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Implicit Bias in Healthcare-2hr

2 Contact Hours
This course does not meet Michigan's Implicit Bias requirements
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This peer reviewed course is applicable for the following professions:
Advanced Practice Registered Nurse (APRN), Athletic Trainer (AT/AL), Certified Nurse Midwife, Certified Nurse Practitioner, Certified Registered Nurse Anesthetist (CRNA), Certified Registered Nurse Practitioner, Clinical Nurse Specialist (CNS), Licensed Practical Nurse (LPN), Licensed Vocational Nurses (LVN), Midwife (MW), Nursing Student, Occupational Therapist (OT), Occupational Therapist Assistant (OTA), Physical Therapist (PT), Physical Therapist Assistant (PTA), Registered Nurse (RN), Respiratory Care Practitioner, Respiratory Therapist (RT)
This course will be updated or discontinued on or before Thursday, October 15, 2026

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CEUFast, Inc. is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center's Commission on Accreditation. ANCC Provider number #P0274.


CEUFast, Inc. is an AOTA Provider of professional development, Course approval ID#03713. This distant learning-independent format is offered at 0.2 CEUs Intermediate, Categories: Professional Issues & Foundational Knowledge. AOTA does not endorse specific course content, products, or clinical procedures. AOTA provider number 9757.


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CEUFast, Inc. (BOC AP#: P10067) is approved by the Board of Certification, Inc. to provide education to Athletic Trainers (ATs).

FPTA Approval: CE24-889436. Accreditation of this course does not necessarily imply the FPTA supports the views of the presenter or the sponsors.
Outcomes

≥ 92% of participants will gain awareness about implicit bias in healthcare and mitigation strategies.

Objectives

After completing this course, the learner will be able to:

  1. Define implicit bias.
  2. Summarize the impact of historical racism.
  3. Determine how implicit bias presents challenges in healthcare.
  4. Recognize different types of implicit bias.
  5. Describe the methods used to assess for, measure, and mitigate implicit bias.
CEUFast Inc. and the course planners for this educational activity do not have any relevant financial relationship(s) to disclose with ineligible companies whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients.

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Implicit Bias in Healthcare-2hr
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To earn a certificate of completion you have one of two options:
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    (NOTE: Some approval agencies and organizations require you to take a test and "No Test" is NOT an option.)
Authors:    Alyssa King (DNP, APRN, CPNP-PC, PMHNP-BC, CLC, CNE) , Pauline Lisciotto (RN, MSN, APHN-BC) , Desiree Reinken (MSN, APRN, NP-C)

Introduction

A bias is a personal and sometimes unreasonable judgment against a person, place, or thing (U.S. Department of Justice, 2021). We all have our own biases. We are human beings. Our life experiences help inform our future experiences. We will briefly define two main types of bias here and then elaborate more upon them in the next section.

Implicit bias is a bias or prejudice that is present but not consciously held or recognized, so we are often unaware that it exists (U.S. Department of Justice, 2021).

Explicit bias is a personal judgment that we have about a person, place, or thing on a conscious level or one that we are aware of (U.S. Department of Justice, 2021).

Whether these biases are implicit or explicit, they can affect our actions, beliefs, and decisions. These biases, including how a person sounds, looks, and even where they live, may influence our decision-making process (New York State [NYS], 2022; U.S. Department of Justice, 2021).

Both of these types of bias can emerge as prejudice, discrimination, and/or oppression on individual, group, or systemic levels (NYS, 2022; U.S. Department of Justice, 2021). Individual biases are often so deeply ingrained and are born out of a long history of unequal treatment of different social groups, the person’s upbringing, cultural conditioning, discrimination, oppression, and stereotypical portrayals (NYS, 2022; U.S. Department of Justice, 2021). The influence of decisions made that are rooted in biases often have a substantial impact on individuals, social groups, and communities (NYS, 2022; U.S. Department of Justice, 2021).

A benefit of being aware of the potential impression of your own biases is that you can choose to take the initiative in lowering their impact on your decision-making (NYS, 2022; U.S. Department of Justice, 2021).

A Deeper Dive: Implicit Bias

Implicit bias (IB), the human tendency to make decisions outside of conscious awareness and based on inherent factors rather than evidence, may influence the healthcare you provide. Also known as unconscious bias, IB establishes itself through attitudes or behaviors developed early in life that are prejudiced against or in favor of one person or group compared to another (Fitzgerald & Hurst, 2017). As identified in the literature across professional health disciplines, IB is associated with negative health disparities, health inequities, and substandard care among diverse populations. Likewise, IB may affect all persons' health by unconsciously influencing how providers perceive and act toward clients and, conversely, how clients may view provider interactions (National Center for Cultural Competency [NCC], 2021; Institute of Medicine [IOM], 2003).

IB is unintentional and attributed to the reflexive neurological system that drives the brain's automatic processing function. As such, an individual's feelings, attitudes, and decisions are involuntary, and their subsequent actions may conflict with their stated views (NCC, 2021). Consequently, the effects of IB can be difficult to identify and measure, and actions resulting from it often are challenging to recognize and control. Healthcare literature describes ongoing IB mitigation efforts, including the promotion of provider awareness, participation in continuing education, advancement of policy development, legislation, and institutional changes, and the contribution of research (Fitzgerald & Hurst, 2017; NCC, 2021; Brecher et al., 2019; The Joint Commission, 2020). Learning about IB and how it differs from explicit bias, recognizing types of IB and how IB provider-client interactions are affected, and embracing strategies to address its impact on practice are approaches toward reducing barriers to equitable care, closing the gap in health disparities between diverse populations, and achieving patient-centered care.

The Impact of Historical Racism

Racial and ethnic minority groups have experienced hardships for as long as anyone can remember. The historical roots of American racism can be traced back to before slavery. Slavery was noted in personal journals in 1619 but is believed to have occurred in the 1400s and 1500s. The nation was divided in the Civil War on the topic and the act of owning enslaved individuals. Specific resistance movements include the Underground Railroad, the Montgomery Bus Boycott, the Selma to Montgomery March, and, most recently, the Black Lives Matter movement (Herschthal, 2022). Each of these movements represents a time when underrepresented populations fought for equality, and many of them had poor experiences with healthcare.

There are specific examples of discrimination in healthcare that have left lasting impressions and resulted in defining types and acts of discrimination and racism (Brandt, 1978):

  • In 1932, researchers recruited 600 African American men in Alabama for a syphilis study. The advertisement read "Free Blood Test; Free Treatment." The 399 participants in the group who had syphilis were never treated – they were just observed until they died. Neither the participants nor their families were aware of this.
  • Another example is the lack of consent. Henrietta Lacks was a 30-year-old African American woman who had cervical cancer. Even though she died, her cancer cells lived on and were cultured on a mass scale without consent.

Throughout history, structural racism has resulted in policies and laws that allocate resources in ways that disempower and devalue individuals, resulting in inequitable access to high-quality care.

Here are some examples of laws that were supposed to promote equality but made systemic issues more difficult (Yearby et al., 2022):

  • In 1935, the National Labor Relations Act expanded union rights, resulting in health insurance coverage. However, the act did not apply to specific domestic and agricultural industries. Instead, it allowed unions to discriminate against racial and ethnic minority workers in these industries.
  • In 1946, the federal government created the Hospital Survey and Construction Act, also called the Hill-Burton Act. This act assisted with the construction of hospitals and long-term care facilities and aimed to create care facilities that were available to everyone, regardless of race or background. However, it allowed states to develop racially separate facilities.

Some of the social and individual forms of racism have foundational issues in the following categories:

  • Power, which is the unfair distribution or disproportionate capacity by a dominant group, results in unfair decisions.
  • Resources such as money, education, information, and political influence are unfairly distributed.
  • Societal standards that marginalize other group norms.

Because of the history of historical racism, underrepresented groups still struggle today. Interpersonal interactions, professional prospects, and quality of life are all affected by the historical roots of racism.

Reproductive Justice

Reproductive justice, formed in response to reproductive politics, is the human right to possess control over health, sexuality, work, gender, and reproduction; it sets forth a piece of intersectionality and analysis of class, race, and gender. The framework surrounding reproductive justice occurs at local, state, and national levels. The fair and equitable principles aim to protect reproductive health. Because reproduction can be a part of culture and identity, it is subject to stigma, discrimination, and restricting laws and policies.

A Brief Note About Explicit Bias

To better understand IB, consider how it contrasts with explicit bias (EB), which is individuals' or institutions' overt expressions of deliberate bias that tend to be recognizable (Jordan, 2018).

EB is attributed to the reflective system of the human brain that is devoted to cognitive processing (NCC, 2021). Consider the following EB example: A neurosurgeon decides to initiate a patient billing policy that excludes the acceptance of patients' insurance and demands full payment at the point of service. Staff posted a sign in the patient waiting room that states, "As of August 1, 2021, this practice does not accept health insurance." This policy openly favors affluent clients over those without financial means, and the inequitable access to care created by it is deliberate, readily identifiable, and measurable.

Challenges of Implicit Bias in Healthcare

IB presents challenges in healthcare when it manifests itself inappropriately and unconsciously contributes to health disparities. Health disparities are the differences in the burden of illness, injury, disability, or mortality outcomes between groups distinguished by characteristics such as age, gender, race, and ethnicity, leading to unfair and avoidable differences in health outcomes. They are considered preventable (CDC, 2020b).

To illustrate this point, the Centers for Disease Control and Prevention reports that during the period 2007-2016, nearly 700 women died in the United States annually from pregnancy-related complications (Petersen et al., 2019). Maternal mortality in the United States is alarming, as are its significant racial and ethnic disparities. American Indian, Alaska Native, and Black women are three to four times more likely to die of pregnancy-related causes than White women (CDC, 2024; Meadows-Fernandez, 2023). It is understood that social determinants of health have historically prevented many people from diverse minority groups from having access to equal opportunities for physical, emotional, and economic health (Howell, 2018). These factors are known to impact health equity (Howell, 2018).

Although targeted efforts to isolate causes and develop successful mitigation strategies to combat the United States’ maternal mortality are ongoing, further innovative research and creative strategies are warranted. Suggestions for provider-focused IB research on this topic may include: Does a provider's IB influence their decision not to make a referral because they believe that the patient is non-compliant, or when to refer a pregnant woman is considered high risk?

Discussion regarding health inequities within the perinatal field does not end with maternal health outcomes. Unfortunately, infant health outcomes are also quite impacted. Despite the overall decline of the infant mortality rate in the United States, significant disparities exist by race and ethnicity. In fact, the non-Hispanic Black population has experienced a 10.8 per 1000 live births infant mortality rate compared to the 4.6 per 1000 live births infant mortality rate of the non-Hispanic White population (Jang & Lee, 2022). It is also known that preterm birth rates among Black and Hispanic populations of people are higher than non-Hispanic White populations. While the overall preterm birth rate in the United States has declined to 10.2% of births, Black families had the highest percentage of preterm births at 14.4% (Jang & Lee, 2022). What factors have been considered that might contribute to these disparities? It is believed that factors that characterize minority populations of people, such as lack of medical insurance, residential environments that are in poor areas with poor conditions, low income, low/disadvantaged education levels, treatment at lower quality medical institutions, and experiences of racial discrimination are often strongly correlated with higher infant mortality rates (Jang & Lee, 2022). It must be considered that racism and socioeconomic factors are involved. In fact, racial discrimination, often demonstrated in the form of IB, has been implicated in leading to increased cortisol levels, contributing to increased adverse health outcomes and prematurity (Jang & Lee, 2022).

In 2003, the Institute of Medicine's formative report, Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, laid a foundation for exploration into healthcare disparities in the US, including bias toward patients of diverse racial, ethnic, or cultural populations. The report concluded that IB, prejudice, stereotypical thinking, and clinical uncertainty in healthcare professions might lead to ethnic and racial disparities within healthcare (IOM, 2003).

More recently, Fitzgerald and Hurst's (2017) systematic review of 42 articles discussed robust documentation of IB among nurses and physicians and reinforced the negative effects of professional caregivers' IB on vulnerable populations, including (Fitzgerald & Hurst, 2017):

  • Children
  • Women
  • Immigrants
  • Those with low health literacy
  • Minority ethnic populations
  • Socioeconomically challenged individuals
  • Sexual minorities
  • Elderly
  • Mentally ill
  • Overweight
  • Disabled

These reports and studies contribute to the evolving body of knowledge about IB in healthcare through research and provoke thoughts about the effects of IB on health outcomes.

Multidisciplinary health literature indicates that many factors contribute to health disparities, including the quality of the healthcare received, the presence of underlying chronic conditions, the existence of structural racism, and, of course, IB (Petersen et al., 2019). Narayan (2019) cites literature that indicates healthcare providers' IB is associated with discriminatory care and adverse effects on patient care, including inaccurate patient assessments, unfitting diagnoses and treatment decisions, less time allocated in patient care, and patient discharges with inadequate follow-up (Narayan, 2019). Additionally, Saluja and Bryant (2021) suggest that IB can affect provider-patient communication among people of color. The effects may include subtle racial biases, such as speaking to patients with a condescending tone that reduces the chances that patients will feel heard by their providers (Saluja & Bryant, 2021). Variations in therapy options may also occur based on assumptions about clients' treatment adherence capabilities or presumed health issues.

Additionally, IB may negatively impact clinical outcomes and violate patient trust. Penner et al. (2016) found in a study of Black oncology patients and their physicians that patients who perceived their providers with significant IB as less supportive and spent less time with them than providers lower in IB. In turn, Black patients viewed high-IB physicians as less patient-centered. With these providers, the patients also had more difficulty remembering what their physicians told them, had overall less confidence in their treatment care plans, and believed it to be more difficult to follow their recommended treatment plans (Penner et al., 2016). These findings on providers' implicit racial bias underscore patients' perceptions of their experiences with providers' IB. However, its overall effects on healthcare quality and health outcomes for diverse populations invite further exploration (Penner et al., 2016).

Barriers to Inclusion

With the shift towards diversity and equity, there come barriers to inclusion. Such barriers may include attitudinal barriers, physical barriers, a lack of or inappropriate education barriers, organizational barriers, and policy barriers.

Attitudinal barriers, or “attitude-based” barriers, are a common and basic type of barrier that can contribute to and lead to the formation of other barriers. Common attitudinal barriers include stereotyping, stigma, discrimination, and prejudice. For example, many societal emotions tend to assume individuals with disabilities have a poor quality of life. A disability should not be considered a deficit (CDC, 2020a). Attitudinal barriers further stigma and discrimination and deny others dignity and equal opportunity. Negative attitudes foster a disabling environment and intensify discrimination and other barriers to inclusion.

Physical barriers also pose a challenge to inclusion, including environmental, institutional, and structural barriers that prevent access and mobility. Examples of physical barriers include not having a wheelchair ramp or accessible walkways (CDC, 2020a).

Education can serve as a barrier to inclusion. If education is not inclusive, does not provide information on resources, or introduces bias, it is a barrier to inclusion. Organizational barriers to inclusion encompass a variety of barriers on administrative, programmatic, and architectural levels. Examples include microaggressions, emotional barriers, jargon, and insensitive behaviors (Abbott & McConkey, 2006).

The policy can implement change. Unfortunately, it can also act as a barrier to inclusivity; this is due to a lack of awareness of laws and regulations, a lack of the ability to enforce laws and regulations, or a lack of ability to make change. Policy barriers can also include a lack of funding (CDC, 2020a).

Cultural Identity & Racism

The social constructs of race, ethnicity, and culture affect identity in many ways. Cultural identity is a term that encompasses the distinctiveness of individuals in a community with shared identities and characteristics (Karjalainen, 2020). Self-perception and self-conception are significant components of cultural identity tied to ethnicity, race, religion, and many other factors.

Unfortunately, with identity comes discrimination for the differences that set us apart. Racial bias, microaggressions, and identity-relevant stressors can, unfortunately, be a part of cultural identity. For many, the formation and modification of identity exist within realms of prejudice and racism. Ethnic and racial discrimination is broadcasted as consistent and unfair treatment within institutions and social structures. Because cultural identity is tied to our very existence, such as school, work, and access to healthcare, the impacts of racism are immeasurable. Racism and discrimination can result in inferiority and a marginalized status, resulting in negative health and quality of life (Yip, 2018).

Measuring & Evaluating Implicit Bias

Surprising to many providers, the level of IB demonstrated by healthcare professionals is understood to be comparable to the general population (Fitzgerald & Hurst, 2017). Given the unconscious nature of IB, directly asking providers about their IB through a self-report survey is not recommended. However, the two most common methods used to assess IB are Implicit Association Testing and Assumption Method.

Implicit Association Testing (IAT) is a computer-generated online testing method that measures associations between participants' attitudes across a wide range of domains, including age, gender, race, ethnicity, sexuality, disability, religion, and weight (Project Implicit, 2021).

For over 20 years, web-based IAT data has been collected through Project Implicit, a consortium of researchers from Harvard University, the University of Virginia, and the University of Washington to study and promote the understanding of attitudes, stereotypes, and other hidden biases that influence perception, judgment, and action (Project Implicit, 2021).

Assumption Method (AM) is a clinical vignette-based testing method that measures differences across participants' responses. The vignettes are designed to be the same except for one variable, such as gender. Inferences are made based on statistically significant responses correlated with the selected feature, such as the patient's gender. An inference is made that the participant’s response is likely due to implicit bias in the individual’s decision-making process (Fitzgerald & Hurst, 2017).

The Priming Test is another way to measure reactions related to inherent and subconscious attitudes. Priming is designed to measure the strength of the association between two stimuli, or targets and particular attributes, or primes. The targets are comparable categories, and the primes are associated with those categories. The Semantic Priming Test uses words, and the Visual Priming Test uses images. With these tests, a prime (word or image) is produced on a screen for a specific period before the target is shown. The participant is told to focus on separating the targets. The participant will react faster if the target is more associated with the prime (Ocejo, 2020).

Affect Misattribution Procedure (AMP) is another test used to measure and evaluate implicit bias. The AMP presents multiple images that are assigned to two categories. Examples of categories include products, ethnic groups, or people. The second category may be neutral, such as a gray image. Then, an icon is displayed with a character, which is judged as positive or negative. According to the logic of the measurement, the effect associated with the image is transferred to the character (Payne et al., 2005).

These are just some examples of common tests used to measure and evaluate implicit bias. There are others; however, they may not be commonly used, and their validity has not been verified.

Mitigating Implicit Bias in Healthcare

Healthcare professionals typically intend to provide optimal patient care, but IB may negatively impact their aim. Strategies to disrupt IB, such as promoting self-awareness and participation in formal training, suggest that biases learned earlier in life may be mitigated (Fitzgerald et al., 2019).

Efforts to define consistent, evidence-based bias reduction strategies are advancing, and evaluation is ongoing. Meanwhile, learning about types of IB and how they may affect healthcare remains important. Likewise, supporting institutional changes is necessary to sustain meaningful, ongoing mitigation efforts. The literature is rich with resources to mitigate IB, including but not limited to the following topics:

  1. Awareness of common types of IB
  2. Legislation to institutionalize IB training across health professions and healthcare systems

Awareness of Common Types of Implicit Bias

Learning about common types of IB and their unintended effects on health professionals and patients is a strategy for building IB awareness. The following list is not intended to be exhaustive but to present a range of IBs that may influence provider-patient or institutional decisions (Brecher et al., 2019; NCC, 2021; Haghighi, 2021). Reflect on how your beliefs may confirm or conflict with the examples and how you might be affected in these scenarios:

Affinity

Affinity– Preference for people who share qualities with you or someone you like.

Example: A Clinic Director (CD) is recruiting to fill one physical therapist vacancy. The final two candidates share comparable minimum education requirements and clinical experiences. The CD selects the candidate who attended their alma mater.

Rationale: Although the candidates are comparable, the CD selects the candidate who feels comfortable and familiar.

Anchoring

Anchoring– Tendency to rely too heavily on the first piece of information offered during decision-making.

Example: While assessing a 25-year-old patient vaccinated for COVID-19, the nurse practitioner notes signs and symptoms: headache, fatigue, sore throat with red and enlarged tonsils, and fever x three days. The patient's strep test is positive, and antibiotics are prescribed. The patient finishes the prescription but returns in seven days with continued complaints of headache and growing fatigue. A rapid COVID-19 test was performed at this visit, and the result was positive.

Rationale: The provider focused on the patient's presenting problem and rushed to a diagnosis that supported their initial clinical impression.

Attribution

Attribution– Tendency to characterize other people's successes as luck or help from others and explain their failures as a lack of skill or personal shortcomings.

Example: A clinical social worker (CSW) who cannot finish case notes promptly compared to their colleagues believes their caseload has too many needy patients with complex mental health diagnoses.

Rationale: CSW's justification is based on perceived situational factors.

Beauty

Beauty– Assumptions about people's skills or personalities based on physical appearance and tendency to favor more attractive people.

Example: A client seeks a surgeon by visiting their insurance plan's website. They are impressed with a physician's photo; they consider them handsome and select them because they associate the surgeon's appearance with intelligence and skill.

Rationale: The client relates beauty with other positive attributes, such as intelligence.

Confirmation

Confirmation– Selective focus on information that supports your initial opinion(s).

Example: A dentist recovers from COVID-19 infection with mild symptoms yet remains vaccine-hesitant.

Rationale: The dentist remains unvaccinated because they have acquired sufficient natural immunity.

Conformity

Conformity– Tendency to be swayed by the views of other people.

Example: A long-term care patient follows Hinduism, practices a strict vegan diet, and asks their nurse for vegan meals. The patient's roommate overhears the conversation and interjects, "dietary will send you whatever you want." Without validating the patient's request with the dietician, the nurse submits the vegan meal request.

Rationale: The nurse tends to agree with people around them rather than use their professional judgment.

Disability

Disability– Tendency to assign a lower quality of life because of disability.

Example: An adult patient with Down syndrome and severe congenital heart disease was considered by their primary care provider (PCP) to be an inappropriate referral for a heart transplant procedure due to their intellectual/developmental delay (IDD).

Rationale: The PCP underestimates the quality of life for this patient based on their IDD and automatically excludes them from consideration for an organ transplant.

Gender

Gender– Preference for one gender over the other.

Example: An infertility practice accepts a 35-year-old female patient with a history of infertility, and in-vitro fertilization is recommended. However, the physician refuses to provide treatment, alleging that their religious beliefs prevent them from performing the procedure for a lesbian.

Rationale: The physician holds an inherent gender bias against a patient with a sexual orientation that conflicts with their religious beliefs.

Halo

Halo– Focus on one positive feature about a person or service that clouds your judgment.

Example: A patient asks a pharmacist for a particular sleep aid advertised by a film star. The pharmacist cautions the patient about the contraindications of that product. However, the patient chooses their originally requested sleep aid.

Rationale: The patient believes the sleep aid spokesperson is honest, just like the film characters they portray.

Obesity

Obesity– Tendency to negatively react to a person's obesity.

Example: An obese teenager receives physical therapy (PT) for back pain. The PT report indicates that the patient is non-compliant with exercise and makes little progress due to their weight. A follow-up x-ray indicates scoliosis with a 30-degree curvature of the spine.

Rationale: The PT report emphasizes negative feelings about the patient's obesity rather than the patient's clinical mobility status.

Racial

Racial– An automatic preference for one race over another.

Example: A Black adult patient with chronic neuropathy and complaint of significant leg pain for two days presents to the Emergency Department. Sobbing, the patient notes that the doctor's medicine never provides relief. The triage nurse believes the patient to be narcotic-seeking and determines that they can wait to be seen.

Rationale: Without completing an objective clinical assessment, the triage nurse believes this drug-seeking behavior is not unusual because the patient is Black.

Some strategies can be used to reduce these different forms of IB. They include the following:

  • Self-reflection can challenge self-perceptions and allow for increased awareness of bias.
  • Controlling strategies exist to control the response to stigma.
  • Stereotype replacement is recognizing that a response is based on preconceived stereotypes. By recognizing this, we can change our reactions.
  • Perspective-taking involves "putting yourself in the other person's shoes."

Legislation to Institutionalize Implicit Bias Training Across Health Professions and Care Settings

Recognizing the need to mitigate IB, address health disparities, and further ensure the quality of care provided by licensed healthcare providers among diverse populations, required IB health provider training is emerging across the United States. These laws empower policymakers, healthcare licensure boards, and healthcare settings to improve health professionals' IB knowledge to effect positive change in care systems. Likewise, they present opportunities for data collection to measure IB changes and evaluate patients' health outcomes over time. The following list includes examples of recent legislation to address IB in professional healthcare:

  • In 2019, California enacted the California Dignity in Pregnancy and Childbirth Act, the first US State to require IB training for perinatal healthcare professionals. The law also mandates State reporting requirements to track outcomes for pregnant women and hospitals and birthing centers to provide information on how patients can file discrimination complaints (Office of the Attorney General, 2021).
  • In 2021, the State of Illinois amended its mandatory child abuse and neglect reporter requirements, including healthcare professionals to complete one hour of training on IB awareness per licensure cycle beginning in 2022 (Illinois General Assembly, 2022).
  • In 2021, the State of Michigan enacted landmark legislation that mandates licensed healthcare providers to complete regular implicit bias training to obtain or renew their licenses beginning in 2022 (Governor Gretchen Whitmer, 2021).
  • In 2021, the State of New Jersey passed requirements for all healthcare professionals who provide perinatal treatment and care to pregnant persons at a hospital or birthing center to undergo explicit IB training (State of New Jersey, 2021).
  • In 2022, the State of New York signed into law amendments to Social Services Law § 413, requiring Mandated Reporters of child abuse and maltreatment to receive implicit bias-specific training within their child abuse Mandated Reporter training content (NYS, 2022).

Diversity, Equity, & Inclusion (DEI) In Healthcare

It is clear that the patients and clients we work with and care for every day are from diverse backgrounds. One conscious effort being put forth in many workplaces across the country to work to mitigate IB and strengthen the healthcare workforce is that of the adoption of the diversity, equity, and inclusion (DEI) initiative. One strategy that can help in supporting workplaces, namely medical organizations, while also supporting the communities that these workplaces and medical organizations serve is by incorporating DEI values.

Diversity: This includes a thorough understanding and appreciation of the background of all of an organization’s employees and patients who are served. Background includes all factors such as gender, culture, sexual orientation, socioeconomic status, and religious beliefs (Baker, 2023).

Equity: Equity, or being fair or impartial, is an emphasis on ensuring healthcare professionals have all that they require to do their jobs every day and that all patients have all that they require to benefit from the best practices for their treatment (Baker, 2023).

Inclusion: This features the necessity that all employees are important and should be heard and all patients and entitled to receive high-quality care in all circumstances (Baker, 2023).

The idea behind DEI is an emphasis on building a diverse community of professionals working for an organization that represents and understands all cultures, ethnicities, races, and backgrounds to allow for a deeper insight into how best to serve these communities of individuals (American Hospital Association, 2022). It is important that all levels of individuals within an organization, especially the leaders, are diverse, inclusive, and representative of the patients and communities they serve (American Hospital Association, 2022). Having an inclusive environment to work in is also beneficial to employees as it can create an increased sense of belonging, allowing for better retention of staff when they feel valued and heard (American Hospital Association, 2022).

While many organizations and businesses across the country are making changes in support of DEI initiatives, healthcare organizations arguably hold some of the most importance in this movement, as DEI can directly and overwhelmingly affect overall patient outcomes and lead to an improvement in quality of life (Baker, 2023). Education about IB and how to mitigate it is among the valuable information to be learned when providing employees with DEI training and putting the DEI mindset into practice in the healthcare environment (Baker, 2023).

Communication

Communication is a form of self-concept, and when performed with intention and clarity, it is very effective. Unfortunately, communication can also be harmful and detrimental. It is important to implement communication techniques to avoid misinterpretation or miscommunication.

Cross-cultural communication, also called intercultural communication, involves basic elements of communication, including specific language, preparedness, openness, and awareness. Cross-cultural communication promotes inclusion while breaking down cultural barriers. Effective and intentional cross-cultural communication aims to change how language is delivered across various backgrounds (Aririguzoh, 2022).

In healthcare, effective cross-cultural communication can lead to increased cultural competence. Many healthcare professionals can use the LEARN model to build cultural competence, enhance communication, and increase the quality of patient care and interactions (Ladha et al., 2018):

Listen: Assess the patient's understanding of health and disease. Providers should have humility and be curious, which promotes foundational trust.

Explain: Convey health perceptions without bias and be open-minded to others' understanding of health based on culture.

Acknowledge: Respect the differences in views, perspectives, and understandings.

Recommend: Propose and develop a care plan through understanding, support, and collaboration.

Negotiate: Incorporate culturally relevant interventions in partnership with the patient.

Case Study

Scenario/Situation/Patient Description

A 32-year-old Black female, Sarah, is being transferred to the post-partum unit following the birth of her first child, Grace. She had a relatively simple pregnancy without any complications. Her birth included 16 total hours of labor, a straight-forward epidural, and an uncomplicated vaginal delivery. About six hours after being moved into her post-partum room, she starts feeling some pressure in her chest.

The next time the nurse came to check on her, Sarah reports the chest pain she was experiencing. Her nurse tells her it likely was just anxiety now that she is a new mom.

Two hours later, Sarah presses the call button. When the nurse comes to check on her, Sarah complains again, now saying that her chest pain is getting worse. The nurse continued to downplay her symptoms, saying that it was probably nothing, that it would go away, and that no intervention or pain relief was indicated or needed.

Upon discharge, Sarah mentioned the chest pain she had been having to her provider. Her doctor echoes what the nurse has been saying and reassures her that it is likely nothing cardiac-related due to her age and overall good health. He simply tells Sarah to try to relax and focus on caring for her new baby. Because she trusts her doctor and nurse’s medical expertise, Sarah shrugs off her concerns, and she and her baby are soon discharged home.

Intervention/Strategies

Sarah has been home with her family for four days. Her chest pain has continued to worsen, now impacting the care she is able to provide for her new baby. David, Sarah’s husband, is very concerned about her. He calls their primary care provider, Dr. Patterson, who asks Sarah to come in. Dr. Patterson was immediately concerned upon his physical examination. He ordered an EKG and stat bloodwork. When Sarah’s cardiac enzymes came back as extremely elevated, and her EKG was pointing to possible ischemia, Sarah was rushed to the emergency room.

Soon after reporting to the emergency room, Sarah underwent additional diagnostic tests that confirmed a diagnosis of spontaneous coronary artery dissection (SCAD), a life-threatening heart condition. She required immediate placement of three cardiac stents. Without the quick thinking of her primary care provider, Sarah likely would have died.

Discussion of Outcomes

Black mothers in the United States are three to four times more likely to suffer a pregnancy-related death when compared to White mothers (CDC, 2024; Meadows-Fernandez, 2023). There are multiple factors that the research is finding that contribute to this disparity, including variation in healthcare quality, underlying chronic health conditions, individual and structural racism, and implicit bias (CDC, 2024; Josiah et al., 2023). Implicit bias can influence healthcare professionals to downplay and discredit pain, dismiss symptoms, and disregard evidence-based protocols (Josiah et al., 2023). Specifically, in regards to pain, there have been historical myths that Black patients did not experience pain the same way as other races (Josiah et al., 2023). In fact, in the 19th century, Black women were the routinely unanesthetized test subjects for new gynecological procedures (Gillette-Pierce et al., 2022).

This clinical situation is a case demonstration of implicit bias. A physical examination or additional investigation was not done to rule out a potentially life-threatening condition, and her pain was downplayed and written off as something else each time. The perceived dismissal of concerns of legitimate symptoms is often to blame for poor birth outcomes and mortality of Black women (Saluja & Bryant, 2021). This scenario also features a bit of “provider bias,” which is prejudiced and stereotyped assumptions about a patient and what is in their best interest (Mann et al., 2021). One could also argue that the doctor immediately agreeing with the nurse’s thoughts about Sarah’s pain without asking additional questions or doing any further investigation is an example of conformity bias.

Although this case could maybe have been handled by these healthcare professionals in the same way for a woman of a different race, the fact is that the statistics show that situations very similar to this are happening to Black women more often than others (CDC, 2024; Josiah et al., 2023). This is an example of racial implicit bias (CDC, 2024; Josiah et al., 2023). Although the nurse and doctor were likely wonderfully kind, experienced, and had the purest of intentions, they likely have their own implicit biases that require some deep self-reflection to prevent a situation like this, in which proper medical intervention was delayed, from happening again.

Reflection

Typically, and in most cases, healthcare professionals intend to provide optimal care to all patients, but implicit bias may negatively impact their aim. Implicit bias is the human tendency to make decisions outside of conscious awareness and based on inherent factors rather than evidence (Fitzgerald & Hurst, 2017).

Conclusion

IB is the unconscious and, therefore, the unintentional human tendency to make decisions based on inherent factors rather than evidence. No one is immune, not even healthcare professionals. Recognizing common types of IB by building self-awareness and participating in voluntary or mandatory training are steps health professionals may take to minimize its impact on their care. Likewise, State governments' mandates specific to IB in healthcare are embedding training across health professions and care settings into law. More research is needed to measure how IB training may change health providers' short- and long-term beliefs, practices, and patients' perceptions. Ultimately, these steps are intended to minimize IB among healthcare providers, reduce barriers to equitable care, close the gap in health disparities between diverse populations, and meet patients' needs.

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Implicit Bias Statement

CEUFast, Inc. is committed to furthering diversity, equity, and inclusion (DEI). While reflecting on this course content, CEUFast, Inc. would like you to consider your individual perspective and question your own biases. Remember, implicit bias is a form of bias that impacts our practice as healthcare professionals. Implicit bias occurs when we have automatic prejudices, judgments, and/or a general attitude towards a person or a group of people based on associated stereotypes we have formed over time. These automatic thoughts occur without our conscious knowledge and without our intentional desire to discriminate. The concern with implicit bias is that this can impact our actions and decisions with our workplace leadership, colleagues, and even our patients. While it is our universal goal to treat everyone equally, our implicit biases can influence our interactions, assessments, communication, prioritization, and decision-making concerning patients, which can ultimately adversely impact health outcomes. It is important to keep this in mind in order to intentionally work to self-identify our own risk areas where our implicit biases might influence our behaviors. Together, we can cease perpetuating stereotypes and remind each other to remain mindful to help avoid reacting according to biases that are contrary to our conscious beliefs and values.

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