Background

With age, along comes a range of musculoskeletal diseases that are known to contribute to physical and economic burden ranging from fractures and sprains to unremitting pain, incapacitating arthritis, and joint replacements (World Health Organization, 2021). Musculoskeletal diseases can affect muscles, bones, joints, the spine, and connective tissue, often leading to functional limitations and debility (World Health Organization, 2021). The Global Burden of Disease Study 2019 data revealed musculoskeletal diseases (n = 1.71 billion people globally), specifically low back pain (n = 568 million people globally) as the most prevalent condition contributing to physical disability across 134 of 204 countries (Cieza et al., 2021). In fact, musculoskeletal diseases accounted for an astonishing aggregate economic impact of $882.5 billion between 2012 and 2014 (Yelin et al., 2019). The 107.5 million people with musculoskeletal conditions (United States Bone and Joint Initiative, 2014) filled 2.2 billion medication prescriptions; partook in 602 million physician visits, 484 million nursing and nonphysician provider visits, and 22 million hospital admissions (Yelin et al., 2019). Older adults (people >=65 years) made up 16% of the total population with a projected growth to over 21% by 2030 (Federal Interagency Forum on Aging-Related Statistics, 2020). The prevalence of health conditions, such as arthritis, continues to increase in adults 65 years and older, and can lead to limitations in function and self-care (Federal Interagency Forum on Aging-Related Statistics, 2020). However, the burden of these debilitating musculoskeletal diseases is not balanced across race and ethnicity (Ezomo et al., 2020; Lefebvre & Lavery, 2011).

Although prevalence of musculoskeletal diseases is similar in both underrepresented groups and non-underrepresented groups, the outcomes of these debilitation diseases are not balanced across race and ethnicity (United States Bone and Joint Initiative, 2014). For the purposes of this study, underrepresented groups include Asian, Black, Hispanic, Indigenous people, and Latinx. Although other groups are underrepresented, they were not identified in the studies included in this review. Underrepresented groups are at greater risk for adverse outcomes such as (1) major lower extremity amputation (Tan et al., 2020); (2) disparate provision of anesthesia and analgesia in total joint replacements (Zhong et al., 2021); (3) lower likelihood of being prescribed a disease-modifying antirheumatic drug for rheumatoid arthritis (Schmajuk et al., 2011; Suarez-Almazor et al., 2007); and (4) lower likelihood of being diagnosed with a spinal disc injury, undergoing surgery, and receiving appropriate legal settlements associated with occupational back injuries (Tait et al., 2004). Racial and ethnic health and healthcare disparities are well-documented across a broad spectrum of healthcare conditions such as coronavirus disease complications (Metra et al., 2021), cardiovascular health (Sidhu et al., 2020), maternity care (MacDorman et al., 2021), and telehealth access (Curtis et al., 2021). In 2003, the Institute of Medicine (now referred to as the National Academy of Medicine; Institute of Medicine, 2003) acknowledged racial and ethnic health disparities as a national public health crisis, while concluding in their 10-year follow-up summary (Institute of Medicine, 2012) that "the gap between [racial and ethnic] groups remains constant" (p. 7). Their follow-up study How Far Have We Come In Reducing Health Disparities? (Institute of Medicine, 2012) identified racial discrimination as a substantive cause of race-based health disparities for underrepresented groups.

Racial discrimination occurs when members of one race provide differential or unfair treatment to members of another race with an intention to harm (Pincus, 1996). Although discrimination is intentional, biases can be either intentional (explicit) or unconscious (implicit). Explicit biases are a person's conscious thoughts and values, whereas implicit biases are unconscious and can be contrary to their declared values (Dovidio et al., 2002; Sabin et al., 2009). A person may not believe themselves to be biased but may have unconscious thoughts leading to biased behaviors (Dovidio et al., 2002; Sabin et al., 2009). Discrimination and biases take on many forms (i.e., appearance, sex/gender, sexual orientation, religious affiliation, disability status, race, and any other marginalized status). Those who have experienced discrimination and/or biases may, as a result, feel unsafe seeking assistance from the police or healthcare providers (Bleich et al., 2019; Harvard T.H. Chan School of Public Health, et al., 2018). Other negative outcomes may include income gaps (Bleich et al., 2019), disparate physical health (Bower et al., 2018; Gonzales et al., 2014; Larsen, 2021), and poorer mental health (Ferdinand et al., 2015). Current literature calls attention to the inherent value of considering racial discrimination and implicit biases based on race as potential factors in racial and ethnic health disparities (Bleich et al., 2019; Ferdinand et al., 2015; Harvard T.H. Chan School of Public Health, et al., 2018; Hoffman et al., 2016; Sabin et al., 2009). The purpose of this integrative review is to summarize the evidence on the relationship among racial discrimination, race-based implicit biases and other types of biases (e.g., gender and appearance), and orthopaedic-related outcomes. The research question is: What is the relationship among racial discrimination, race-based biases, and orthopaedic-related outcomes? The findings may contribute to emerging knowledge about the associations between racial discrimination and unconscious biases on health outcomes.

Methods

Design

This integrative review was conducted according to Jackson's (1980) six-step methodological framework: (1) select a research question, (2) sample studies for review, (3) represent characteristics of the studies, (4) analyze the studies, (5) interpret the results, and (6) and report the review. Jackson (1980) proposed that the six-step method offers clarity for readers to generate their own judgments about the primary studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to ensure transparent reporting of the study review process (McGuinness, 2021).

Study Selection and Search Method

Inclusion criteria for this review included studies (a) written in the English language, (b) published between January 1970 and July 2021, (c) focused on racial discrimination, race-based implicit biases, and other types of biases (e.g., gender and appearance) linked to orthopaedic-related outcomes (including but not limited to fractures, sprains/strains, arthritis, joint replacement, back or neck pain, and connective tissue disorders such as rheumatoid arthritis), and (d) included participants 18 years and older. To be included in this review, studies had to measure either racial discrimination or race-based biases. Some studies that measured racial discrimination or race-based biases also measured other forms of biases; these studies were included in the review. Prevalence studies of orthopaedic outcomes were not included because there were no measures of racial discrimination or raced-based bias. Studies were excluded if they focused on racial discrimination or race-based biases only linked to mental health outcomes, were not linked to orthopaedic-related outcomes, were in a language other than English, or sampled participants younger than 18 years. Our search range was selected to include extant literature beginning with Chester Pierce's (1970) landmark introduction of the term "macroaggressions" as overt discriminatory acts and his 1974 seminal conceptualization of "microaggressions" as harmful unconscious biases (Pierce, 1974). Thus, our search spanned the time between January 1970 and July 2021. The review was limited to published peer-reviewed studies. Databases and search terms are in Table 1.

Table 1. Keyword Search Query

Search Outcomes

The online database search uncovered 156 studies and two additional studies were found through hand searching reference lists. Two researchers blindly screened studies for eligibility, and a third researcher assisted in resolving conflicts. A total of 122 studies were ineligible, 21 duplicates were removed, and 13 studies met inclusion criteria for full text review. The 122 screened studies were ineligible after title and abstract review because they did not measure racial discrimination or race-based biases. Instead, they exclusively focused on racial discrimination and race-based biases linked to mental health outcomes, were descriptive studies, or did not sample participants from the orthopaedic population. The full text review yielded four studies that were excluded because they did not measure racial discrimination or race-based biases (see Figure 1).

Figure 1. Preferred Reporting Items for Systematic Review and Meta-Analyses flow diagram. From "The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews," by L. A.

Measures and Analytic Strategy

The fourth step of Jackson's (1980) six-step methodological framework is to analyze the primary studies for strengths and weaknesses, to assess participant characteristics, and consider causality of variables. In this review, Johns Hopkins nursing evidence-based practice, models and guidelines (Dang & Dearholt, 2018) evidence-leveling system, was used to assess the hierarchy of included studies. There are five rating levels assigned by Roman numerals, with Level I being the highest evidence rating reserved for randomized controlled trials, systematic reviews of randomized controlled trials, and explanatory mixed method studies with only Level I quantitative studies. Level II is for quasiexperimental studies, systematic reviews of a combined randomized controlled trial and a quasiexperimental study, and explanatory mixed method studies with only Level II quantitative studies. Nonexperimental studies, systematic reviews of a combination of study designs (e.g., quasiexperimental and nonexperimental studies, or only nonexperimental studies), explanatory mixed-methods studies with only Level III quantitative studies, or qualitative study meta-synthesis designs are assigned to Level III. Clinical practice guidelines and position statements are Level IV. Level V is the lowest rating and it is assigned to integrative reviews, literature reviews, case reports, expert opinions, and quality improvement reports. Consistent with these methods, data were extracted from the nine included studies, strengths and weaknesses were analyzed, and relevant information was populated into a table (see Table 2). All three authors collaborated to categorize data from the eligible studies.

Table 2. Summary of the Literature Review

Results

Methodological Characteristics of Included Studies

Eight of the nine studies in this review were cross-sectional, and one of the nine studies was a qualitative grounded theory design. All nine studies received a Level III ranking. Of the eight studies that used quantitative cross-sectional designs, five were secondary data analyses. Two of the cross-sectional studies randomly assigned participants to clinical vignette-based interventions (Dy et al., 2015; Oliver et al., 2014). Random assignment minimizes selection bias and decreases the probability of chance outcomes (Suresh, 2011). Eight studies collected data through survey instruments (Dy et al., 2015; Edwards, 2008; Goodin et al., 2013; Herbert et al., 2017; McClendon et al., 2021; Oliver et al., 2014; Walker et al., 2016, 2018), with three studies using investigator-developed instruments (Dy et al., 2015; Edwards, 2008; Oliver et al., 2014). Internal consistency reliability of research measures for five out of eight studies that did not use investigator-developed survey instruments ranged from 0.70 to 0.93 (Herbert et al., 2017; McClendon et al., 2021; Oliver et al., 2014; Walker et al., 2016; Walker et al., 2018). Oliver et al. (2014) combined the Implicit Association Test (IAT) with an investigator-developed clinical vignette and questionnaire. The IAT has various adaptations with a Cronbach [alpha] ranging from 0.70 to 0.90 (Schnabel et al., 2008). A weakness is that internal consistency reliability was not reported by investigators of included studies who developed their own survey instruments. Authors in the qualitative study collected data through semistructured interviews (Thurston et al., 2014). Semistructured interviews allow investigators to capture participants' lived experiences through their own lens. Although the interview data can have rich depth, it is not generalizable (Denny & Weckesser, 2019).

Study Design and Sample Characteristics

A summary of study characteristics is listed in Table 2. Seven of the nine studies were conducted in the United States (Alabama, Florida, New Mexico, New York, Pennsylvania, Texas, and Virginia) (Dy et al., 2015; Edwards, 2008; Goodin et al., 2013; Herbert et al., 2017; McClendon et al., 2021; Walker et al., 2016, 2018). One study was conducted in Canada (Thurston et al., 2014) and the last study recruited online participants through the nation-wide volunteer participant pool at the Project Implicit website (Oliver et al., 2014).

In seven of the nine studies, data were collected from patients who identified as having orthopaedic-related disorders (Edwards, 2008; Goodin et al., 2013; Herbert et al., 2017; McClendon et al., 2021; Thurston et al., 2014; Walker et al., 2016, 2018). In three of the nine studies, data were collected from healthcare providers in the following disciplines: nursing, physical therapy, occupational therapy, primary care physicians, and specialty care physicians (orthopaedic surgeons and rheumatologists) (Dy et al., 2015; Oliver et al., 2014; Thurston et al., 2014). In one of the nine studies, data were collected from patients and healthcare providers (Thurston et al., 2014). Across all 9 studies, the sample sizes varied drastically, from 31 to 3,397 and participants ages ranged from 25 to 85 years. One study did not disclose the healthcare provider-participants ages (Thurston et al., 2014). Two studies exclusively focused on women (Walker et al., 2016, 2018). Among the remaining studies, female participation ranged from 5% to 75%, and male participation ranged from 25% to 95%. No studies reported nonbinary participant identity.

Researchers in four of the nine studies exclusively recruited Black and White participants (Edwards, 2008; Goodin et al., 2013; Herbert et al., 2017; McClendon et al., 2021). The sample ranged from 7% to 62% for Black participants, and from 38% to 93% for White participants. In two of the nine studies, recruitment was limited to Black women (Walker et al., 2016, 2018). Dy et al. (2015) recruited a diverse sample from Black, Latinx, and White identities, as well as participants who selected "other" as their racial category. The racial composition of participants in the study conducted by Oliver et al. (2014) was also diverse with representation from Alaskan, American Indian, Asian, Black, Latinx, White, and mixed identities. Researchers in one of the nine studies recruited healthcare providers with undisclosed racial and ethnic identities, and patients with Indigenous First Nations, Metis, and Inuit identities (Thurston et al., 2014). Table 2 also summarizes results extracted from each study. Results were grouped into three categories: (a) perceived racial discrimination, (b) racial biases, and (c) other biases.

Perceived Racial Discrimination

Seven of the nine studies in this review examined perceived racial discrimination. One of the seven studies explored perceived racial discrimination experienced in healthcare settings for Indigenous Peoples with osteoarthritis (OA) or rheumatoid arthritis and found perceived racial discrimination as a deterrent to seeking arthritic care (Thurston et al., 2014). An overarching theme of this qualitative research study was that patients cope by "toughing out" their arthritic pain and were deterred from seeking care due to their racial discriminatory experiences in the healthcare setting. Another of the seven studies investigated perceived racial discrimination and low back pain in Black and White adults and found that lifetime racial discriminatory occurrences, across all settings of life, were associated with low back pain in Black men and Black women (Edwards, 2008). Daily racial discriminatory experiences (such as being treated with less respect than other people, being harassed or insulted, or receiving poorer service than others due to race) were associated with low back pain for Black women, but not for Black men. Perceived racial discrimination was not correlated with low back pain for White participants (Edwards, 2008).

Four studies examined perceived racial discrimination and depression. Two of these four studies found depressive symptoms mediated the relationship between perceived racial discrimination and disability (Walker et al., 2016), and pain (Walker et al., 2018) in Black women with OA. One of the four studies found cumulative disadvantage (the intersection of female gender, Black race, annual income <$20,000, high school education, and/or unemployment related to disability) correlated with perceived discrimination, pain, and depression in Black women with knee OA (McClendon et al., 2021). Participants in the study conducted by McClendon et al. (2021) cited race (26%) as the predominant reason for perceived discrimination. The final study in this category revealed that not only did Black participants report greater perceived racial discrimination and depressive symptoms, but their perceived racial discrimination was associated with greater mistrust of medical researchers (Goodin et al., 2013). There were no significant findings for White participants.

Two of the seven studies examined the association of perceived racial discrimination with experimental pain. Experimental pain is defined as pain (thermal, chemical, etc.) that is reproduced in the laboratory under controlled settings to allow assessment of pain pathways (Reddy et al., 2012).

Investigators in the first study induced cold-related pain in the laboratory setting in Black and White participants with knee OA and found that perceived racial discrimination was not correlated with cold pain tolerance in Black or White participants, and there were no ethnic differences in the perception of pain intensity (Herbert et al., 2017). Investigators in the second study induced heat-related pain in the laboratory setting in Black and White participants with knee OA. Perceived racial discrimination was inversely correlated with heat pain tolerance for Black but not for White participants, and Black participants reported greater baseline knee pain over the 48 hours prior to experimental heat application (Goodin et al., 2013). Laboratory-induced pain in both studies was not correlated with clinically reported pain.

Racial Biases

The concept of race-based bias was a focal area of three studies (Dy et al., 2015; Oliver et al., 2014; Thurston et al., 2014). In two of those studies, the sample was exclusively physicians who identified their race as American Indian, Asian/Pacific Islander, Black, Hispanic/Latinx, White, and mixed race. The physician-participants viewed a control patient's video vignette prior to completing an investigator-developed questionnaire in one study (Dy et al., 2015), and they viewed an online clinical vignette and took the IAT prior to completing an investigator-developed questionnaire and explicit bias survey in the second study (Oliver et al., 2014). Researchers in both studies found no association between patients' race and recommendation for a total knee arthroplasty in Black and White patients with knee OA. Findings from Oliver et al. (2014) further revealed no association between race and total knee arthroplasty recommendation even when restricting the sample to White physicians. An unexpected finding was that physicians implicitly and explicitly preferred White to Black patients. Even beyond the clinical setting, the physicians in the study explicitly preferred White to Black people. Physicians in the study associated the concept of "medical cooperativeness" with White patients, and had significantly higher feelings of warmth toward White people than Black people. Providers in the study by Thurston et al. (2014) viewed their Indigenous patients with OA and rheumatoid arthritis as having knowledge, cultural, and resource deficits leading to lack of "buy-in" with their arthritic care and provider recommendations. These providers viewed patients' poor conditions as being a result of the patients' actions and inactions. The Indigenous patient view of healthcare was shaped by their interactions with healthcare providers.

Other Biases

The relationship between other biases and orthopaedic-related outcomes was examined in four studies (Dy et al., 2015; Edwards, 2008; McClendon et al., 2021; Oliver et al., 2014). Two of these studies also measured racial discrimination and those findings are reported earlier. Two of the four studies found that gender-related bias toward participants was not associated with the recommendation for a total knee arthroplasty (Dy et al., 2015; Oliver et al., 2014). In the third study, Edwards (2008) reported gender and appearance as reasons for participants' perceived discrimination leading to their increased low back pain. The fourth study revealed an association among perceived gender, physical disability, and education discrimination toward participants and their increased knee OA pain for Black and White men and women (McClendon et al., 2021).

Discussion

The aim of this integrative review was to examine evidence surrounding the relationships among racial discrimination, race-based implicit biases, and orthopaedic-related outcomes. Nine studies met inclusion criteria and were grouped into three interrelated categories: perceived racial discrimination, race-based biases, and other biases. Seven of the nine studies reported on the relationships among racial discrimination, race-based biases, and patient outcomes; however, two of the seven studies concluded that race-based biases were not associated with orthopaedic-related outcomes. Four studies also examined other biases such as gender, appearance, physical disability, and education.

The prevalence of orthopaedic conditions is projected to increase (Federal Interagency Forum on Aging-Related Statistics, 2020), and there is an increased likelihood that orthopaedic-related outcomes will continue to exert detrimental effects on health and health outcomes such as physical disability. Disability increases with age and results in loss of independence, greater immobility, and less ability to perform self-care (Federal Interagency Forum on Aging-Related Statistics, 2020). Orthopaedic conditions, such as arthritis, encumber those who are stricken and, at times, devastate their quality of life (Chen et al., 2020). Orthopaedic conditions can also lead to an early transition out of the workforce (Cieza et al., 2021), and leave individuals grappling with perpetual pain management. It is critical for healthcare professionals to ensure that discriminatory behavior and biases do not inform orthopaedic patient care such as pain management.

Pain was cited as a being associated with racial discrimination and raced-based biases across the majority of included studies (n = 7), and this is consistent with current literature on pain-related outcome disparities for underrepresented groups. Pain in any form can become so significant that it impairs mundane daily tasks, limits functional mobility (Hooten et al., 2012), and contributes to mental health challenges (Chen et al., 2020; Hooten et al., 2012); however, Black patients tend to report more pain-related limitations (Hooten et al., 2012). In a recent study of participants with knee OA, Black participants reported more severe knee pain symptoms and limitations in their activities of daily living than their White peers (Simkin et al., 2021). Hooten et al. (2012) further reported that Black participants with chronic pain had greater pain severity, diminished functioning, and depression before and after completing a multidisciplinary 3-week outpatient pain rehabilitation program in comparison to White participants. Overcoming these disparate outcomes is further challenged by the inequities in the distribution of analgesics by healthcare providers to Black and Hispanic patients for pain management (Dominick et al., 2004; Drweck et al., 2011; Terrell et al., 2010).

Drwecki et al. (2011) conducted a study with 40 nurses and found that they exhibited pain-related treatment biases favoring White patients. Similarly, Black patients were less likely to be prescribed opioids and, when they were prescribed opioids, received a lower mean annual days' supply of opioids for OA as compared with White patients (Dominick et al., 2004). In the emergency department, Black and Hispanic patients received fewer prescribed opioids upon discharge for non-fracture-related musculoskeletal disorders in comparison to their White peers (Terrell et al., 2010). Unfortunately, provider biases are not limited to prescribing patterns.

Implicit and explicit biases can shape how healthcare providers view and interact with their patients. A study in this review found that physicians reported equal explicit perceptions of cooperativeness for Black and White patients. This is in contrast to a study by Green et al. (2007) that uncovered an implicit association of uncooperativeness with Black patients, and a reduced likelihood of the physicians recommending thrombolytic therapy for myocardial infarctions for Black patients. These results are consistent with other literature reporting provider biases such as physical therapists' tendency to prescribe fewer exercises when designing a home exercise program for Black patients compared with White patients with knee OA (Cavanaugh & Rauh, 2020), and overall healthcare providers' preference for treating White patients (Sabin et al., 2009).

Even though healthcare providers are held to egalitarian standards, their professional practice can reflect their personal biases-implicitly and explicitly. The Harvard T.H. Chan School of Public Health et al. (2018) research survey revealed how clinical biases mirror everyday life. For example, individuals of a variety of diverse groups (Asian Americans, Black Americans, Latinx, Native Americans, White Americans, lesbian, gay, bisexual, transgender, and queer community members) report facing discrimination when seeking healthcare, securing housing, and being approached by police. Women report unfair discrimination in relation to employment pay and promotion (Harvard T.H. Chan School of Public Health et al., 2018). These everyday biases can affect providers' thoughts about and communication with patients, thereby contributing to existing health disparities. Patients' lived experiences of biases and discrimination can lead to depressive symptoms (March et al., 2015), psychological distress (Ferdinand et al., 2015), and unintentionally erected barriers to establishing trusting relationships with their providers (Lewis et al., 2010). Lack of trust can further endanger the likelihood that diverse patients will complete provider-recommended treatment (Lewis et al., 2010) and can further widen outcome gaps. Participants were clear that experiencing racial discrimination in healthcare settings can be a deterrent to seeking care (Thurston et al., 2014).

Strengths and Limitations

This review highlights the gaps in research related to the relationship among racial discrimination, race-based biases, and orthopaedic-related outcomes. A strength of this review is that participants were recruited from more than one site in all nine included studies. Sampling participants from more than one site can improve the generalizability of outcomes (Tipton & Matlen, 2019). There are several limitations in this integrative review. Eight out of the nine studies used cross-sectional methodology. Cross-sectional designs help researchers gain information about outcome prevalence, but they are limited in determining causality (Setia, 2016). Future researchers should consider longitudinal methodology to better assess the relationship among racial discrimination, raced-based biases, and orthopaedic related-outcomes over time (Salkind, 2010). A second limitation is that the sample was not representative of individuals who typically experience racial discrimination and race-based biases. Dy et al. (2015) and Edwards (2008) conducted studies with samples composed of 83% and 93% of White participants, respectively. It is possible that individuals perceive and experience discrimination differently (Pew Research Center, 2016), and thus there is value in learning about these experiences from diverse perspectives. A third limitation is that there were only nine articles that met inclusion criteria. This speaks to the limited attention that has been given to examining racism and biases in orthopaedic care.

Implications for Orthopaedic Nursing

Orthopaedic nurses are well-positioned to champion change in a number of ways. A first step is to self-assess ones' own biases and acknowledge how they implicitly or explicitly contribute to clinical decision-making (Nardi et al., 2020). A next step is to diversify the orthopaedic nursing workforce. Diversification is a long-term process that starts with ensuring safe and positive working environments, recruitment, and training of nurses from underrepresented groups. Orthopaedic nurses should also generate opportunities for collaborative learning experiences and make way for nurses from underrepresented groups and diverse identities to serve in key leadership positions in nursing education, research, and practice (Moorley et al., 2020). Their lived experiences are a powerful tool for synthesizing diverse perspectives and will provide opportunities to identify and incorporate measures of discrimination in research studies. Schools of nursing need to incorporate concepts of racial discrimination, race-based biases, and other biases into academic and clinical nursing education (Nardi et al., 2020; Waite & Nardi, 2021). Student nurses and new graduates should be equipped with knowledge and tools to promote awareness of discriminatory and biased behavior in clinical settings. This work will prepare current and future orthopaedic nurses to command an active role in leading interprofessional healthcare teams through advocacy to change disparate orthopaedic-related outcomes across diverse groups.

Conclusion

Musculoskeletal diseases are not bound by race or ethnicity, but cross all demographic boundaries. There is a substantial body of evidence that reveals that underrepresented groups bear a greater burden of unsatisfactory orthopaedic-related outcomes. In this integrative review, only nine articles met inclusion criteria, so this study identifies a clear gap in the literature on the relationship among racial discrimination, race-based biases and other biases, and orthopaedic outcomes. Experiences of racial discrimination and race-based biases have the potential to further widen health and healthcare disparities and should be considered when designing research with aims to examine these unsatisfactory orthopaedic outcomes. Regardless of their unique identity, people deserve equitable treatment inside and outside of the clinical milieu.

References