Racial and Ethnic Differences in Time to Acute Reperfusion Therapy for Patients Hospitalized With Myocardial Infarction FREE

Many studies have demonstrated different patterns of cardiovascular care by racial and ethnic groups,^1- 4 but few have investigated the relative contributions of sociodemographic, economic, clinical, or health system factors to these differences. Understanding the sources of racial and ethnic differences in cardiovascular care is paramount to designing effective interventions to eliminate disparities, which has been designated as a national priority.^5- 7 Therefore, studies are needed to examine the broad range of factors that might explain racial and ethnic differences in care.

Acute reperfusion for patients presenting with ST-segment elevation myocardial infarction (STEMI) provides a good opportunity to examine the interplay of patient and health system features and racial and ethnic differences in cardiovascular care. Prompt reperfusion markedly improves survival for patients with STEMI^8- 11 and is an indicator of quality of care used by the Centers for Medicare & Medicaid Services and the Joint Commission on Accreditation of Healthcare Organizations. Recent reports indicate that patients identified as African American/black or as nonwhite minority experience significantly longer times to fibrinolytic therapy (door-to-drug times) and percutaneous coronary intervention (PCI) (door-to-balloon times) than patients identified as white,^12- 15 raising concerns of health care disparities. However, existing studies have not comprehensively investigated the factors that explain or mediate the observed racial and ethnic differences in time to reperfusion therapy.

Accordingly, we used data from the National Registry of Myocardial Infarction (NRMI) 3 and 4¹⁶ and the American Hospital Association Survey of Hospitals¹⁷ to examine time to reperfusion therapy for patients with STEMI. We sought to characterize racial and ethnic differences in time between hospital arrival and receipt of reperfusion therapy, and we examined the role of sociodemographic factors, insurance status, clinical characteristics, and health system factors in explaining these differences. This information is essential for understanding possible reasons for differences in this key quality indicator and for formulating interventions that would support national efforts to eliminate racial and ethnic disparities in cardiovascular care.

We conducted a retrospective, observational study using admission and treatment data from a national cohort of patients with STEMI. The sample for this analysis comprised patients enrolled in the NRMI, an observational registry sponsored by Genentech Inc,^18- 19 who had STEMI or left bundle-branch block and who were hospitalized from January 1, 1999, through December 31, 2002, to receive acute reperfusion therapy with either fibrinolytic therapy or primary PCI. The Figure shows the sample selection process and specific exclusion criteria. We began with the 830 473 hospitalized patients who were enrolled in NRMI 3 or NRMI 4 and who met any of the following criteria for acute myocardial infarction (AMI): level of total creatine kinase or creatine kinase MB that was 2 or more times the upper limit of the reference range or elevations in alternative cardiac markers; electrocardiographic evidence of AMI; nuclear medicine testing, echocardiography, or autopsy evidence of AMI; or a diagnosis of AMI according to the International Classification of Diseases, Ninth Revision, Clinical Modification (code 410.X1). The diagnosis code 410.X1 was required for NRMI 4.

We then excluded patients who had neither ST-segment elevation (≥2 leads) nor left bundle-branch block on the first electrocardiogram to identify an ideal group for primary reperfusion therapy. From this group, we excluded patients who were transferred in from other hospitals as well as patients whose AMI symptom onset was after admission or who were missing data on symptom onset time and who had no chest pain present at admission. The percentage of patients missing data on symptom onset time did not vary by race/ethnicity. To focus on primary reperfusion, we then eliminated patients who either did not receive primary reperfusion with fibrinolytic therapy or PCI or who received reperfusion therapy more than 6 hours after hospital arrival.

We developed 2 cohorts based on whether the patient received fibrinolytic therapy or PCI. If NRMI data indicated that the patient received both fibrinolytic therapy and PCI, we considered only the first one received. In each cohort, we excluded patients with unknown door-to-treatment time and those admitted to a hospital outside the United States. The absence of door-to-treatment time did not vary significantly by race/ethnicity. To avoid including hospitals that administered reperfusion therapy uncommonly, we also excluded patients who were admitted to hospitals that reported to the NRMI fewer than an average of 5 cases per year of fibrinolytic therapy (for the fibrinolytic therapy cohort) or of primary PCI (for the PCI cohort) over the study period. Finally, we excluded patients for whom race/ethnicity information was missing. The institutional review board at the Yale University School of Medicine determined that this protocol was exempt from review because we used existing data that had no patient identifiers.

The principal outcome was the time between hospital arrival and delivery of reperfusion therapy. Time to fibrinolytic therapy (ie, door-to-drug time) and time to PCI (ie, door-to-balloon time) were analyzed as separate outcomes. We modeled each as a continuous variable, given recent evidence supporting the continuous relationship between time to reperfusion and 1-year mortality.²⁰ Because the distributions of the outcome variables were skewed, we log transformed^21- 22 the outcome measures for performing parametric analysis. To improve the clinical interpretation of the results, we converted the transformed values from the model back to their original units, ie, minutes, using geometric means^21- 22 and simulation with 10 000 reiterations.²³ Compared with the arithmetic mean, the geometric mean gives less weight to outlying values and thus better reflects the median outcome values.

The primary independent variable was patient race/ethnicity, coded as a set of dummy variables indicating patients’ racial/ethnic group, which was abstracted from the medical records using the following categories: white, African American/black, Hispanic, Asian/Pacific Islander, American Indian or Alaska native, and other or unknown race/ethnicity. Admission or triage staff recorded race/ethnicity as the patient was registered, using hospital-defined race/ethnicity options; in NRMI, patients were assigned to only 1 race/ethnicity category.

Patient-level variables other than race/ethnicity included sex, age (<65, 65-80, >80 years), insurance status, and clinical characteristics. Clinical characteristics consisted of medical history (current smoker, chronic renal insufficiency, previous AMI, hypertension, family history of coronary artery disease, hypercholesterolemia, heart failure, previous percutaneous transluminal coronary angioplasty, previous coronary artery bypass graft surgery, chronic obstructive pulmonary disease, stroke, angina, diabetes); presentation characteristics (chest pain, systolic blood pressure, pulse rate, heart failure); and the results of the first electrocardiogram obtained after hospital arrival (number of leads with ST-segment elevation, left bundle-branch block, AMI location, ST-segment depression, nonspecific ST-segment or T-wave changes, Q wave). We included the reported time between symptom onset and hospital arrival, arrival time and day of week, and whether a prearrival electrocardiogram had been performed. We also included calendar time, calculated as the number of days between January 1, 1999, and the hospital admission date, as an independent variable to account for any secular trends as well as for differing reporting periods by hospitals, although it was nonsignificant in all models.

Hospital characteristics were obtained from the American Hospital Association Annual Survey of Hospitals¹⁷ and the SMG Marketing Group data set²⁴ and included Census region, urban/rural location (urban defined as location in a county with a population ≥50 000) and teaching status (ie, participation in a residency or fellowship training program accredited by the Liaison Committee on Medical Education), hospital ownership type (government, not-for-profit, for-profit), and cardiac facilities (presence of cardiac surgery capability, catheterization laboratory only, or neither for the fibrinolytic therapy sample). We combined hospital urban/rural location and teaching status to include the resulting 4-level variable. For the door-to-drug analysis, we estimated the hospital’s annual fibrinolytic therapy volume (0-14, 15-30, >30 cases) and the percentage of all primary reperfusion cases that were performed with fibrinolytic therapy rather than PCI (<20%, 20%-90%, >90%) from the NRMI database. For the door-to-balloon analysis, we estimated the hospital’s annual PCI volume (<20, 20-40, >40 cases) and percentage of all primary reperfusion cases performed with PCI rather than drug therapy (<20%, 20%-90%, >90%) from the NRMI database.

We performed separate analyses for the fibrinolytic therapy and PCI cohorts. We first examined overall geometric means for door-to-treatment times for each racial/ethnic group, which we termed “crude” means, by comparing log time to treatment between groups using t tests adjusted for clustering of patients within hospitals.²⁵ Then, to explore how these crude differences might be mediated by patient-level and hospital-level factors, we estimated a sequence of hierarchical models²⁶ for each cohort. We used hierarchical models because patients were clustered within hospitals (the unit of enrollment in the NRMI). In all models the intercept and calendar time were modeled as random effects to account for hospital-specific effects, ie, differences in mean time to treatment and in improvement in time to treatment at the hospital level.

We first estimated a hierarchical model including only race/ethnicity to assess the extent to which crude racial/ethnic differences in time to treatment were attenuated by hospital-specific effects. Then, in successive hierarchical models, we adjusted for covariates in the following sequence: (1) patient age, sex, and insurance status; (2) clinical characteristics; (3) time between symptom onset and hospital arrival, arrival time and day of week, and whether a prehospital electrocardiogram was performed; and (4) hospital characteristics. Covariates considered in each model have been shown in previous literature to be associated with β-blocker use or were empirically associated with β-blocker use in this data set. We validated the normality assumptions of all models by inspecting the quartile-quartile plots of the patient-level residuals and the Mahalanobis distance of the hospital-level residuals.²⁷ The proportion of variance in the outcome explained was indicated by the R² for each model. Statistical analyses were performed using SAS versions 6.12 and 8.2 (SAS Institute Inc, Cary, NC), HLM version 5.04 (SSI, Lincolnwood, Ill), and Stata version 8.0 (Stata Corp, College Station, Tex).

The cohorts included 73 032 patients receiving fibrinolytic therapy in 1052 hospitals and 37 143 patients receiving primary PCI in 434 hospitals. Table 1, Table 2, Table 3, and Table 4 describe the patient and hospital characteristics for both the fibrinolytic therapy and the PCI patient cohorts separately. In both cohorts, about 5% were identified as African American/black, about 4% as Hispanic, about 2% as Asian/Pacific Islander, less than 1% as American Indian or Alaska Native, and about 4% as “other” race or ethnicity. The geometric mean for door-to-drug time for all racial and ethnic groups combined was 34.3 minutes (95% confidence interval [CI], 34.1-34.4 minutes) (Table 1). The geometric mean door-to-balloon time was 104.7 minutes (95% CI, 104.2-105.1 minutes) (Table 2).

Many patient and hospital covariates differed significantly by racial and ethnic groups (Tables 1-4), highlighting the importance of adjusting for these factors in analysis of racial and ethnic differences in the outcome. White patients tended to be older than patients of other racial and ethnic groups. African American/black patients were more likely to be female compared with white patients. Insurance status differed significantly, with nonwhite patients more likely to have Medicaid only or no insurance compared with white patients. Differences in clinical characteristics were pronounced, and patients in the nonwhite groups were generally more likely than white patients to be current smokers and to have chronic renal insufficiency, diabetes, or hypertension. Racial and ethnic group differences are also apparent in the geographic region of the hospital to which patients were admitted, urban/rural location, teaching status, ownership type of the hospital, availability of cardiac facilities, and volume of reperfusion cases (fibrinolytic therapy and PCI) performed annually at the hospital.

As shown in Table 5, the crude geometric mean of door-to-drug time was significantly longer for patients identified as African American/black (41.1 minutes), Hispanic (36.1 minutes), and Asian/Pacific Islander (37.4 minutes) compared with patients identified as white (33.8 minutes; P<.01 for all). These crude differences by race/ethnicity were attenuated to varying degrees, depending on the racial/ethnic group, after accounting for the overall mean door-to-drug time at the hospital in which the patient was treated (Table 5, model 0).

The racial and ethnic group differences in door-to-drug time remained significant, although further attenuated, after adjustment for age, sex, and insurance status (Table 5, model 1); clinical characteristics (Table 5, model 2); time of arrival, time since symptom onset, and having a prehospital electrocardiogram performed (Table 5, model 3); and hospital characteristics (Table 5, model 4). After full adjustment for patient-level and hospital-level factors (Table 5, model 4), the differences by racial/ethnic group in door-to-drug times were 5.1 (95% CI, 4.2-5.9) minutes longer for patients identified as African American/black compared with white patients (P<.001), 1.3 (95% CI, 0.4-2.3) minutes longer for Hispanic compared with white patients (P = .006), and 1.7 (95% CI, 0.4-3.0) minutes longer for Asian/Pacific Islander compared with white patients (P = .01).

As shown in Table 2 and Table 6, the geometric mean of door-to-balloon times for patients identified as African American/black (122.3 minutes) or Hispanic (114.8 minutes) were significantly longer than for patients identified as white (103.4 minutes) (P<.001 for all). A marked proportion of these differences were attenuated for all racial/ethnic groups when we accounted for differences in the geometric mean time to treatment of patients treated at the hospital at which a given patient was treated (Table 6, model 0).

Consistent with the analysis of door-to-drug time, racial/ethnic group differences in door-to-balloon time remained significant, although attenuated in most cases, after adjusting for age, sex, and insurance status (Table 6, model 1) and then further adjusting for clinical characteristics such as covariates (Table 6, model 2); time of arrival, time since symptom onset, and whether a prehospital electrocardiogram was performed (Table 6, model 3); and hospital characteristics (Table 6, model 4). In the fully adjusted model (Table 6, model 4), door-to-balloon time remained 8.7 (95% CI, 6.7-10.8) minutes longer for African American/black patients compared with white patients (P <.001) and 3.7 (95% CI; 1.3-6.1) minutes longer for Hispanic patients compared with white patients (P = .002).

We found marked differences in time to reperfusion by race/ethnicity, with patients identified as African American/black having on average about 20% longer door-to-drug and door-to-balloon times than patients identified as white. This difference equates to times that are 7 minutes longer for door-to-drug time and 19 minutes longer for door-to-balloon time. We also found significant differences in times to acute reperfusion therapy for patients identified as Hispanic and for those identified as Asian/Pacific Islander, although the magnitude of these differences was more modest.

While differences in door-to-treatment times have been shown in previous studies,^12- 15 our study advances that research in several ways. We examine multiple racial/ethnic categories, whereas previous studies of differences in time to acute reperfusion focused only on African American/black vs white comparisons^12,15 or on nonwhite vs white comparisons,¹⁴ which might oversimplify our understanding of difference by racial/ethnic groups. Due to the relatively small numbers of patients identified as Asian and American Indian, however, we had little statistical power to detect differences among these groups, as reflected in the wide CIs for the estimates for these groups. In addition, unlike previous studies, we used hierarchical models to examine both hospital-level and patient-level factors that simultaneously and adequately account for the clustering of patients within hospitals. Without such modeling, it is difficult to explicitly examine the effect of the hospitals on patients’ time to reperfusion therapy; estimates of all effects may be incorrect, and standard errors are typically underestimated. Also, unlike previous studies of racial/ethnic differences in time to treatment, we use sequential models to investigate the extent to which hospital-level and patient-level factors mediate, and thus potentially explain, these disparities. Understanding the relative importance of these factors is critical for targeting effective interventions to eliminate such disparities.

Our findings reveal that a substantial portion of the racial and ethnic disparity in time to treatment is accounted for by the hospital to which a patient is admitted, in contrast to differential treatment by race and ethnicity inside the hospital. For instance, the crude difference in door-to-balloon time between African American/black and white patients was reduced by 33% after accounting for differences between the hospitals in which patients were treated. More striking, the crude difference in door-to-balloon times between Hispanic patients and white patients was reduced by nearly 75% after accounting for differences between the hospitals in which they were treated.

However, the racial/ethnic group differences were not attenuated substantially by the addition of structural hospital characteristics to the models. This suggests that the crude race/ethnicity-related differences in time to treatment were not largely attributable to traditional proxies for hospital quality such as volume, teaching status, or urban/rural location. Rather, the crude differences by race/ethnicity were accounted for by other unmeasured differences in hospitals in which certain patients received care. The result is important for designing interventions that address such disparities and highlights the importance of improving the quality of care in hospitals in which minority groups are more likely to be treated.

Nonetheless, holding the hospital in which care was received constant, there remained racial and ethnic disparities in door-to-drug and door-to-balloon times. These within-hospital differences by race/ethnicity were independent of differences in patients’ clinical characteristics, sociodemographic factors, insurance status, or structural hospital characteristics. Although the magnitude of this independent race/ethnicity effect was modest, recent research indicates that small delays can importantly influence 1-year mortality.²⁰ The effect is notable given the comprehensive set of covariates for which we adjusted. Furthermore, from the perspective of health care equity, systematically longer times to treatment for certain racial/ethnic groups that are not explained by clinical characteristics raise concerns. These remaining differences may result from unmeasured aspects of patients’ clinical characteristics or other issues such as differences in patient preferences, communication patterns between clinicians and patients, or clinician/institutional bias, which may influence patterns of care.

There are several study design issues to consider in interpreting these findings. We used a national sample of hospitals and thus had diverse groups of patients, enabling us to assess differences across multiple racial and ethnic groups. However, racial/ethnic groups are heterogeneous, and the assignment of patients to these groups is inherently imperfect.²⁸ We used race/ethnicity codes recorded by admissions or triage staff as the patient was registered, and these may or may not reflect the patients’ self-identified race/ethnicity.^29- 33 Nevertheless, to the degree that these reflect how clinicians view a patient’s race and ethnicity, this approach is reasonable for understanding potential differential treatment based on perceived racial and ethnic groups. In addition, we were unable to obtain information on other patient socioeconomic factors that might vary by race and ethnicity, such as education, occupation, and income. We did, however, adjust for insurance status, an important aspect of socioeconomic status in this context. Furthermore, we did not assess differences in patient preferences or clinician bias, which others have suggested might account for racial and ethnic differences in treatment.^3,34- 36 Finally, our sample was drawn from hospitals that participated in the NRMI, which tend to have greater AMI volume, are more likely to be nonprofit, and are larger than hospitals that do not participate in the NRMI; furthermore, time-to-treatment data are self-reported by hospitals. However, the NRMI provides the only national, longitudinal data on the clinical characteristics and time to treatment for patients with AMI, and we believe these issues are unlikely to have substantially affected our findings.

Our study has important implications for efforts to eliminate disparities in time to acute reperfusion. Although efforts to increase awareness of racial/ethnic disparities inside the hospital are important, our findings suggest the need for parallel efforts directed toward improving the care in hospitals that are lagging in their quality and in which minority patients may be more likely to receive their care. Experts have identified possible explanations for the racial and ethnic disparities in cardiovascular care,^1,3,37- 39 including differences in clinical presentation, access to care, and clinician bias.

We conclude that the genesis of racial/ethnic disparities in time to treatment is complex, involving differences in the hospitals accessed by minority groups as well as differential treatment inside the hospital. Interventions to eliminate racial/ethnic disparities are likely to fall short of their goals unless they are accompanied by systemic changes that can ensure all patients have access to high-quality hospitals.