Surveying health inequities in cardiac arrhythmia detection.

Atrial fibrillation (AF) is understood to be the most common cardiac arrhythmia, impacting an estimated 37.6 million people around the world.¹ By 2050, this number is expected to increase by more than 60%, according to Lippi et al., authors of “Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge,” published in International Journal of Stroke: Official Journal of the International Stroke Society.²

JUMP TO A TOPIC:

• Variations in AF prevalence and treatment across racial and ethnic groups.
• Disparities in AF prevalence with respect to gender. 
• Social determinants in relation to AF. 
  
• AF and related disease states.
• Implicit bias in cardiac health disparities. 
• The potential of digital health innovations. 
• The path forward. 

Notable differences in the prevalence and management of AF among various racial and ethnic groups have been observed by researchers, with social determinants considered to potentially play a role in shaping these disparities.^3,4 As Tamirisa et al., authors of the study “Racial and ethnic differences in the management of atrial fibrillation,” noted in the journal CJC Open, “Many factors might contribute to the racial and ethnic disparities in AF management, including systemic biases, social determinants of health, trust in healthcare providers, health literacy, and perceived differences in response to therapy that may or may not be real.”⁵  

The possible influence of social determinants and the potential for certain digital health innovations to address inequalities in AF detection between different groups may merit further discussion. 

Variations in AF prevalence and treatment across racial and ethnic groups. 

Researchers suggest that measured rates of AF prevalence vary among different racial and ethnic populations. Tamirisa et al. stated that “Population-based studies have consistently reported a lower AF burden among racial and ethnic minorities, despite their having a higher prevalence of traditional risk factors.”⁶ To better understand and address the disparities and biases in AF detection, Tamirisa et al. considered that it may be valuable to explore race-specific risk factors associated with AF and conduct a comprehensive review of the differences in AF management for various racial and ethnic groups.⁷ 

In “Differences by race/ethnicity in the prevalence of clinically detected and monitor-detected atrial fibrillation,” a study published in the American Heart Association's journal, Circulation: Arrhythmia and Electrophysiology, authors Heckbert et al. state, “The prevalence of clinically detected AF was substantially lower in African American than in [W]hite participants, without or with adjustment for AF risk factors. However, unbiased AF detection through ambulatory monitoring revealed little difference in the proportion of AF by race/ethnicity.”⁸ The researchers offer this explanation, “Differences by race/ethnic group in clinically-detected AF may be real; may reflect differences in symptom perception, clinical AF recognition, or health care access; or may be due to differences in the completeness of clinical event ascertainment.”⁹ 

It is important to note that “clinical detection”¹⁰ of atrial fibrillation typically refers to identification and diagnosis of AF through evaluation performed by healthcare professionals. In this context, there may be room for physician bias as physicians decide who they evaluate further, which may be a factor that plays into health disparities. In the Heckbert et al. study, all participants were provided with a Zio XT monitor, so AF in this case was actually “monitor detected,” eliminating physician selection of patients.¹¹ 

Disparities in AF prevalence with respect to gender. 

Volgman et al., authors of the paper “Sex and race/ethnicity differences in atrial fibrillation,” published in the Journal of the American College of Cardiology, found more literature is reported and studied focusing on sex differences in patients with AF as opposed to racial/ethnic differences in patients with AF.¹² 

“There is a significant difference in the prevalence of AF by sex, with a 3:2 male to female ratio that has not been fully explained. However, this observation does not consider age-related differences and the predominance of women in our elderly population,” said Volgman et al.¹³ They further noted that “addressing this sex knowledge gap could provide direction for novel approaches to forestall or even prevent the development of AF in men and women.”¹⁴

Regarding racial/ethnic differences, Volgman et al. state, “in the analysis reported, it appears that there are significant racial/ethnic differences, with [W]hites having higher rates of AF versus [B]lacks.”¹⁵  

Social determinants in relation to AF. 

It is believed that the potential to develop AF may be partially determined by social factors. In the journal Nature Reviews Cardiology, Essien et al. authored “Social determinants of atrial fibrillation,” which states, “Social determinants, such as race/ethnicity, financial resources, social support, rurality and residential environment, and health literacy, have crucial roles in the detection, evaluation, treatment and management of atrial fibrillation.”¹⁶ The authors further note that “collecting, studying and addressing social determinants of health provides an important opportunity to reduce the substantial social and economic burden of atrial fibrillation and its associated complications.”¹⁷ 

Incorporating social determinants of health into AF research may be beneficial for those working toward removing substantial disparities in AF diagnosis, treatment, and outcomes across different populations. In JAMA Cardiology, authors of “Transforming atrial fibrillation research to integrate social determinants of health: A National Heart, Lung, and Blood Institute workshop report” Benjamin et al. highlight that “individuals with AF have multiple adverse social determinants, which may cluster in the individual and in systemically disadvantaged places (eg, rural locations, urban neighborhoods). Cumulative disadvantages may accumulate over the life course and contribute to inequities in the diagnosis, management, and outcomes in AF.”¹⁸ 

AF and related disease states. 

There may also be other factors worth considering in AF detection as it varies between different groups, such as associated disease states. In “Association of diabetes with atrial fibrillation phenotype and cardiac and neurological comorbidities: Insights from the Swiss-AF study,” this quote from Bano et al. suggests there may be a link between asymptomatic AF and diabetes: “Patients who have AF with diabetes less often perceive AF symptoms but have worse quality of life and more cardiac and neurological comorbidities than those without diabetes. This raises the question of whether patients with diabetes should be systematically screened for silent AF.”¹⁹ 

In the US, more American Indian/Alaksa Native, Hispanic, Black, and Asian adults were diagnosed with diabetes than White adults between 2017 and 2018.²⁰ Given the starting point for AF testing in the US is often the presence of symptoms,²¹ it could be argued that the AF prevalence data for patients with comorbidities — especially those in racial minorities — may be artificially low. 

Implicit bias in cardiac health disparities. 

The National Institutes for Health defines implicit bias as, “a form of bias that occurs automatically and unintentionally, that nevertheless affects judgments, decisions, and behaviors.”²²  

Studies of patients in the Veterans Affairs (VA) system considered whether cardiac health disparities may have less to do with access to care, than with other factors such as bias.^23,24 VA patients generally all have equal access to the same drugs and therapies, but appear to experience different prescription patterns and health outcomes based on race and ethnicity.^25,26 

The study “Racial disparities in prescriptions for cardioprotective drugs and cardiac outcomes in Veterans Affairs Hospitals” by Mehta et al. found that White patients received more overall cardioprotective therapies in the VA system than Black patients — based on data for 474,565 patients in the Veterans’ Integrated Service Network 16 database.²⁷ The Mehta et al. study reveals that beta blockers were prescribed to 24.8% of White patients, but only 19.7% of Black patients.²⁸ Statins were prescribed to 30.2% of White patients and 20.5% of Black patients,²⁹ a nearly 1.5-fold disparity. The trend continued across other therapies, including angiotensin-converting enzyme inhibitors prescribed to 30.0% of White patients and 27.7% of Black patients.³⁰ 

A VA study by Essein et al. focused on anticoagulant therapy including two types of anticoagulants, direct oral anticoagulants (DOACs) and warfarin.³¹ DOACs are regarded as the more effective and safer of the two,³² as warfarin can cause life-threatening bleeding.³³ During the 2014–2018 period when the VA was transitioning its focus to DOACs, overall DOAC use increased from 29.9% to 86.7% and warfarin use decreased from 70.1% to 13.3%.³⁴ The research by Essein et al. published in “Disparities in anticoagulant therapy initiation for incident atrial fibrillation by race/ethnicity among patients in the Veterans Health Administration System” shows that DOAC prescriptions reached 66.0% for White patients, 60.9% for Black patients, and 58.3% for Hispanic patients. And warfarin prescriptions fell to 34.0% for White patients, 39.1% for Black patients, and 41.7% for Hispanic patients.³⁵  

One explanation for the differences in AF management shown in the VA studies above could be due to implicit bias on the part of physicians. Healthcare systems can take steps including raising awareness, providing implicit bias training, and implementing bias-reductions strategies to help mitigate implicit bias.³⁶   

The potential of digital health innovations. 

Researchers suggest that developing health informatics and digital health innovations with engagement from underserved communities may help impeded health inequities.³⁷ As Brewer et al. point out in the paper they authored “Back to the future: Achieving health equity through health informatics and digital health,” published in JMIR mHealth and uHealth, “There is no doubt that these fields will continue to have accelerated growth and a substantial impact on population health. However, there are legitimate concerns about how these promising technological advances can lead to unintended consequences such as perpetuating health and health care disparities for underresourced populations.”³⁸ 

Continuing, Brewer et al. posit, “To mitigate this potential pitfall, it is imperative for the health informatics and digital health scientific communities to understand the challenges faced by disadvantaged groups, including racial and ethnic minorities, which hinder their achievement of ideal health. . . . We strongly encourage researchers and innovators to integrate community engagement into the development of data-driven, modernized solutions for every sector of society to truly achieve health equity for all​​​​.”³⁹ 

Other researchers expressed, “Digital health interventions show incredible potential to improve cardiovascular diseases.”⁴⁰ In the article “Health techequity: Opportunities for digital health innovations to improve equity and diversity in cardiovascular care,” published in Current Cardiovascular Risk Reports, authors Hernandez et al. comment on considerations regarding the digital divide, “As the expansion of digital health technologies continues, it is vital to increase representation of minoritized groups in all stages of the process: product development (needs findings and screening, concept generation, product creation, and testing), clinical research (pilot studies, feasibility studies, and randomized control trials), and finally health services deployment.”⁴¹ 

Combining telehealth with self-application of ambulatory electrocardiographic (ECG) monitors could help bridge healthcare gaps for people living in remote areas. Today, patients can receive and apply ambulatory ECG patch monitors at home and return them by mail at the end of the wear period. This process has the potential to eliminate two clinic visits — one to apply the monitor and one to return the monitor. In the study “Effect of a home-based wearable continuous ECG monitoring patch on detection of undiagnosed atrial fibrillation: The mSToPS randomized clinical trial,” published in JAMA, authors Steinhubl et al. used an ambulatory ECG patch monitor when leading a “direct-to participant” clinical trial of individuals who had an increased likelihood of developing AF.⁴²  They found “immediate monitoring with a home-based wearable ECG sensor patch, compared with delayed monitoring, resulted in a higher rate of AF diagnosis after 4 months. Monitored individuals, compared with nonmonitored controls, had higher rates of AF diagnosis, greater initiation of anticoagulants, but also increased health care resource utilization at 1 year.”⁴³ 

Steinhubl et al. shared mSToPS study follow-up results in “Three year clinical outcomes in a nationwide, observational, siteless clinical trial of atrial fibrillation screening—mHealth Screening to Prevent Strokes (mSToPS),” published in PLOS ONE: 

Among the screened cohort with incident AF, one-third were diagnosed through screening. For all individuals whose AF was first diagnosed clinically, a clinical event was common in the 4 weeks surrounding that diagnosis: 6.6% experienced a stroke, 10.2% were newly diagnosed with heart failure, 9.2% had a myocardial infarction, and 1.5% systemic emboli. Cumulatively, 42.9% were hospitalized. For those diagnosed via screening, none experienced a stroke, myocardial infarction or systemic emboli in the period surrounding their AF diagnosis, and only 1 person (2.3%) had a new diagnosis of heart failure.⁴⁴ 

AF is well known to increase the likelihood of stroke and heart failure.^45,46 Given that young Black adults have been found to be four times more likely to have a stroke than their White peers⁴⁷ and that the US Department of Health and Human Services said Black adults were nearly 30% more likely to die from heart disease than White adults in 2019,⁴⁸ tools like telehealth and remote ambulatory ECG monitoring could help break down health disparities for patients in underrepresented populations. 

The path forward. 

Sex- and race-based health disparities are multifactorial.⁴⁹ The many differences in AF diagnoses between men and women as well as Whites and Black, as studied by Volgman et al.⁵⁰ highlight the need to effectively address health disparities. In addition to raising awareness and education,⁵¹ solutions may lie in focusing on social determinants, as discussed by Benjamin et al.,⁵² or providing healthcare remotely, like the self-applied ECG patch monitors used by Steinhubl et al.⁵³  

Understanding the challenges faced by disadvantaged groups, striving to perform unbiased research, and incorporating community engagement into the development of data-driven solutions will likely help the healthcare community work toward advancing health equity.