Abstract
Objective
To compare asthma care quality for children with and without minority-serving providers.
Design
Cross-sectional telephone survey of parents, linked with a mailed survey of their children’s providers.
Setting
A Medicaid-predominant health plan and multispecialty provider group in Massachusetts.
Participants
Children with persistent asthma identified from claims and encounter data.
Main Exposure
Whether the child’s provider was minority-serving (>25% of patients black or Latino).
Outcomes
Parent report of whether the child had: 1) ever received inhaled steroids; 2) received influenza vaccination during the past season and 3) received an asthma action plan in the past year.
Results
The study included 563 children. In unadjusted analyses, Latino children and those with minority-serving providers were more likely to have never received inhaled steroids. In adjusted models, the odds of never receiving inhaled steroids were not significantly different for children with minority-serving providers (OR 1.29, 95% CI 0.63–2.64), or for Latino vs. white children (OR 1.76, 95% CI 0.74–4.18); odds were increased for children receiving care in community health centers (OR 4.88, 95% CI 1.70–14.02) or hospital clinics (OR 4.53, 95% CI 1.09–18.92) vs. multi-specialty practices. Such differences were not seen for influenza vaccinations or action plans.
Conclusions
Children with persistent asthma were less likely to receive inhaled steroids if they received care in community health centers or hospital clinics. Practice setting mediated initially-observed disparities in inhaled steroid use by Latino children and those with minority-serving providers. No differences by race/ethnicity or minority-serving provider were observed for influenza vaccinations and asthma action plans.
BACKGROUND
Health care for minority patients has been shown to be concentrated among a sub-set of providers. Minority patients are more likely to receive care from community health centers and academic institutions, and from providers who are foreign medical graduates, non-physician clinicians, or not board certified.1–4 Data from adult populations suggest that racial/ethnic disparities in health care quality are driven in part by differences between providers.5, 6 Data are mixed as to whether differences are due to factors associated with having a minority-serving provider, such as provider characteristics or practice setting,7 or due to an independent association between quality and the proportion of minority patients in a practice.8, 9 Possible explanations for the latter are that providers who serve larger minority patient populations encounter more complex medical and social issues, language barriers, and lower health literacy.4,10 While most studies in this area have been in adult populations, there is some evidence that suggests that minority infants are more likely to receive care at underperforming hospitals. However, data for pediatric care in the ambulatory setting are lacking.11
Asthma is one of the most common chronic diseases of children, and racial/ethnic disparities have been well documented in childhood asthma treatment and outcomes.12–14 Guidelines for the outpatient management of children with persistent asthma recommend daily inhaled steroid use, yearly influenza vaccination, and use of asthma action plans.15 However, minority children are often less likely to receive these services.12, 16–18 A number of studies have explored the relationship of race/ethnicity and other patient and provider-level factors to asthma care,16, 19–22 including one where providers with large proportions of minority patients were less likely to report prescribing daily inhaled steroid use, even after controlling for practice type.23 However, more data is needed to evaluate the role of having a minority-serving provider on quality of asthma care in the context of associated patient, provider, and practice setting characteristics.
Thus, this study’s objectives were to examine whether children with and without minority-serving providers received asthma care of similar quality, as measured by receipt of inhaled steroids, influenza vaccination, and asthma action plans.
METHODS
Study Design and Setting
This was a cross-sectional study using linked parent and provider survey data on children with asthma in two health care systems: Harvard Vanguard Medical Associates (HVMA), a large multispecialty group practice in the Boston metropolitan area with privately-insured and Medicaid-insured patients, and Neighborhood Health Plan (NHP), a Medicaid-predominant health plan in Massachusetts. The study was approved by the institutional review boards of Harvard Pilgrim Health Care and Boston University School of Medicine.
Study population
The study included children aged 2 to 12 years with persistent asthma. Eligible children were identified from computerized claims and electronic medical records based on an algorithm modeled on Health Employer Data Information Set (HEDIS) criteria for persistent asthma.24 Children were included if they had a clinical encounter with an ICD-9 code for asthma for an emergency department (ED) visit, a hospitalization, or two outpatient visits, plus any one of the following during the prior 12-months: 1) ≥ 4 asthma medication dispensings; 2) ≥ 1 emergency department visit or hospitalization for asthma; or 3) ≥ 4 outpatient visits with asthma as the primary diagnosis and ≥2 prescriptions for asthma medications. Children were excluded if we did not have a completed survey from their asthma care provider.
Data collection
Parent survey
Parents of eligible children were surveyed by telephone in English or Spanish between March 2005 and March 2006 using a structured, closed-ended 30-minute interview. If parents did not respond after 12 telephone attempts, a mailed version of the survey in English or Spanish was sent.
Provider survey
We sought to identify the non-specialist physician or advanced practice clinician who was the child’s primary asthma care provider by asking in the parent survey for the name of the provider most in charge of the child’s asthma care. If this did not yield a valid response, we used the provider identified in computerized data as the child’s primary care provider.
Eligible providers were mailed a structured, closed-ended survey in November 2005, with two additional mailing attempts for non-responders. Providers were asked questions about their prescribing patterns for patients with asthma in addition to questions about themselves and their practices (described below).
Data from each provider’s survey was linked to parent survey data for each child for whom that provider was the primary asthma care provider.
Measures
Outcome variables
The primary outcome variables were three measures of recommended care for children with persistent asthma that are consistent with national guidelines: receipt of inhaled steroids, asthma action plans, and influenza vaccination.15 We measured receipt of inhaled steroids and asthma action plans by parent report. Receipt of inhaled steroids was defined as report of current use of inhaled steroids or a “yes” response to the question of whether a provider had ever recommended that the child take a daily inhaled steroid. Receipt of asthma action plans was defined as “yes” responses to two questions: whether the child’s doctor had given them a written treatment plan in the past 12 months for the child’s asthma, and whether this plan told ways to tell how severe an asthma flare-up was, such as green, yellow, and red zones. We measured receipt of influenza vaccination from parent report or electronic records indicating influenza vaccination in the prior season.
Predictor variables
The primary predictors of interest in this study were the child’s race/ethnicity as reported by the parent and whether the child received asthma care from a minority-serving provider. The child’s race/ethnicity was categorized as white, black, Latino, or multi/other (children with more than one race or other races). If the parent reported the child’s ethnicity as Latino, the child was categorized as Latino regardless of race. The providers were categorized as minority-serving if they reported in the provider survey that more than 25% of their patient population was black or more than 25% of their patient population was Latino.
Other child-level co-variates of interest included age, family income as a percent of the Federal Poverty Level (FPL), parental education, whether the child lived in a single parent household, and insurance type. To adjust for asthma morbidity, we used computerized data from the prior year to measure whether the child had any asthma-related ED use or hospitalizations, and to determine the number of bronchodilator and oral steroid prescriptions filled.
Other provider-level co-variates included the provider’s self-reported race/ethnicity, number of years in practice, practice type, and whether > 25% of the provider’s patients had Medicaid insurance or were uninsured.
Analyses
We conducted bivariate analyses using chi square tests to evaluate whether child and provider-level characteristics were associated with the asthma care outcomes of interest (never receiving inhaled steroids, no influenza vaccination in the prior season, and no asthma action plan in the past 12 months).
We conducted separate multivariate analyses for each of the three outcomes of interest, modeling the odds of never receiving inhaled steroids, of not receiving an influenza vaccination, and of not receiving an asthma action plan. Models included patient and provider-level covariates that were associated with the outcome at p < 0.10 in bivariate analyses, with the primary predictors of interest (child race/ethnicity and minority-serving provider) forced into the models. When there was a significant bivariate association between race/ethnicity and one of the outcomes, we assessed the mediating effects of other co-variates with an iterative, forced-entry modeling approach. The unadjusted first-stage model evaluated the association between race/ethnicity and the outcome of interest. Next, in the second stage model, patient-level co-variates were added to the model if they were associated with the outcome at p < 0.10 in bivariate analyses. In the third stage model, minority-serving provider was forced into the model. Lastly, in the final model, provider-level covariates were added if they were associated with the outcome at p < 0.10 in bivariate analyses. All multivariate analyses were done using generalized linear mixed models to account for clustering of children within providers.
RESULTS
Of 1,047 eligible parents, 754 completed the parent survey, for a response rate of 72%. Of these, 89% were completed by phone in English, 3% by phone in Spanish, and 8% by mail. Of 344 eligible providers, 251 completed the provider survey, for a response rate of 73%. Completed and linked parent and provider surveys were available for 563 children and 138 providers. The number of children per provider in the final study sample ranged from 1 to 32, with a median of 2 children per provider. Based on data from the parent survey, there were no statistically significant differences in terms of race/ethnicity, income, parent education, and single parent household, between children in the study sample and those excluded because they lacked linked provider data.
Of the 563 children in our study, 45% were white, 22% were black, 19% were Latino, and 14% were multiple/other races (Table 1). The 76 children with multiple/other races included children who were Asian (35) or Native American (1), or had multiple (31) or other races (9). Twenty-one percent had family incomes below the poverty level, 25% had parents with a high school education or less, 32% came from single-parent households, and 27% had insurance coverage from Medicaid. Fifty percent of children in our sample had minority-serving providers. Our study population differs somewhat from the general population of children in Massachusetts of which 74% are white, 9% are black, 10% are Latino, 19% are below the poverty level, and 24% have Medicaid coverage.25
Table 1.
Characteristics of Study Population
| Patient-level characteristics | Percent |
|---|---|
| Child’s race/ethnicity | |
| White | 44.9 |
| Black | 22.4 |
| Latino | 19.2 |
| Multi/Other | 13.5 |
|
| |
| Child’s age in years | |
| <5 | 24.0 |
| 5–9 | 51.2 |
| 10–13 | 24.9 |
|
| |
| Income | |
| <100% FPL | 21.4 |
| 100–199% FPL | 18.1 |
| ≥200% FPL | 60.5 |
|
| |
| Parent education ≤ high school | 25.3 |
|
| |
| Single parent household | 32.3 |
|
| |
| Child’s insurance type | |
| Medicaid | 27.4 |
| Private | 72.7 |
|
| |
| ED visit | 16.3 |
|
| |
| Hospitalization | 7.6 |
|
| |
| Bronchodilator fills | |
| 0 | 12.8 |
| 1 | 20.3 |
| 2 | 21.1 |
| 3 | 15.8 |
| 4 | 30.0 |
|
| |
| Systemic steroid fills | |
| 0 | 52.2 |
| 1 | 24.0 |
| 2 | 23.8 |
|
| |
| Minority-serving provider* | 50.1 |
|
| |
| Provider race/ethnicity | |
| White | 75.8 |
| Black | 8.0 |
| Latino | 6.2 |
| Asian | 10.0 |
|
| |
| Provider years in practice | |
| < 10 | 4.2 |
| 10–20 | 20.4 |
| > 20 | 75.5 |
|
| |
| Provider practice type | |
| Health center | 13.2 |
| Hospital clinic | 3.6 |
| Multi-specialty group | 72.6 |
| Single-specialty/solo practice | 10.6 |
|
| |
| > 25% of provider’s patients have Medicaid or are uninsured | 46.6 |
> 25% of provider’s patients are Black or Hispanic.
Minority children tended to receive asthma care from different sources than white children. Care for minority children was concentrated among minority-serving providers, with 79% of black children and 69% of Latino children having a minority-serving provider, while only 29% of white children did (p= < 0.001). Latino and black children were more likely to receive care from providers at community health centers (33% and 14%, respectively) than white children (4%), and Latino children were less likely to receive care at multi-specialty group practices compared to black and white children (55% vs. 77% vs. 78%, respectively) (p<0.0001).
Bivariate analyses
Twenty-three percent of Latino children had never received inhaled steroids, compared to 11% of black children and 10% of white children (p=0.004). Children with minority-serving providers were more likely to have never received inhaled steroids than children whose providers were not minority-serving (17% vs. 11%, respectively; p=0.034). Children had greater likelihood of never receiving inhaled steroids if their provider practiced in a community health center (36%) or hospital clinic (26%) than in a single-specialty/solo practice (12%) or multi-specialty group practice (9%) (p<0.001).
The percent of children who did not receive an influenza vaccination in the prior year did not vary by their race/ethnicity or by having a minority-serving provider. Likewise, the percent who had not received an asthma action plan did not vary by race/ethnicity or by having a minority-serving provider.
Multivariate analyses
We used a series of multivariate models to assess whether racial/ethnic variation in receipt of inhaled steroids was mediated by having a minority-serving provider and other patient and provider-level factors (Table 3). In the unadjusted model, Latino children had significantly greater odds of never receiving inhaled steroids compared to white children (OR 2.64, 95% CI 1.42–4.94), a finding that persisted after adjusting for other patient-level co-variates in the second-stage model (OR 2.35, 95% CI 1.09–5.09). However, when having a minority-serving provider was added as a co-variate in the third-stage model, Latino children no longer had significantly increased odds of never receiving inhaled steroids (OR 1.89, 95% CI 0.84–4.28). In this model, the odds of never receiving inhaled steroids were not significantly different for children with minority-serving providers compared to children with other providers (OR 1.90, 95% CI 0.98–3.70). When remaining provider-level variables were added, the model would not converge due to correlation between variables for having a minority-serving provider and having a provider with >25% of patients with Medicaid/uninsured, so the latter variable was excluded. In the final model, with provider practice type added, the odds ratio for having a minority-serving provider was reduced to 1.29 (95% CI 0.63–2.64). Provider practice type was significantly associated with never receiving inhaled steroids, with increased odds for children whose provider practiced at a health center (OR 4.88, 95% CI 1.70–14.02) or hospital clinic (OR 4.53, 95% CI 1.09–18.92) compared to a multi-specialty group practice. This sequence of results suggests that the initially-observed associations of inhaled steroid use with patient race/ethnicity and minority-serving provider were largely mediated by the practice setting.
Table 3.
Characteristics associated with never receiving inhaled steroids
| Odds of never receiving inhaled steroids (95% CI)
|
||
|---|---|---|
| Unadjusted model | Final model | |
| Patient-level characteristics | ||
|
| ||
| Race/ethnicity | ||
| White | Ref | Ref |
| Black | 1.10 (0.53–2.29) | 1.07 (0.43–2.66) |
| Latino | 2.64 (1.42–4.94) | 1.76 (0.74–4.18) |
| Multi/other | 2.28 (1.12–4.62) | 1.62 (0.66–3.99) |
|
| ||
| Income | ||
| <100% FPL | 0.86 (0.31–2.30) | |
| 100–199% FPL | 0.85 (0.35–2.06) | |
| ≥ 200% | Ref | |
|
| ||
| Parental education ≤high school | 2.30 (1.18–4.84) | |
|
| ||
| Medicaid insurance (vs. private) | 0.78 (0.29–2.10) | |
|
| ||
| Bronchodilator fills | ||
| 0 | Ref | |
| 1 | 0.50 (0.22–1.15) | |
| 2 | 0.37 (0.16–0.88) | |
| 3 | 0.25 (0.08–0.73) | |
| 4 | 0.13 (0.05–0.35) | |
|
| ||
| Systemic steroid fills | ||
| 0 | Ref | |
| 1 | 0.28 (0.12–0.70) | |
| 2 | 0.44 (0.18–1.04) | |
|
| ||
| Provider-level characteristics | ||
|
| ||
| Minority-Serving Provider* | 1.29 (0.63–2.64) | |
|
| ||
| Practice Type | ||
| Health center | 4.88 (1.70–14.02) | |
| Hospital clinic | 4.53 (1.09–18.92) | |
| Multi-specialty group | Ref | |
| Single-specialty/solo practice | 1.23 (0.46–3.29) | |
> 25% of provider’s patients are Black or Hispanic.
p< 0.05 in bold. Adjusted model controls for all variables listed.
As in bivariate analyses, our multivariate models indicated no significant differences in receipt of influenza vaccinations or asthma action plans by race/ethnicity or by having a minority-serving provider. No significant association was observed between not receiving an influenza vaccination and either race/ethnicity or having a minority-serving provider, in a model that controlled for age, single parent household, and number of systemic steroid prescriptions dispensed (Table 4). For not receiving an asthma action plan, we also did not see a significant relationship with race/ethnicity or minority-serving provider in a model that controlled for age, insurance type, and number of bronchodilator fills (Table 4).
Table 4.
Characteristics associated with not receiving an influenza vaccination and with not receiving an action plan
| NOT RECEIVING INFLUENZA VACCINATION | Adjusted OR (95% CI) |
|---|---|
|
Patient-level characteristics
| |
| Race/ethnicity | |
| White | Ref |
| Black | 1.16 (0.66–2.02) |
| Latino | 1.30 (0.74–2.27) |
| Multi/other | 1.03 (0.55–1.90) |
|
| |
| Child’s age in years | |
| <5 | 0.33 (0.19–0.58) |
| 5–9 | 0.44 (0.28–0.69) |
| 10–13 | Ref |
|
| |
| Single parent household | 1.41 (0.93–2.14) |
|
| |
| Systemic steroid fills | |
| 0 | Ref |
| 1 | 0.43 (0.26–0.71) |
| 2 | 0.47 (0.29–0.77) |
|
| |
| Provider-level characteristics | |
|
| |
| Minority-Serving Provider* | 0.86 (0.56–1.32) |
| NOT RECEIVING ACTION PLAN | Adjusted OR (95% CI) |
|---|---|
|
Patient-level characteristics
| |
| Race/ethnicity | |
| White | Ref |
| Black | 0.70 (0.40–1.22) |
| Latino | 0.97 (0.56–1.69) |
| Multi/other | 1.21 (0.66–2.21) |
|
| |
| Child’s age in years | |
| <5 | 1.71 (0.99–2.96) |
| 5–9 | 1.72 (1.08–2.76) |
| 10–13 | Ref |
|
| |
| Medicaid insurance (vs. private) | 1.73 (1.09–2.74) |
|
| |
| Bronchodilator fills | |
| 0 | Ref |
| 1 | 0.66 (0.34–1.30) |
| 2 | 1.16 (0.60–2.24) |
| 3 | 1.00 (0.50–2.01) |
| 4 | 0.57 (0.30–1.06) |
|
| |
| Provider-level characteristics | |
|
| |
| Minority-Serving Provider* | 0.80 (0.49–1.30) |
> 25% of provider’s patients are Black or Hispanic.
p< 0.05 in bold. Each model controls for all variables listed.
DISCUSSION
Overall, this study did not find consistent differences in the quality of childhood asthma care delivered by minority-serving providers. Receipt of influenza vaccination and asthma action plans were similar for children with and without minority-serving providers. Children with persistent asthma were less likely to have ever been recommended inhaled steroids, based on parent report, if they received care from community health centers or hospital clinics. The practice setting appeared to mediate variation in receipt of inhaled steroids by patient race/ethnicity and whether the provider was minority-serving. Contrary to our original hypothesis, we did not find that having a minority-serving provider was independently associated with lower quality asthma care.
Our finding that racial/ethnic disparities in receipt of inhaled steroids were attenuated after adjusting for provider-level factors is consistent with studies in other populations that have shown that racial/ethnic disparities are driven in part by where minority children receive care.5, 6, 19, 26 Our results would suggest that for racial/ethnic disparities in inhaled steroid use, setting of care plays a more important role than having large numbers of minority patients itself. We did not find an independent association between quality of care and having a minority-serving provider, in contrast to other studies that focused on adult populations receiving care from minority-serving hospitals rather than minority-serving outpatient providers.8, 9 Additionally, our results may differ because our analyses controlled for patient-level socioeconomic and other variables, was conducted at the patient rather than provider level, and used process measures of quality rather than health outcomes. Variation across studies may be seen because being a minority-serving provider may be associated with measured and unmeasured characteristics related to practice type that can affect quality, such as, organizational structure and staffing, provider training, payer mix, geography and residential segregation, work environment, and the availability of health information technology and other resources.2, 4, 10, 29, 30 Practice-level factors, such as having policies to promote access and continuity and the use of reports to clinicians, have been shown to be associated with greater use of preventive asthma medications for children.21 Safety net practices serving large numbers of uninsured and Medicaid-insured patients may have fewer resources to devote to policies that promote adherence to guidelines.27,28 Because of the correlation between having large proportions of minority and Medicaid patients, we were unable to assess the adjusted association between having large proportions of Medicaid patients and receipt of inhaled steroids. However, other studies controlling for both have found that having a minority-serving provider remained significantly associated with lower quality.9
It is reassuring that we did not see differences by race/ethnicity and having a minority-serving provider for children’s receipt of influenza vaccinations and action plans. As seen in other studies, racial/ethnic disparities may be present for some services and not others.31 Although differences by practice type were noted for receipt of inhaled steroids, health centers and hospital clinics appear to provide the same level of quality as other practice types for influenza vaccinations and action plans. Prescribing inhaled steroids may be more a more complex and nuanced task that is subject to multiple provider and patient factors that differ across practice types, such as the extent of multiple competing medical and social issues, the availability of resources to support staff to conduct education and management about medications, the availability of translation services, or perceptions about adherence related to patient mix.
Policy implications
Our findings highlight a number of important policy issues related to quality improvement and the reduction of racial/ethnic disparities in asthma care for children. Our results show that disparities in quality may be not be present across all measures of asthma care, and that apparent disparities in some measures for minority children and those with minority-serving providers may be mediated by practice site factors. This suggests that a targeted approach to improving quality and reducing disparities may be warranted. For example, focusing on improvement of inhaled steroid use in community health centers and hospital clinics might be a way to improve quality generally and for minority children in particular. Although most minority children receive care in private or group practices, 30% of Black and 41% of Latino children receive care at community health centers,1 and minority children in our study and others1, 33 are more likely than white children to receive care in health centers and hospital clinics.
Debate continues over whether improvements in quality of care for racial/ethnic minorities are best achieved by efforts specifically targeting these populations and the places where they receive care,34 or whether broad-based quality improvement efforts will improve care for racial/ethnic minorities and reduce disparities.35 Policies promoting pay-for-performance and public reporting will need to consider how rewards based on quality measures will affect providers in settings that serve minority children, and how such policies may indirectly affect racial/ethnic disparities.36–38 If baseline quality is lower for providers in settings that have disproportionate numbers of minority children, these providers could be penalized in pay-for-performance or public reporting programs through decreases in revenue or patient volume.
Limitations
Our study population was drawn from a Medicaid-predominant health plan and a multispecialty provider group in Massachusetts, so our findings about quality of asthma care for minority children may not be generalizable to other populations in other areas with different racial/ethnic composition, practice patterns, and health care systems. Although we controlled for a number of important patient and provider-level factors in assessing asthma care processes, we could not assess the effects of unmeasured provider-level factors such as training, cultural competence, technological resources, or availability of care management programs. Provider-level factors such as practice type may be correlated with unmeasured patient characteristics and provider-patient interactions in ways that could affect the quality outcomes studied. Our sample size was not large, leading to wide confidence intervals in some of our findings. Despite this, we were able to detect statistically significant results with confidence intervals encompassing clinically and policy-relevant differences. Relying on self-reported data is a limitation, and parents may not accurately recall when the provider had recommended or prescribed inhaled steroids or given them an asthma action plan. We attempted to capture provider behavior by asking about services that were provider-initiated (such as having inhaled steroids recommended or given), rather than parent-initiated (such as adherence). Our use of claims-based HEDIS measures to identify children with persistent asthma may have led us to include some children with mild intermittent asthma for whom inhaled steroids might appropriately not be recommended. If this were the case, we would expect higher rates of not receiving inhaled steroids for children whose asthma was erroneously identified as persistent. However, among children in our study sample who did not meet a more stringent criteria for persistent asthma (parent report of having > 4 days or > 1 nights with symptoms or > 4 days with Albuterol use in the past 2 weeks), rates of not receiving inhaled steroids were not significantly greater than for children meeting this more strict criteria for persistent asthma (14.7% vs.12.2%, respectively, p=0.402).
Conclusions
Children with persistent asthma were less likely to receive inhaled steroids if they received care in community health centers or hospital clinics. The practice setting appeared to mediate the initially-observed disparities in inhaled steroid use by children who were Latino or received care from minority-serving providers. Differences by setting of care, minority-serving provider, and race/ethnicity were not observed for influenza vaccination and asthma action plans. Based on the limited set of asthma measures studied, our findings do not support the hypothesis that minority-serving providers deliver lower-quality asthma care. However, efforts to enhance the consistency of inhaled steroid prescribing practices should consider focusing on settings such as community health centers and hospital clinics, which disproportionately serve minority children.
Table 2.
Relationship between asthma care quality measures and patient and provider characteristics
| Percent Not Receiving
|
||||||
|---|---|---|---|---|---|---|
| Inhaled steroids | p value | Influenza vaccination | p value | Action plan | p value | |
| Overall | 13.8 | 29.8 | 48.4 | |||
|
| ||||||
| Patient-level characteristics | ||||||
|
| ||||||
| Child’s race/ethnicity | ||||||
| White | 9.9 | 29.6 | 48.7 | |||
| Black | 10.5 | 0.004 | 30.2 | 0.996 | 40.2 | 0.150 |
| Latino | 22.6 | 30.6 | 51.5 | |||
| Multi/Other | 19.7 | 29.0 | 56.9 | |||
|
| ||||||
| Child’s age in years | ||||||
| <5 | 14.2 | 20.7 | 54.1 | |||
| 5–9 | 11.9 | 0.303 | 26.7 | <0.001 | 51.0 | 0.017 |
| 10–13 | 17.4 | 45.0 | 37.6 | |||
|
| ||||||
| Income | ||||||
| <100% FPL | 17.6 | 25.2 | 52.4 | |||
| 100–199% FPL | 17.0 | 0.087 | 36.2 | 0.231 | 48.2 | 0.589 |
| ≥200% FPL | 10.6 | 29.6 | 46.5 | |||
|
| ||||||
| Parent education | ||||||
| ≤ high school | 22.9 | <0.001 | 29.8 | 0.905 | 47.6 | 0.849 |
| > high school | 10.2 | 29.3 | 48.6 | |||
|
| ||||||
| Single parent household | ||||||
| Yes | 15.3 | 0.384 | 34.8 | 0.062 | 49.7 | 0.698 |
| No | 12.6 | 27.1 | 47.8 | |||
|
| ||||||
| Child’s insurance type | ||||||
| Medicaid | 21.9 | <0.001 | 26.0 | 0.219 | 56.4 | 0.026 |
| Private | 10.8 | 31.3 | 45.4 | |||
|
| ||||||
| ED visit | 11.0 | 0.396 | 25.0 | 0.267 | 41.0 | 0.137 |
| No ED visit | 14.4 | 30.8 | 49.9 | |||
|
| ||||||
| Hospitalization | 9.3 | 0.374 | 25.6 | 0.525 | 42.1 | 0.418 |
| No hospitalization | 14.2 | 30.2 | 48.9 | |||
|
| ||||||
| Bronchodilator fills | ||||||
| 0 | 29.6 | 29.2 | 55.6 | |||
| 1 | 17.5 | 35.1 | 42.9 | |||
| 2 | 12.0 | <0.001 | 33.6 | 0.248 | 56.5 | 0.021 |
| 3 | 11.2 | 30.3 | 55.6 | |||
| 4 | 7.2 | 23.7 | 39.9 | |||
|
| ||||||
| Systemic steroid fills | ||||||
| 0 | 19.3 | 37.1 | 51.2 | |||
| 1 | 8.2 | <0.001 | 22.2 | <0.001 | 46.5 | 0.439 |
| 2 | 7.5 | 21.6 | 44.7 | |||
|
| ||||||
| Provider-level characteristics | ||||||
|
| ||||||
| Minority-serving provider* | ||||||
| Yes | 16.9 | 0.034 | 29.4 | 0.832 | 46.1 | 0.289 |
| No | 10.7 | 30.3 | 50.8 | |||
|
| ||||||
| Provider race/ethnicity | ||||||
| White | 12.8 | 28.1 | 47.6 | |||
| Black | 9.3 | 0.173 | 45.5 | 0.072 | 57.5 | 0.468 |
| Latino | 17.7 | 38.2 | 54.8 | |||
| Asian | 22.6 | 27.3 | 42.9 | |||
|
| ||||||
| Provider years in practice | ||||||
| < 10 | 13.9 | 22.2 | 51.6 | |||
| 10–20 | 16.7 | 0.597 | 35.2 | 0.267 | 49.0 | 0.894 |
| > 20 | 12.9 | 28.9 | 47.6 | |||
|
| ||||||
| Provider practice type | ||||||
| Health center | 36.1 | 32.4 | 40.3 | |||
| Hospital clinic | 26.3 | <0.001 | 25.0 | 0.488 | 63.2 | 0.317 |
| Multi-specialty group | 9.4 | 31.0 | 49.2 | |||
| Single-specialty/solo | 11.9 | 22.0 | 47.3 | |||
|
| ||||||
| Percent of patients with | ||||||
| Medicaid/uninsured | ||||||
| >25% | 19.5 | 0.001 | 28.2 | 0.689 | 49.4 | 0.780 |
| ≤25% | 9.6 | 29.8 | 48.1 | |||
p < 0.05 in bold
> 25% of provider’s patients are Black or Hispanic.
Acknowledgments
We would like to thank Neighborhood Health Plan, Dr. Jack Lasche and Harvard Vanguard Medical Associates, and Dr. Pauline Sheehan for their collaboration and support of this work. We would also like to thank Ken Kleinman, ScD, from the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care, for assistance with the statistical models and helpful comments on the manuscript. We also greatly appreciate the contributions of our study’s research assistants.
This work was supported by a grant from the National Institute of Child Health and Human Development (grant R01 HD044070). Dr Bokhour’s effort was supported in part by the Department of Veterans Affairs, Health Services Research and Development Service. Dr. Sawicki’s effort was supported by an Agency for Healthcare Research and Quality grant (T32 HS000063-13) to the Harvard Pediatric Health Services Research Fellowship Program. Dr. Lieu’s effort was supported in part by a Mid-Career Investigator Award in Patient-Oriented Research from the National Institute of Child Health and Human Development (grant K24 HD047667). The above funders did not play a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Dr. Galbraith had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
References
- 1.Flores G, Olson L, Tomany-Korman SC. Racial and ethnic disparities in early childhood health and health care. Pediatrics. 2005;115(2):e183–193. doi: 10.1542/peds.2004-1474. [DOI] [PubMed] [Google Scholar]
- 2.Bach PB, Pham HH, Schrag D, Tate RC, Hargraves JL. Primary care physicians who treat blacks and whites. N Engl J Med. 2004 Aug 5;351(6):575–584. doi: 10.1056/NEJMsa040609. [DOI] [PubMed] [Google Scholar]
- 3.Grumbach K, Hart L, Mertz E, Coffman J, Palazzo L. Who is caring for the underserved? A comparison of primary care physicians and nonphysician clinicians in California and Washington. Ann Fam Med. 2003;1:97–104. doi: 10.1370/afm.49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Reschovsky JD, O’Malley AS. Do primary care physicians treating minority patients report problems delivering high-quality care? Health Aff (Millwood) 2008 May-Jun;27(3):w222–231. doi: 10.1377/hlthaff.27.3.w222. [DOI] [PubMed] [Google Scholar]
- 5.Hasnain-Wynia R, Baker DW, Nerenz D, et al. Disparities in Health Care Are Driven by Where Minority Patients Seek Care: Examination of the Hospital Quality Alliance Measures. Arch Intern Med. 2007 Jun 25;167(12):1233–1239. doi: 10.1001/archinte.167.12.1233. [DOI] [PubMed] [Google Scholar]
- 6.Barnato AE, Lucas FL, Staiger D, Wennberg DE, Chandra A. Hospital-level racial disparities in acute myocardial infarction treatment and outcomes. Med Care. 2005 Apr;43(4):308–319. doi: 10.1097/01.mlr.0000156848.62086.06. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mehta RH, Liang L, Karve AM, et al. Association of patient case-mix adjustment, hospital process performance rankings, and eligibility for financial incentives. Jama. 2008 Oct 22;300(16):1897–1903. doi: 10.1001/jama.300.16.1897. [DOI] [PubMed] [Google Scholar]
- 8.Skinner J, Chandra A, Staiger D, Lee J, McClellan M. Mortality After Acute Myocardial Infarction in Hospitals That Disproportionately Treat Black Patients. Circulation. 2005 Oct 25;112(17):2634–2641. doi: 10.1161/CIRCULATIONAHA.105.543231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Jha AK, Orav EJ, Zheng J, Epstein AM. The characteristics and performance of hospitals that care for elderly Hispanic Americans. Health Aff (Millwood) 2008 Mar-Apr;27(2):528–537. doi: 10.1377/hlthaff.27.2.528. [DOI] [PubMed] [Google Scholar]
- 10.Varkey AB, Manwell LB, Williams ES, et al. Separate and Unequal: Clinics Where Minority and Nonminority Patients Receive Primary Care. Arch Intern Med. 2009 Feb 9;169(3):243–250. doi: 10.1001/archinternmed.2008.559. [DOI] [PubMed] [Google Scholar]
- 11.Howell EA, Hebert P, Chatterjee S, Kleinman LC, Chassin MR. Black/white differences in very low birth weight neonatal mortality rates among New York City hospitals. Pediatrics. 2008 Mar;121(3):e407–415. doi: 10.1542/peds.2007-0910. [DOI] [PubMed] [Google Scholar]
- 12.Lieu TA, Lozano P, Finkelstein JA, et al. Racial/ethnic variation in asthma status and management practices among children in managed Medicaid. Pediatrics. 2002;109(5):857–865. doi: 10.1542/peds.109.5.857. [DOI] [PubMed] [Google Scholar]
- 13.Gupta RS, Carrion-Carire V, Weiss KB. The widening black/white gap in asthma hospitalizations and mortality. J Allergy Clin Immunol. 2006 Feb;117(2):351–358. doi: 10.1016/j.jaci.2005.11.047. [DOI] [PubMed] [Google Scholar]
- 14.Agency for Healthcare Research and Quality. [Accessed Feb 10, 2009];National Healthcare Disparities Report. 2007 http://www.ahrq.gov/qual/nhdr07/Chap4c.htm#children.
- 15.National Asthma Education and Prevention Program Expert Panel Report 3 (EPR-3) Guidelines for the diagnosis and management of asthma -- summary report 2007. J Allergy Clin Immunol. 2007;120:S94–S138. doi: 10.1016/j.jaci.2007.09.043. [DOI] [PubMed] [Google Scholar]
- 16.Finkelstein JA, Lozano P, Farber HJ, Miroshnik I, Lieu TA. Underuse of controller medications among Medicaid-insured children with asthma. Arch Pediatr Adolesc Med. 2002 Jun;156(6):562–567. doi: 10.1001/archpedi.156.6.562. [DOI] [PubMed] [Google Scholar]
- 17.Inkelas M, Garro N, McQuaid EL, Ortega AN. Race/ethnicity, language, and asthma care: findings from a 4-state survey. Ann Allergy Asthma Immunol. 2008 Feb;100(2):120–127. doi: 10.1016/S1081-1206(10)60420-6. [DOI] [PubMed] [Google Scholar]
- 18.Piper CN, Elder K, Glover S, Baek JD. Racial influences associated with asthma management among children in the United States. Ethn Dis. 2008 Spring;18(2):225–227. [PMC free article] [PubMed] [Google Scholar]
- 19.Finkelstein JA, Brown RW, Schneider LC, et al. Quality of care for preschool children with asthma: the role of social factors and practice setting. Pediatrics. 1995 Mar;95(3):389–394. [PubMed] [Google Scholar]
- 20.Yoos HL, Kitzman H, McMullen A. Barriers to anti-inflammatory medication use in childhood asthma. Ambul Pediatr. 2003 Jul-Aug;3(4):181–190. doi: 10.1367/1539-4409(2003)003<0181:btamui>2.0.co;2. [DOI] [PubMed] [Google Scholar]
- 21.Lieu TA, Finkelstein JA, Lozano P, et al. Cultural competence policies and other predictors of asthma care quality for Medicaid-insured children. Pediatrics. 2004;114(1):e102–110. doi: 10.1542/peds.114.1.e102. [DOI] [PubMed] [Google Scholar]
- 22.Smith LA, Bokhour B, Hohman KH, et al. Modifiable risk factors for suboptimal control and controller medication underuse among children with asthma. Pediatrics. 2008 Oct;122(4):760–769. doi: 10.1542/peds.2007-2750. [DOI] [PubMed] [Google Scholar]
- 23.Sawicki GS, Smith L, Bokhour B, et al. Periodic Use of Inhaled Steroids in Children With Mild Persistent Asthma: What Are Pediatricians Recommending? Clinical Pediatrics. 2008 Jun 1;47(5):446–451. doi: 10.1177/0009922807312184. [DOI] [PubMed] [Google Scholar]
- 24.National Committee for Quality Assurance. HEDIS 2003. Washington, DC: National Committee for Quality Assurance; 2003. [Google Scholar]
- 25.Kaiser Family Foundation. [Accessed June 17, 2009];Child Health Fact Sheets: Massachusetts and the United States. http://www.statehealthfacts.org/chfs.jsp?rgn=23&rgn=1.
- 26.Heisler M, Smith DM, Hayward RA, Krein SL, Kerr EA. Racial disparities in diabetes care processes, outcomes, and treatment intensity. Med Care. 2003 Nov;41(11):1221–1232. doi: 10.1097/01.MLR.0000093421.64618.9C. [DOI] [PubMed] [Google Scholar]
- 27.Pham HH, Schrag D, Hargraves JL, Bach PB. Delivery of preventive services to older adults by primary care physicians. Jama. 2005 Jul 27;294(4):473–481. doi: 10.1001/jama.294.4.473. [DOI] [PubMed] [Google Scholar]
- 28.Rust GS, Murray V, Octaviani H, et al. Asthma care in community health centers: a study by the southeast regional clinicians’ network. J Natl Med Assoc. 1999 Jul;91(7):398–403. [PMC free article] [PubMed] [Google Scholar]
- 29.McGinn J, Davis C. Geographic variation, physician characteristics, and diabetes care disparities in a metropolitan area, 2003–2004. Diabetes Research and Clinical Practice. 2006;72(2):162–169. doi: 10.1016/j.diabres.2005.10.023. [DOI] [PubMed] [Google Scholar]
- 30.Williams D, Collins C. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Reports. 2001;116:404–416. doi: 10.1093/phr/116.5.404. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Baicker K, Chandra A, Skinner JS, Wennberg JE. Who you are and where you live: how race and geography affect the treatment of medicare beneficiaries. Health Aff (Millwood) 2004;(Suppl Web Exclusives):VAR33–44. doi: 10.1377/hlthaff.var.33. [DOI] [PubMed] [Google Scholar]
- 32.Cabana MD, Chaffin DC, Jarlsberg LG, Thyne SM, Clark NM. Selective provision of asthma self-management tools to families. Pediatrics. 2008 Apr;121(4):e900–905. doi: 10.1542/peds.2007-1559. [DOI] [PubMed] [Google Scholar]
- 33.Forrest CB, Whelan EM. Primary care safety-net delivery sites in the United States: A comparison of community health centers, hospital outpatient departments, and physicians’ offices. JAMA. 2000 Oct 25;284(16):2077–2083. doi: 10.1001/jama.284.16.2077. [DOI] [PubMed] [Google Scholar]
- 34.Fisher TL, Burnet DL, Huang ES, Chin MH, Cagney KA. Cultural leverage: interventions using culture to narrow racial disparities in health care. Med Care Res Rev. 2007 Oct;64(5 Suppl):243S–282S. doi: 10.1177/1077558707305414. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Sehgal AR. Impact of quality improvement efforts on race and sex disparities in hemodialysis. Jama. 2003 Feb 26;289(8):996–1000. doi: 10.1001/jama.289.8.996. [DOI] [PubMed] [Google Scholar]
- 36.Casalino LP, Elster A, Eisenberg A, Lewis E, Montgomery J, Ramos D. Will pay-for-performance and quality reporting affect health care disparities? Health Aff (Millwood) 2007 May-Jun;26(3):w405–414. doi: 10.1377/hlthaff.26.3.w405. [DOI] [PubMed] [Google Scholar]
- 37.Chien AT, Chin MH, Davis AM, Casalino LP. Pay for performance, public reporting, and racial disparities in health care: how are programs being designed? Med Care Res Rev. 2007 Oct;64(5 Suppl):283S–304S. doi: 10.1177/1077558707305426. [DOI] [PubMed] [Google Scholar]
- 38.Werner RM, Goldman LE, Dudley RA. Comparison of change in quality of care between safety-net and non-safety-net hospitals. JAMA. 2008 May 14;299(18):2180–2187. doi: 10.1001/jama.299.18.2180. [DOI] [PubMed] [Google Scholar]