People who are black or of Latin American descent with heart failure are less likely to be admitted to specialized cardiology units, a disparity that may help explain long-known racial differences in heart failure outcomes, according to new research published in the American Heart Association's journal Circulation: Heart Failure.
The retrospective, single-center study is one of the first to demonstrate that racial inequities in the type of care received, either specialized cardiac care or general care, for patients admitted to the hospital with heart failure may drive subsequent racial inequities in heart failure outcomes.
Researchers reviewed hospital admissions and discharges for 10 years to yield nearly 2,000 patients treated for heart failure at Brigham and Women's Hospital in Boston.
After adjusting for a variety of demographic and clinical factors, the analysis found patients who self-identified as black were 9% less likely to be admitted to specialized cardiac care units; patients who self-identified as Latinx, a gender-neutral term describing a person of Latin American origin or descent, were 17% less likely to be admitted to specialized heart units; and female heart failure patients and those older than 75 were more likely to be treated on a general medicine floor.
Also, admission to a heart specialty unit was independently associated with a 16% lower rate of hospital readmission within 30 days. Readmission during the first month of discharge generally may signal poorly managed disease, but often foreshadows worse outcomes and worse overall prognosis in heart failure, the researchers said.
WHAT'S THE IMPACT
Racial inequities and higher readmission rates among minority populations have been documented in previous studies. But the findings here suggest that admission practices may provide a partial explanation behind these well-known racial disparities in heart failure outcomes. The researchers emphasize that the observed disparities in outcomes likely stem from structural and systemic differences in care rather than biological differences in disease progression for people of different ancestries.
The factors behind the difference in admission patterns are likely multifactorial, the researchers said, but reflect inequities in outpatient access to outpatient cardiology care. Black and Latinx patients were not under the care of a cardiologist as an outpatient at the time of hospitalization -- the strongest predictor of admission to a cardiology unit, according to the study.
Levels of perceived discrimination and mistrust in the healthcare system may also lead to differential self-advocacy for admission to a specialized service by patients from different backgrounds. While structural drivers are likely the major drivers, the authors feel that implicit bias is ubiquitous and probably contributes as well.
The study was not designed to uncover the reasons behind the higher readmission rates among those treated in the general medicine unit. But the difference in outcomes may be driven by the greater expertise, improved overall care and specialized support services with a focus on cardiac illness that are available in cardiology units. The researchers said premature discharge, inadequate transitions of care from the hospital to home and lower rates of cardiology follow-up for those admitted to general medicine may also worsen patient outcomes.
Decision tools and guidelines for admissions staff and racial equity training for clinicians could help close the gap in access to specialized cardiac care and to improve outcomes. Increased staff education could also help to standardize heart failure care between cardiology and general medicine units. Additional tools may include strategies to ensure that all patients are followed by a cardiologist after leaving the hospital, the researchers said.
THE LARGER TREND
Racial disparities are evident in many facets of healthcare, some of them unexpected.
Another study published this month found racial bias in an algorithm from Optum that is widely used by health systems. The algorithm helps hospitals identify high-risk patients, such as those who have chronic conditions, to help providers know who may need additional resources to manage their health.
The authors black patients assigned the same level of risk by the algorithm are actually sicker than white patients, but bias occurs because the algorithm uses health costs as the measure for health needs. The algorithm predicts healthcare costs, rather than illness; meanwhile, less money is spent caring for black patients than for white patients.