≥ 92% of participants will gain awareness about implicit bias in healthcare and mitigation strategies.
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.
≥ 92% of participants will gain awareness about implicit bias in healthcare and mitigation strategies.
After completing this course, the learner will be able to:
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).
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).
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.
Racial and ethnic minority groups have experienced hardships for as long as anyone can remember.
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):
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):
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.
IB presents challenges in healthcare when it manifests itself inappropriately and unconsciously contributes to health disparities.
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).
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):
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.
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.
Unfortunately, with identity comes discrimination for the differences that set us apart.
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.
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:
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:
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– 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.
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– 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– 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.
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.
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– 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.
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– 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.
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.
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:
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.
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 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.
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):
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.
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.
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.
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.
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).
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.
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.