Version May 2024
INTRODUCTION — Inequities in health and health care are pervasive and have continued to plague the health care system despite increasing recognition among patients and providers of their existence. Inequities are defined as undesirable differences in outcomes or care and are generally not driven by informed differences in expressed patient preference. Meaningful and concerning inequities are prevalent in all spheres of health and disease. Inequities exist in both health outcomes and in health care and arise from myriad contributors, including socioeconomic factors, education, and environment. Inequities have been documented globally by patient race/ethnicity, sex, gender and sexual identity, religion, socioeconomic status, immigration status, and geography, among other characteristics. This topic will focus generally on inequities related to race/ethnicity in the context of female reproductive health and health care in the United States, as the United States' history of chattel slavery has resulted in unequal health care practices and resultant racial inequities in health-related outcomes.
Discussions of cross-cultural care and patient communication are presented separately:
●(See "The patient’s culture and effective communication".)
●(See "Use of race and ethnicity in medicine".)
In this topic, when discussing study results, we will use the terms "woman/en", "man/en", "patient(s)", and racial/ethnic descriptors as they are used in the studies presented. We encourage the reader to consider the preferred language as well as specific counseling and treatment needs of transgender, gender diverse, and underrepresented individuals.
BACKGROUND — Health results from a complex interplay of individual factors (eg, genetics, lifestyle), population group factors (eg, race and ethnicity, sex, sexual orientation, immigrant status), and social determinants (ie, conditions in which persons are born, grow, live, work, and age) [1-3]. Definitions of relevant terms are available in the table (table 1). While degree of health, disease risk factors, and access to health care are often intermixed and worsened by social, economic, and environmental disadvantages [4], these factors do not account for all gaps in health care outcomes and services noted among different populations [5]. Studies have reported that Black people are more likely to die of cardiovascular causes than White people [6], children living in poverty are more likely to be obese [7], and transgender men are less likely to have adequate Pap screening than are cisgender women [8]. Biologic variation and socioeconomic differences do not fully explain these discrepancies.
A health disparity population, as defined by the National Institutes of Health, is one in which there is "a significant disparity in the overall rate of disease incidence, prevalence, morbidity, or mortality in the specified population as compared with the general population" [1]. Within the United States, designated disparity populations include African Americans, Hispanic American, American Indians/Alaska Natives, Asian Americans, Native Hawaiians and Other Pacific Islanders, socioeconomically disadvantaged populations, underserved rural populations, and sexual and gender minorities [9]. Within the field of female reproductive health care, persons who are members of underrepresented racial and ethnic groups experience inequities in health outcomes and access to services [1]. As one example, non-Hispanic Black women have higher rates of preterm birth compared with White women even after adjustment for variables such as income [10,11]. These differences cannot be entirely explained by differences in income, housing, and education.
EXAMPLES OF INEQUITIES IN REPRODUCTIVE HEALTH — Racial inequities in reproductive health are well documented in obstetrics and gynecology and reflect both discrepant health outcomes and access to services.
Outcomes — Examples of outcome differences by racial/ethnic group include:
●Maternal death – Maternal death in the United States is more common in non-Hispanic Black women, compared with White women, and has been rising [12-17]. In one study of 13 million US live births between 2014 and 2018, this disparity existed in both low- and high-vulnerability settings [17]. In two analyses of data from the Centers for Disease Control and Prevention's national Pregnancy Mortality Surveillance System, Black American and American Indian/Native Alaskan women were two to three times more likely to die from pregnancy-related causes than White women [15,18]. Similar data have been reported for the United Kingdom [19].
A detailed discussion of race and both maternal mortality and morbidity is presented separately. (See "Overview of maternal mortality", section on 'Race and ethnicity'.)
●Severe maternal morbidity (SMM) – A study of United States deliveries between 2006 and 2015 reported that the rate of SMM (ie, a life-threatening event during pregnancy, delivery, or postpartum) was up to 115 percent higher for Black compared with White women, after adjustment for age mix, and did not change significantly during the study time period [20]. A different study of a United States inpatient database reported that, from 2012 to 2015, the incidence of SMM was significantly higher for every underrepresented racial and ethnic group compared with non-Hispanic White women [21]. After exclusion of cases in which blood transfusion was the only indicator of SMM, non-Hispanic Black women were 20 percent more likely to experience SMM compared with non-Hispanic White women (risk ratio 1.2, 95% CI 1.2-1.3). Among women with multiple medical and/or physical comorbidities, women of all underrepresented racial and ethnic groups were more likely to experience an SMM event compared with non-Hispanic White women. In a United States database study including over 11.3 million births between 2012 and 2014, when compared with non-Hispanic White women, non-Hispanic Black women were approximately 80 percent more likely to be readmitted postpartum and 16 percent more likely to have an SMM during readmission [22]. However, unlike the above studies, these differences were not found for other groups.
●Impact of postpartum hemorrhage – A retrospective cohort study of over 360,000 women with postpartum hemorrhage reported that, after adjusting for comorbidity, non-Hispanic Black women who experienced postpartum hemorrhage had a higher risk of severe morbidity and death compared with non-Hispanic White women [23]. The adjusted maternal mortality rates per 100,000 women were 121.8 (95% CI 94.7-156.8) and 24.1 (95% CI 19.2-30.2) for Black and non-Black women, respectively, with a relative risk for mortality of 5.1 (95% CI 3.6-7.1) for Black women. (See "Overview of postpartum hemorrhage", section on 'Risk factors for PPH'.)
●Preterm birth – A prospective study of over 9400 racially-diverse nulliparous women with singleton gestations across eight United States study sites reported that, even after adjusting for known confounders and self-reported measures of psychosocial stress, non-Hispanic Black women continued to be at higher risk for any category of preterm birth compared with non-Hispanic White women [11]. (See "Spontaneous preterm birth: Overview of risk factors and prognosis", section on 'Non-Hispanic Black or American Indian/Alaska Native race'.)
●Gestational diabetes – A study of the 2000 to 2010 United States State Inpatient Databases, which accounts for approximately 86 percent of hospitalizations nationally, reported that Hispanic women had the highest age-standardized relative increase in gestational diabetes diagnoses compared with other racial/ethnic groups (relative increase of 66 versus 54 percent [non-Hispanic White], 53 percent [non-Hispanic Black], and 58 percent [non-Hispanic Asian/Pacific Islander]) [24]. (See "Gestational diabetes mellitus: Screening, diagnosis, and prevention", section on 'Risk factors'.)
●Obstetric anal sphincter injury – A retrospective cohort study of over 22,700 deliveries in the Kaiser Permanente Northern California health care system reported that Asian women had double the risk of severe obstetric perineal lacerations compared with White, African American, or Hispanic women (incidence of 9.3 versus 4.2, 2.7 and 2.4 percent, respectively) [25]. (See "Obstetric anal sphincter injury (OASIS)".)
●Hysterectomy route and outcomes – For individuals undergoing hysterectomy for benign indications, including endometriosis, Black and other under-represented women are more likely than White women to have open surgery and experience surgical complications [26-29]. In a cohort study of over 15,000 United States women that adjusted for uterus size, prior pelvic surgery, body mass index, and other clinical variables, Black women, compared with White women, were twice as likely to undergo open surgery, and they experienced more major (4.1 versus 2.3 percent) and minor complications (11.4 versus 6.7 percent) [28]. In the subgroup of women undergoing laparoscopic hysterectomy in this study, Black women still experienced more complications compared with White women (3.3 versus 1.8 percent), which suggests that factors other than surgical route may be involved. The study was unable to evaluate practice patterns at the surgeon, hospital, and regional levels, which might provide further insight as to the sources of the disparate surgical approaches and outcomes.
●Cancer mortality
•Cervical cancer – In the United States, cervical cancer incidence and mortality is higher in Black or Hispanic women than in non-Hispanic White women [30]. In a retrospective review of over 44,500 United States women with cervical cancer from 1998 to 2007, Black women were nearly 10 percent more likely to die compared with White women (adjusted hazard ratio 1.09, CI 1.03-1.15) after adjustment for socioeconomic status and stage at diagnosis [31]. (See "Invasive cervical cancer: Epidemiology, risk factors, clinical manifestations, and diagnosis", section on 'Epidemiology'.)
•Breast cancer – Although Black women have a lower incidence of breast cancer compared with White women in the United States, their mortality is higher [32-34]. (See "Prognostic and predictive factors in early, non-metastatic breast cancer", section on 'Patient features'.)
-A propensity-matched study from the United States National Cancer Database reported that, among women with hormone receptor positive breast cancer, Black women had twice the risk of death compared with White women (hazard ratio 2.05, 95% CI 1.94-2.17) [35]. Over one-third of the excess risk of death was attributed to differences in health insurance.
-A study of over 1.3 million United States women diagnosed with breast cancer between 2001 and 2009 reported that survival for Black women was consistently 10 percentage points lower than for White women, and the difference persisted over time [36].
•Ovarian cancer – In a study of over 172,000 United States women diagnosed with ovarian cancer between 2001 and 2009, non-Hispanic Black women had consistently worse survival both by time interval and disease stage compared with White women, despite very similar distributions of cancer stages [37]. For overall survival (combined stages of disease), survival rates were 29.6 to 31.1 percent for Black women compared with 40.1 to 41.7 percent for White women (time periods 2001-2003 and 2004-2009, respectively).
•Endometrial cancer – Among women with endometrial cancer, the mortality risk is 55 percent higher for Black compared with White women (five-year mortality rates of 39 versus 20 percent, respectively) [38]. One reason for this disparity is that Black women are less likely to be diagnosed with early-stage disease [39]. However, the basis for later-stage diagnosis appears to be a result of improper evaluation rather than biologic cause. At least two studies have reported that Black women are less likely to receive guideline-concordant care, which is in turn associated with higher odds of advanced stage of disease at diagnosis [40,41].
Content or level of care received — While differences in health outcomes may be partially attributable to patient-level variables such as genetics or other biological constructs, it is harder to "explain away" differences in health care that occur once a woman has gained access to the health care system, particularly for interventions with standardized recommendations, such as health screening tests. However, there are numerous examples of obstetric and gynecologic conditions for which the type of care and level of care varies by patient characteristics in ways not easily explained by usual confounding variables.
Examples include:
●Health screening – Analysis of the 2015 United States National Health Interview Survey (NHIS) data reported that Native American Indian/Alaska and Asian women were least likely to be up to date with recommended screening for cervical cancer (women aged 21 to 65 year) or breast cancer (women aged 50 to 74 years) [42]. In contrast, both the NHIS study and a study from the 2011 to 2015 National Survey of Family Growth reported that the prevalence of mammography was higher among non-Hispanic Black women compared with almost all other groups [42,43].
●Hysterectomy – Two different studies of women who underwent hysterectomy reported that Black, Hispanic, and publicly-insured women were least likely to receive minimally invasive techniques (vaginal, laparoscopic, or robotic hysterectomy) compared with White women, even when eligible for minimally invasive techniques [44,45]. A study of data from the 2006 to 2010 TRICARE system, which provides universal insurance coverage to United States Armed Service members and their dependents, reported that Black women were approximately 35 percent less likely and Asian women were approximately 30 percent less likely to receive either vaginal or laparoscopic hysterectomy than White patients [46]. As all women were equally insured, differences in insurance status or coverage type could not have contributed to these findings.
●Ectopic pregnancy – In a study of over 62,500 women treated for ectopic pregnancy between 2006 and 2015, among the over 49,000 who underwent surgery, Black and Hispanic women were approximately 20 percent less likely to receive tube-conserving surgery (ie, salpingostomy) compared with White women [47]. In a study of over 3000 women covered by TRICARE insurance and treated for ectopic pregnancy between 2006 and 2010, rates of minimally invasive laparoscopy varied significantly by race (rates of laparoscopy: 33 percent [Asian], 35 percent [Black], and 42 percent [White]) [48]. As with hysterectomy, all women were equally insured, and thus insurance coverage should not have been an influencing factor.
●Contraception – A study of over 7200 women aged 15 to 44 years reported that, compared with White women, Black women were 35 percent less likely to use any contraception and Black and Hispanic women were approximately 50 percent less likely to use highly or moderately effective contraception (odds ratio 0.49 and 0.57, respectively) (figure 1) [49].
In addition, there is significant variation by race/ethnicity in fertility preservation counseling among women treated with gonadotoxic therapies for cancer diagnoses [50], diagnosis of endometriosis [51], treatment of postpartum pain [52], and, in prenatal diagnosis, the offer of screening and testing modalities [53,54].
SOURCES OF HEALTH INEQUITIES — Much consideration has been given to determining the sources of inequities in care delivered to women of different races and ethnicities [55]. Factors that contribute to health care inequities exist at the patient, clinician, health care system, and cultural levels (figure 2).
Patient — Differences in patient-level factors may play some role in contributing to differences in specific health outcomes or to differences in level or type of care received. For example, individuals with varying levels of education and health literacy may advocate for quality of care to different extents. Some may have culturally mediated preferences for certain treatments over others, although strictly speaking such differences, if derived from informed preferences, do not meet the definition of health care inequity.
Clinician and role of implicit bias — Clinicians may provide different levels of care to individuals of different racial/ethnic groups: Data suggest much of this bias is not explicit and that many providers are unaware of the prevailing inequities in their fields or their role in perpetuating them [56,57]. In addition, when the patient and clinician meet at the level of the clinical encounter, communication may be suboptimal and/or culturally insensitive.
For conditions and care in which inequities exist, the potential role of the individual clinician in contributing to imbalances is inescapable. While some clinicians may admit and demonstrate explicit preferences for certain groups over others, the greater threat to equal patient care occurs through implicit biases, or those pervasive and rapid judgments and attitudes that arise subconsciously and are informed by our own backgrounds and experiences [21,58]. Examples of implicit bias at work include:
●A study of 287 internal and emergency medicine residents who reviewed a clinical vignette of a patient presenting to the Emergency Department with an acute coronary syndrome reported implicit preference favoring White patients and implicit bias stereotyping Black patients as less cooperative with medical procedures and less cooperative generally [59]. As physician preference for White patients increased, the likelihood of treating White patients with thrombolysis and not treating Black patients also increased.
●A cross-sectional study that measured implicit general and race bias for 40 primary care physicians and 269 patients in urban community-based practices reported an association between preferences for White patients on the Implicit Association Test (IAT) and poorer health care communication and ratings of care, particularly among Black patients [60].
Possible strategies to address implicit bias on the part of the clinician are discussed below. (See 'Mitigation of implicit bias' below.)
Health care system — The experiences of patients and providers in the United States are housed in the broader structure of the health care system, which itself contributes to inequity [61,62]. The financing of American health care, despite reforms, leaves some women with minimal access to health services by virtue of no or underinsurance, and these women are more likely to be from underrepresented racial/ethnic groups [63,64]. In addition, access to specific technologies, such as assisted reproductive technologies or costly medications, may be tiered by insurance product, which further contributes to inequities in care rendered. A study of nearly 2500 women diagnosed with breast cancer in North Carolina from 2008 to 2013 reported that Black women were more likely than White to note any adverse financial impact of cancer at 25 months postdiagnosis (adjusted risk difference +14 percentage points), in an analysis adjusted for age, stage of disease, and treatment received [65].
Sociocultural context — Health care systems function within a broader sociocultural context that also includes the educational, financial, and criminal justice systems, among others. In 2018, the American College of Obstetricians and Gynecologists issued a Committee Opinion on the role of social determinants of health on health outcomes and care that acknowledged the important interplay between the structural elements such as health literacy, food insecurity, and poverty on women's health outcomes [2]. In addition, underlying structural racism operates beyond socioeconomic inequities. As an example, in a model designed to evaluate the association between community-level determinants of health and maternal health outcomes in the US, Black women experienced higher maternal mortality levels and worse obstetric outcomes compared with White women at all resource levels [17].
Additionally, there remains a legacy of mistreatment of patients of color within the health care system that appears to have impaired the development of patient trust and therapeutic alliances by women of color [66,67]. Forced sterilization of women [68] and the United States Public Health Service Syphilis Study at Tuskegee [69] are but two examples of abuses that continue to inform patients' beliefs about their treatment in the modern health care system [70].
STRATEGIES TO REDUCE HEALTH CARE INEQUITIES
Mitigation of implicit bias — While data on mitigation of bias come primarily from social science studies, these approaches may be applied in other settings, such as health care. Although supporting data specific to health care settings are lacking, the risk of intervention is low and the potential gain is high. Thus, we advise clinicians both in and beyond the United States consider these approaches.
Clinician preparation — As implicit biases operate below providers' awareness, it is difficult to both assess biases and the impact of mitigation strategies. Interventions to reduce bias have been proposed in the education and criminal justice arenas [71,72], but there are few published evidence-based strategies specific to health care. Within the social psychology literature, researchers have proposed three conditions as necessary for "de-biasing" [73,74]: (1) intention to change existing biases, (2) attention to one's own stereotypical responses, and (3) time to practice strategies required to break habitual associations.
As part of establishing intention, providers are encouraged to complete a self-assessment of their own unconscious biases. A commonly sourced tool is the Implicit Association Test (IAT) [75], a computer-based exercise designed to measure implicit biases of several types (eg, race, religion, disability, weight). This process sometimes produces surprising and unsettling results for participants, and the accuracy of the results may be doubted. Without a clear gold standard for comparison, the methodologic validity of the IAT has occasionally been called into question; however, the IAT remains widely accepted as a good approximation of unconscious biases.
Once providers have identified their implicit biases, they must work to lessen the effects of said biases through strategy-based interventions that are practiced on a regular basis. Proposed exercises include [73]:
●Stereotype replacement – The individual learns to recognize responses to an individual or scenario that rely on stereotypes, then actively replaces the biased response with an unbiased one.
●Counter-stereotypic imagining – After the individual learns to recognize his/her stereotypical response to an individual from a particular background, the individual then remembers interactions with other persons from the same background who counter the stereotype and prove it inaccurate.
●Individuating – The individual learns how to obtain specific details of a different person's background, likes, dislikes, family, work, et cetera, in order to better make judgements based on individual, rather than group, characteristics.
●Perspective-taking – The individual actively considers the perspective of a stereotyped person, which may facilitate understanding of the emotional toll borne by those often stereotyped.
●Increasing opportunities for positive contact – The individual actively seeks out opportunities to experience or be in contact with positive examples of stereotyped groups.
In an experimental context, participants who completed an intervention employing the above strategies reported both increased concern for racial biases and scored lower on the Black-White IAT for implicit biases against Black people, with changes that persisted over time [73]. Providers who demonstrated increased concern for discrimination after the intervention was delivered were most likely to benefit. This study suggests that health care providers will participate in a study that reveals personal unconscious biases and that they next try to recognize when biased responses threaten to emerge during clinical interactions.
Using these techniques of assessing levels of implicit bias followed by exercises may help to minimize related harms during interactions, ideally leading to improved clinical encounters and therapeutic relationships. However, long-term outcome data on this approach are not yet available.
Medical education — The need for bias-reduction instruction at the level of medical education is highlighted by the fact that, while under-represented persons comprise approximately 30 percent of the United States population, only 9 percent of medical doctors are themselves from underrepresented groups [76]. To reduce the harmful effects of unconscious bias in medical learners, at least one researcher suggests that learners engage in developmental processes, which make them increasingly aware of their unconscious biases and mechanisms to regulate them [77]. As with other clinical skills, the opportunity to practice is paramount and may be modeled by others further along in their own journeys to reduce bias. The use of reflection via writing or group discussion exercises can provide opportunities to evoke and counter stereotypes in simulated settings [78]. In a study that exposed participants to images of admired and disliked persons from different races, the participants demonstrated a decrease in automatic preference for White people when study participants were shown images of positive Black exemplar individuals [79]. This study suggests that medical learners, potentially including seasoned clinicians, may begin to "unlearn" their biases with increasing exposure to positive examples of members from groups most often affected by bias, whether through case simulation, actual patient exposure, or intentional immersive experiences. Other clinicians have described an approach that includes cultivating a team of "race consciously trained" faculty consultants, developing race-conscious curricula, and employing innovative and interactive methods of training that promote critical dialogue amongst learners [76]. Using tools to identify bias and performing exercises to mitigate stereotypes, whether in medical education and training or in clinical practice, may help to minimize bias-related harms during patient interactions and ideally lead to improved clinical encounters and therapeutic relationships.
Inquire about patient experience with bias — There are limited data on steps a clinician can take at the bedside or in the office to reduce harms associated with implicit bias. As one approach, the author suggests asking patients about perceived prior discrimination in the health care setting. Research in this area often uses a question from the Behavioral Risk Factor Surveillance System: "Within the past 12 months when seeking health care, do you feel your experiences were worse than, the same as, or better than for people of other races?" [80]. While the query is designed as part of surveys often used for investigational purposes, the question seems to have face and content validity and can easily be used in a clinical context. Clinician acknowledgment of positive responses, or otherwise recognizing cues that indicate mistrust or concern for care that is not culturally sensitive, can signal to caregivers a need to build trust and perhaps employ learned de-biasing strategies where appropriate.
System changes — The Council on Patient Safety in Women's Health Care, which develops maternal safety bundles to promote safe care, recommends in its "Reduction of Peripartum Racial/Ethnic Disparities" bundle that every health system provide staff-wide education on implicit bias, with a goal of implementing interventions to reduce these harmful biases [81]. Focus on standardized care practices or bundles may also be helpful. As an example, use of a standardized protocol for maternal hemorrhage among 99 hospitals in California resulted in reduction of severe maternal morbidity across all groups, with the greatest reduction in Black individuals [82]. (See "Overview of maternal mortality", section on 'Race and ethnicity' and "Severe maternal morbidity", section on 'Racial and ethnic minorities'.)
Other recommendations include ensuring access to adequate medical interpretation services and appropriate and granular collection of race/ethnicity data to inform quality efforts. Currently used quality metrics in obstetrics often focus on "overuse" measures, such as low-risk cesarean delivery, labor induction, and early elective delivery, and therefore may not fully capture outcomes for which women with poorer health care access may be at risk [83]. Efforts to collect quality data specifically designed to assess inequity (for example, use of interpreter services among patients of limited English proficiency, reporting of differences in offer of prenatal genetic screening by race/ethnicity, or allowing qualitative feedback from patients about experiences of discrimination in a health center or system) should be paired with more traditional measures of care quality.
In the broader context of the health care system, the financing of health care affects the distribution of resources and equity of outcomes. Women of low income are most likely to be covered by Medicaid during pregnancy but are vulnerable to insurance gaps before and after pregnancy [84]; such coverage transitions are associated with poorer access to and quality of care [85,86]. Removal of barriers to reproductive health services has been associated with reduction in adverse outcomes [87,88], which suggests that such efforts on a widespread basis may also be potential systems-level interventions to narrow inequities.
RESOURCES FOR PATIENTS AND CLINICIANS — Free open-access information for patients and clinicians can be found at the following sites:
●World Health Organization – Health Equity
●National Institutes of Health – National Institute of Minority Health and Health Disparities
●The Alliance on Innovation for Maternal Health (AIM) Council on Patient Safety in Women's Health Care provides education and tools to reduce maternal mortality
●The American College of Obstetricians and Gynecologists – Cultural Awareness and Sensitivity in Women's Health Care
SOCIETY GUIDELINE LINKS — Links to society and government-sponsored guidelines from selected countries and regions around the world are provided separately. (See "Society guideline links: Diversity, equity, and inclusivity in medicine".)
SUMMARY AND RECOMMENDATIONS
●Contributors to health and health disparity – Health results from a complex interplay of individual factors (eg, genetics, lifestyle), population group factors (eg, race and ethnicity, sex, sexual orientation, immigrant status), and social determinants (ie, conditions in which persons are born, grow, live, work, and age). While degree of health, disease risk factors, and access to health care are often intermixed and worsened by social, economic, and environmental disadvantages, these factors do not account for all gaps in health care outcomes and services noted among different populations. A health disparity population, as defined by the National Institutes of Health, is one in which there is "a significant disparity in the overall rate of disease incidence, prevalence, morbidity, or mortality in the specified population as compared with the general population." (See 'Background' above.)
●Inequities in reproductive health care – Racial and ethnic inequities are well documented in obstetrics and gynecology and reflect discrepant health outcomes and differential access to services as well as inequities in the quality of care delivered. (See 'Examples of inequities in reproductive health' above.)
•Inequities in health outcomes – Examples of inequities in health outcomes have been reported for maternal mortality, the sequelae of postpartum hemorrhage, and rates of preterm birth, gestational diabetes, obstetric anal sphincter injury, and cancer-related death. (See 'Outcomes' above.)
•Inequities in level or content of care – Examples of inequities in the level or content of care have been reported for health screening measures, use of minimally invasive hysterectomy, care of ectopic pregnancy, and contraception. (See 'Content or level of care received' above.)
●Contributing factors – Factors that contribute to health care inequities exist at the clinician, health care system, and cultural levels (figure 2). (See 'Sources of health inequities' above.)
•Clinicians and importance of implicit bias– Clinicians may provide different levels of care to individuals of different racial/ethnic groups: Data suggest much of this bias is not explicit and that many providers are unaware of the prevailing inequities in their fields or their role in perpetuating them. While some providers may admit and demonstrate explicit preferences for certain groups over others, the greater threat to equal patient care occurs through implicit biases, or those pervasive and rapid judgments and attitudes that arise subconsciously and are informed by our own backgrounds and experiences. (See 'Clinician and role of implicit bias' above.)
•Interplay of health care and other systems – Health care systems function within a broader sociocultural context that also includes the educational, financial, and criminal justice systems, among others. In 2018, the American College of Obstetricians and Gynecologists issued a Committee Opinion on the role of social determinants of health on health outcomes and care that acknowledged the important interplay between the structural elements such as health literacy, food insecurity and poverty, and women's health outcomes. (See 'Sociocultural context' above.)
●Implicit bias identification and mitigation – To help mitigate the role of implicit bias, clinical providers are encouraged to complete a self-assessment of their own unconscious biases. A commonly-sourced tool is the Implicit Association Test (IAT), a computer-based exercise designed to measure implicit biases of several types. To reduce the harmful effects of unconscious bias in medical learners, it has been suggested that learners engage in processes to make themselves aware of their unconscious biases and mechanisms to regulate them. Data are needed to determine the efficacy of such programs. (See 'Mitigation of implicit bias' above.)
●System-level changes – To reduce health care discrepancies at the system level, staff-wide education on implicit bias is encouraged, with a goal of implementing interventions to reduce these harmful biases. Other suggestions include ensuring access to adequate medical interpretation services and appropriate and granular collection of race/ethnicity data to inform quality efforts. (See 'System changes' above.)
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