Task Force on the Future of Military Health Care, Department of Defense, Task Force on the Future of Military Health Care Final Report.  Washington, DC Department of Defense2007;
Akinbami  LJMoorman  JEGarbe  PLSondik  EJ Status of childhood asthma in the United States, 1980-2007. Pediatrics 2009;123 ((suppl 3)) S131- S145
PubMed
Centers for Disease Control and Prevention, Early release of selected estimates based on data from the 2008 National Health Interview Survey. http://www.cdc.gov/nchs/data/nhis/earlyrelease/200809_15.pdf. Accessed March 19, 2009
Flores  GTomany-Korman  SC Racial and ethnic disparities in medical and dental health, access to care, and use of services in US children. Pediatrics 2008;121 (2) e286- e298
PubMed10.1542/peds.2007-1243
Moorman  JERudd  RAJohnson  CA  et al. Centers for Disease Control and Prevention, National surveillance for asthma: United States, 1980-2004. MMWR Surveill Summ 2007;56 (8) 1- 54
PubMed
McDaniel  MPaxson  CWaldfogel  J Racial disparities in childhood asthma in the United States: evidence from the National Health Interview Survey, 1997 to 2003. Pediatrics 2006;117 (5) e868- e877
PubMed
Kruse  LKDeshpande  SVezina  M Disparities in asthma hospitalizations among children seen in the emergency department. J Asthma 2007;44 (10) 833- 837
PubMed
Stingone  JAClaudio  L Disparities in the use of urgent health care services among asthmatic children. Ann Allergy Asthma Immunol 2006;97 (2) 244- 250
PubMed
Agency for Healthcare Research and Quality, National Healthcare Disparities Report.  Washington, DC Agency for Healthcare Research and Quality2007;204
Adams  RJFuhlbrigge  AFinkelstein  JA  et al.  Impact of inhaled anti-inflammatory therapy on hospitalization and emergency department visits for children with asthma. Pediatrics 2001;107 (4) 706- 711
PubMed
Bacharier  LBBoner  ACarlsen  K-H  et al. European Pediatric Asthma Group, Diagnosis and treatment of asthma in childhood: a PRACTALL consensus report. Allergy 2008;63 (1) 5- 34
PubMed
McDonald  KRomano  PDavies  S  et al.  Measures of pediatric health care quality based on hospital administrative data: the pediatric quality indicators. http://www.qualityindicators.ahrq.gov/downloads/pdi/pdi_measures_v31.pdf. Accessed April 2, 2009
TRICARE Management Activity, Health Care Survey of DoD Beneficiaries. http://www.tricare.mil/survey/hcsurvey/default.cfm. Accessed April 2, 2009
Agency for Healthcare Research and Quality, AHRQ Pediatric Quality Indicators Overview.  Rockville, MD Agency for Healthcare Research and Quality2006;
National Heart, Lung, and Blood Institute; National Asthma Education and Prevention Program, Expert panel report 3: guidelines for the diagnosis and management of asthma: full report 2007. http://www.nhlbi.nih.gov/guidelines/asthma/asthgdln.pdf. Accessed April 2, 2009
Fishman  PAShay  DK Development and estimation of a pediatric chronic disease score using automated pharmacy data. Med Care 1999;37 (9) 874- 883
PubMed
Ai  CNorton  EC Interaction terms in logit and probit models. Econ Lett 2003;80123- 129
Norton  ECWang  HAi  C Computing interaction effects and standard errors in logit and probit models. Stata J 2004;4 (2) 154- 167
Diette  GBSkinner  EANguyen  TTHMarkson  LClark  BDWu  AW Comparison of quality of care by specialist and generalist physicians as usual source of asthma care for children. Pediatrics 2001;108 (2) 432- 437
PubMed
Finkelstein  JALozano  PFarber  HJMiroshnik  ILieu  TA Underuse of controller medications among Medicaid-insured children with asthma. Arch Pediatr Adolesc Med 2002;156 (6) 562- 567
PubMed
Butz  AMTsoukleris  MDonithan  M  et al.  Patterns of inhaled antiinflammatory medication use in young underserved children with asthma. Pediatrics 2006;118 (6) 2504- 2513
PubMed
Schatz  MZeiger  RSMosen  D  et al.  Improved asthma outcomes from allergy specialist care: a population-based cross-sectional analysis. J Allergy Clin Immunol 2005;116 (6) 1307- 1313
PubMed
Vollmer  WMO’Hollaren  MEttinger  KM  et al.  Specialty differences in the management of asthma: a cross-sectional assessment of allergists' patients and generalists' patients in a large HMO. Arch Intern Med 1997;157 (11) 1201- 1208
PubMed
Smedley  BDedStith  AYedNelson  ARed Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care.  Washington, DC Institute of Medicine2002;
Agency for Healthcare Research and Quality, National Healthcare Disparities Report 2007.  Rockville, MD Agency for Healthcare Research and Quality2008;AHRQ publication 08-0041
Herrod  HGChang  CF Potentially avoidable pediatric hospitalizations as defined by the Agency for Healthcare Research and Quality: what do they tell us about disparities in child health? Clin Pediatr (Phila) 2008;47 (2) 128- 136
PubMed
Forester  JPOng  BAFallot  A Can equal access to care eliminate racial disparities in pediatric asthma outcomes? J Asthma 2008;45 (3) 211- 214
PubMed
US Environmental Protection Agency, Indoor environmental asthma triggers. http://www.epa.gov/asthma/triggers.html. Accessed March 19, 2009
Centers for Disease Control and Prevention, Asthma. http://www.cdc.gov/asthma/faqs.htm#triggers. Accessed March 19, 2009
Bray  RMHourani  LL Substance use trends among active duty military personnel: findings from the United States Department of Defense Health Related Behavior Surveys, 1980-2005. Addiction 2007;102 (7) 1092- 1101
PubMed
Burchard  EGZiv  ECoyle  N  et al.  The importance of race and ethnic background in biomedical research and clinical practice. N Engl J Med 2003;348 (12) 1170- 1175
PubMed

Figures

Tables

Table Graphic Jump LocationTable 1. Demographic and Military-Related Characteristics Among the Full Cohort of Children and Children With Asthma
Table Graphic Jump LocationTable 2. Asthma Prevalence, Outcomes, and Treatments by Race and Ethnicitya
Table Graphic Jump LocationTable 3. Odds Ratios and 95% Confidence Intervals From Logistic Regression Models by Age for Diagnosed Asthma, Asthma-Related Outcomes, and Treatments

References

Starfield  BShi  L The medical home, access to care, and insurance: a review of evidence. Pediatrics 2004;113 (5) ((suppl)) 1493- 1498
PubMed
Beal  AC Policies to reduce racial and ethnic disparities in child health and health care. Health Aff (Millwood) 2004;23 (5) 171- 179
PubMed
Cooper  LAHill  MNPowe  NR Designing and evaluating interventions to eliminate racial and ethnic disparities in health care. J Gen Intern Med 2002;17 (6) 477- 486
PubMed
McWilliams  JMMeara  EZaslavsky  AMAyanian  JZ Differences in control of cardiovascular disease and diabetes by race, ethnicity, and education: US trends from 1999 to 2006 and effects of Medicare coverage. Ann Intern Med 2009;150 (8) 505- 515
PubMed
Sehgal  AR Universal health care as a health disparity intervention. Ann Intern Med 2009;150 (8) 561- 562
PubMed
Shone  LPDick  AWKlein  JDZwanziger  JSzilagyi  PG Reduction in racial and ethnic disparities after enrollment in the State Children's Health Insurance Program. Pediatrics 2005;115 (6) e697- e705
PubMed
Institute of Medicine, America's Uninsured Crisis: Consequences for Health and Health Care.  Washington, DC Institute of Medicine2009;
Task Force on the Future of Military Health Care, Department of Defense, Task Force on the Future of Military Health Care Final Report.  Washington, DC Department of Defense2007;
Akinbami  LJMoorman  JEGarbe  PLSondik  EJ Status of childhood asthma in the United States, 1980-2007. Pediatrics 2009;123 ((suppl 3)) S131- S145
PubMed
Centers for Disease Control and Prevention, Early release of selected estimates based on data from the 2008 National Health Interview Survey. http://www.cdc.gov/nchs/data/nhis/earlyrelease/200809_15.pdf. Accessed March 19, 2009
Flores  GTomany-Korman  SC Racial and ethnic disparities in medical and dental health, access to care, and use of services in US children. Pediatrics 2008;121 (2) e286- e298
PubMed10.1542/peds.2007-1243
Moorman  JERudd  RAJohnson  CA  et al. Centers for Disease Control and Prevention, National surveillance for asthma: United States, 1980-2004. MMWR Surveill Summ 2007;56 (8) 1- 54
PubMed
McDaniel  MPaxson  CWaldfogel  J Racial disparities in childhood asthma in the United States: evidence from the National Health Interview Survey, 1997 to 2003. Pediatrics 2006;117 (5) e868- e877
PubMed
Kruse  LKDeshpande  SVezina  M Disparities in asthma hospitalizations among children seen in the emergency department. J Asthma 2007;44 (10) 833- 837
PubMed
Stingone  JAClaudio  L Disparities in the use of urgent health care services among asthmatic children. Ann Allergy Asthma Immunol 2006;97 (2) 244- 250
PubMed
Agency for Healthcare Research and Quality, National Healthcare Disparities Report.  Washington, DC Agency for Healthcare Research and Quality2007;204
Adams  RJFuhlbrigge  AFinkelstein  JA  et al.  Impact of inhaled anti-inflammatory therapy on hospitalization and emergency department visits for children with asthma. Pediatrics 2001;107 (4) 706- 711
PubMed
Bacharier  LBBoner  ACarlsen  K-H  et al. European Pediatric Asthma Group, Diagnosis and treatment of asthma in childhood: a PRACTALL consensus report. Allergy 2008;63 (1) 5- 34
PubMed
McDonald  KRomano  PDavies  S  et al.  Measures of pediatric health care quality based on hospital administrative data: the pediatric quality indicators. http://www.qualityindicators.ahrq.gov/downloads/pdi/pdi_measures_v31.pdf. Accessed April 2, 2009
TRICARE Management Activity, Health Care Survey of DoD Beneficiaries. http://www.tricare.mil/survey/hcsurvey/default.cfm. Accessed April 2, 2009
Agency for Healthcare Research and Quality, AHRQ Pediatric Quality Indicators Overview.  Rockville, MD Agency for Healthcare Research and Quality2006;
National Heart, Lung, and Blood Institute; National Asthma Education and Prevention Program, Expert panel report 3: guidelines for the diagnosis and management of asthma: full report 2007. http://www.nhlbi.nih.gov/guidelines/asthma/asthgdln.pdf. Accessed April 2, 2009
Fishman  PAShay  DK Development and estimation of a pediatric chronic disease score using automated pharmacy data. Med Care 1999;37 (9) 874- 883
PubMed
Ai  CNorton  EC Interaction terms in logit and probit models. Econ Lett 2003;80123- 129
Norton  ECWang  HAi  C Computing interaction effects and standard errors in logit and probit models. Stata J 2004;4 (2) 154- 167
Diette  GBSkinner  EANguyen  TTHMarkson  LClark  BDWu  AW Comparison of quality of care by specialist and generalist physicians as usual source of asthma care for children. Pediatrics 2001;108 (2) 432- 437
PubMed
Finkelstein  JALozano  PFarber  HJMiroshnik  ILieu  TA Underuse of controller medications among Medicaid-insured children with asthma. Arch Pediatr Adolesc Med 2002;156 (6) 562- 567
PubMed
Butz  AMTsoukleris  MDonithan  M  et al.  Patterns of inhaled antiinflammatory medication use in young underserved children with asthma. Pediatrics 2006;118 (6) 2504- 2513
PubMed
Schatz  MZeiger  RSMosen  D  et al.  Improved asthma outcomes from allergy specialist care: a population-based cross-sectional analysis. J Allergy Clin Immunol 2005;116 (6) 1307- 1313
PubMed
Vollmer  WMO’Hollaren  MEttinger  KM  et al.  Specialty differences in the management of asthma: a cross-sectional assessment of allergists' patients and generalists' patients in a large HMO. Arch Intern Med 1997;157 (11) 1201- 1208
PubMed
Smedley  BDedStith  AYedNelson  ARed Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care.  Washington, DC Institute of Medicine2002;
Agency for Healthcare Research and Quality, National Healthcare Disparities Report 2007.  Rockville, MD Agency for Healthcare Research and Quality2008;AHRQ publication 08-0041
Herrod  HGChang  CF Potentially avoidable pediatric hospitalizations as defined by the Agency for Healthcare Research and Quality: what do they tell us about disparities in child health? Clin Pediatr (Phila) 2008;47 (2) 128- 136
PubMed
Forester  JPOng  BAFallot  A Can equal access to care eliminate racial disparities in pediatric asthma outcomes? J Asthma 2008;45 (3) 211- 214
PubMed
US Environmental Protection Agency, Indoor environmental asthma triggers. http://www.epa.gov/asthma/triggers.html. Accessed March 19, 2009
Centers for Disease Control and Prevention, Asthma. http://www.cdc.gov/asthma/faqs.htm#triggers. Accessed March 19, 2009
Bray  RMHourani  LL Substance use trends among active duty military personnel: findings from the United States Department of Defense Health Related Behavior Surveys, 1980-2005. Addiction 2007;102 (7) 1092- 1101
PubMed
Burchard  EGZiv  ECoyle  N  et al.  The importance of race and ethnic background in biomedical research and clinical practice. N Engl J Med 2003;348 (12) 1170- 1175
PubMed

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