Race-based and cultural bias is prevalent and widespread in many medical and clinical informatics environments for patients, caregivers, providers, and staff. Patients of non-racially dominant races or cultures can be subject to bias that negatively impacts their medical experience and health outcomes. The types of impacts vary, however, as Asian American health is often studied by examining this group as a monolithic category. This racially convenient labelling of heterogeneous individuals perpetuates bias and homogenizes health risks within this diverse group. As one of many examples, machine learning may perpetuate disparities based on insufficiently representative data.1 This faultiness results from studies that do not appropriately account for race-based considerations and idiosyncrasies in their methods and interpretation. Additional scenarios range from practitioners who may have been educated on race-based misinformation to patients who may not speak the culturally dominant language, and hence receive medical management that would not be on par with those who speak it.
In this perspective, we summarize relevant issues and literature in relation to gaps we have encountered in our professional work as clinical informatics professionals. With respect to the diversity of clinical informatics practitioners and professionals, bias also can contribute to limitations in career advancement and employment opportunities across numerous sectors, including academia, health care, industry, and government. There is a tendency in professional settings to mythicize Asian Americans as a “model minority,” which both glamorizes and stereotypes certain characteristics of professionals of Asian descent.2 There is also a “bamboo ceiling,” or underrepresentation of professionals of Asian descent in leadership positions in the United States, even though the perception is that there is overrepresentation of this group in the natural sciences and engineering disciplines.3,4
Professionals of Asian descent commonly experience race-based microaggressions (i.e., “Where are you really from?” or “Your English is really good.”), other forms of discrimination, and, more recently since the COVID-19 pandemic, an uptick in hate and harassment. Patient and caregiver experiences coupled with the need for culturally competent care can impact outcomes.5 Such phenomena must be exposed, identified, and acknowledged for resolution that can enable change and optimization of experiences and outcomes of those impacted for patients, staff and informaticists alike. Additionally, there are other opportunities to address previously overlooked issues, for example:
• Developing culturally sensitive patient educational materials and education for health professionals on these issues to support clinical practice
• Highlighting racism and racial and cultural bias, including how to identify and address it in different organizational settings for clinicians, staff and leaders
• Providing mentoring programs for different types of career challenges and stages (e.g., scholarly communications, such as scientific publication) and sponsorship to promote professional communications and advancement, with a focus enabling diversity and inclusion in informatics and adjacent professions
• Highlighting the impacts of underrepresentation in clinical trials and databases, which in turn inform and introduce bias into predictive analytic models, and advancing methods to address underrepresentation such as recruitment and different analytic techniques focusing on responsible artificial intelligence
• Identifying and disseminating the ways by which informatics and allied professionals can identify bias against patients and colleagues to become better informed and prepared allies.
In the spirit of Asian Pacific American Heritage Month, we look forward to the opportunity to share our perspectives live at a panel discussion of the American Medical Informatics Association’s Clinical Informatics Conference in late May. There, we will engage with our fellow informaticists in dialogue on race-based and cultural bias in clinical informatics work and learning environments and to identify ways of addressing these issues. As professionals with training and personal experience in these spaces, we believe that greater awareness is needed about the impact such biases can have on patients, medical practitioners, informatics practitioners and professionals across various settings, such as academia, health care, industry, publishing, and government. We also welcome readers to contact us further regarding their own experiences and viewpoints on how best to address these challenging structural biases in health care and informatics.