Clinical Orthopaedics and Related Research® is proud of its long history of support for work that promotes fairness to musculoskeletal professionals and the patients we treat. CORR® has published five symposia covering disparities—with topics related to sex and gender, race and ethnicity, education, and affluence—in the last 10 years, including a hard-hitting issue on the topic last month , and we expect to continue to do this going forward. We also are proud of our strong official-journal relationships with the J. Robert Gladden Orthopaedic Society and the Ruth Jackson Orthopaedic Society. CORR continues to support these societies’ missions in word and deed.
We’re well aware, and we have written before, that studies about disparities, and in particular studies in which race or ethnicity is a variable of interest, are difficult to do well [8, 11]. But doing them poorly is no longer an option. Too many studies about healthcare disparities in our specialty have attributed findings to race without also considering potentially relevant sociodemographic variables. Several widely available metrics now permit researchers to take those variables into account; these include the Distressed Communities Index , the Social Vulnerability Index , and the Area Deprivation Index . Depending on a study’s topic of interest, controlling for other related sociodemographic variables commonly associated with race may also be informative.
Going forward, CORR will insist that authors use tools like those when it is appropriate to do so, since skipping that key step risks attributing to race or ethnicity what is more likely to be caused by (or associated with) other sociodemographic attributes, typically—although not always—economic want.
Last month, several papers made it clear how important it is to do this [6, 7, 13]. We went deep with the senior author of one of those papers  in our Editor’s Spotlight/Take 5 section ; the interview with that author, in particular, is worth your attention. Discrimination’s terrible legacy in the United States is that race and poverty too often remain linked in this country. However, that link is not so inextricable as it once was, and if studies fail to look at these factors separately, they risk misattributing findings and misdirecting our solutions. The three papers in last month’s symposium that we mentioned all took a more-nuanced approach, and all found that some, many, or most complications that would have been attributed to race were instead independently associated with poverty, community deprivation, and other covariates. This means, of course, that the recommended solutions were entirely different in those studies than would have been the case if race alone had been analyzed.
We just can’t risk making that kind of mistake. The harms to the very patients we seek to help are too real and too great.
This isn’t an across-the-board policy about studies that evaluate race or in which race is a variable. For example, it doesn’t apply to studies where there is a plausible biological link between race and endpoint of interest, and where race or heritage are categorized using a sensible biological approach (such as genomic or genetic studies), nor would it apply if the authors can make the case that a particular community is interacting with a healthcare system in particular ways. A quote from an interviewee in CORR’s Editor’s Spotlight section that we’ve returned to before applies again here: “The outlook for a first-generation Spanish speaker from El Salvador in this regard may be different from that of a Mayan speaker from Central America, a Mexican-American from Texas, and a third-generation native English speaker with African-Caribbean ancestry from New York. All of these individuals likely would have different takes on the challenges to accessing the healthcare system” . The issue of how communities interact with healthcare systems might be a phenomenon of ethnicity, race, or both [2, 15], and in each study, these need to be teased apart. Regardless, though, it should not surprise us that different racial and ethnic groups might be variably skeptical of healthcare systems in which racism and prejudice persist, and we need to be attentive to this problem.
Studies can categorize patients by race and ethnicity when it is important or relevant to do so, and those studies should make it clear what the categories were, and how patients were categorized (such as genetic testing, patient self-report, or whatever it happened to be), but CORR will not insist that all papers categorize patients by race or ethnicity. Most orthopaedic research is retrospective, so this information often isn’t available, and when it is, it’s often so broad as to be useless. For example, too many studies still categorize patients as “White or non-White.” Given the very high percentage of people who are neither one thing nor another, this approach is seldom sufficiently nuanced for the task at hand. In addition, the variables of race and ethnicity are not relevant to all studies, and since including a variable almost always leads to its analysis, one needs to be very careful: Post hoc analyses in this context risk both Type I and Type II statistical errors, and both can cause harm in the name of helping, as we’ve highlighted before on the topic of sex and gender . Finally, careless or thoughtless application of race in clinical research has resulted in clinical guidelines and recommendations that have, in numerous instances, worsened health and resulted in patients being steered away from potentially life-saving interventions .
As always, it’s up to the authors to provide a sound rationale for the methodological approach chosen.
Finally, we note that the language on this topic often is problematic. We try to avoid words like “vulnerable” (as in “vulnerable patients” or “vulnerable populations”), which in this context strikes us as vague, often euphemistic, and frequently patronizing. One writer correctly pointed out that in public health research, that word generally is used to “avoid the discomfort associated with naming structural racism as the true root cause of many public health problems” , which is something well worth considering. We prefer more-specific language. Vulnerable to what? At whose hand? Even the name of this whole area of research—it’s sometimes called “social determinants of health”—seems, well, rather more deterministic than it is. Cause and effect are desperately hard to prove in these contexts, and well-intentioned researchers often have mistakenly attributed outcomes to one or another patient trait, in ways that sometimes have been odious .
This leads to the last word, which doesn’t appear very often in medical journals: racism. It’s still with us, and it still demands well-designed study. CORR will prioritize studies that evaluate racism in healthcare or in the professional lives of those individuals who provide that care, as well as studies on disparities more generally, provided that those studies control adequately for relevant sociodemographic covariates that frequently are associated with race and ethnicity. This deadly problem deserves more than casual inference-drawing.
1. Avila CJ. “Vulnerable” is a public health euphemism we need to stop using. Available at: https://theincidentaleconomist.com/wordpress/vulnerable-is-a-public-health-euphemism-we-need-to-stop-using/
. Accessed December 12, 2022.
2. Bazargan M, Cobb S, Assari S. Discrimination and medical mistrust in a racially and ethnically diverse sample of California adults. Ann Fam Med. 2021;19:4-15.
3. . Area Deprivation Index and vulnerable populations - how do I find them? Available at: https://help.broadstreet.io/article/adi/
. Accessed December 12, 2022.
4. Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry/Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index. Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/index.html
. Accessed December 12, 2022.
5. Economic Innovation Group. Introduction to the Distressed Communities Index (DCI). Available at: https://eig.org/distressed-communities/
. Accessed December 12, 2022.
6. Engler ID, Vasavada KD, Vanneman ME, Schoenfeld AJ, Martin BI. Do community-level disadvantages account for racial disparities in the safety of spine surgery? A large database study based on Medicare claims. Clin Orthop Relat Res. 2023;481:268-278.
7. Hadad MJ, Rullán-Oliver P, Grits D, et al. Racial disparities in outcomes after THA and TKA are substantially mediated by socioeconomic disadvantage both in black and white patients. Clin Orthop Relat Res. 2023;481:254-264.
8. Leopold SS. Editorial: Beware of studies claiming that social factors are “independently associated” with biological complications of surgery. Clin Orthop Relat Res. 2019;477:1967-1969.
9. Leopold SS. Editor’s Spotlight/Take 5: Telemedicine use in orthopaedic surgery varies by race, ethnicity, primary language, and insurance status. Clin Orthop Relat Res. 2021;479:1417-1425.
10. Leopold SS. Editor’s Spotlight/Take 5: Postacute care readmission and resource utilization in patients from socioeconomically distressed communities after total joint arthroplasty. Clin Orthop Relat Res. 2023;481:198-201.
11. Leopold SS, Beadling L, Calabro AM, et al. Editorial: The complexity of reporting race and ethnicity in orthopaedic research. Clin Orthop Relat Res. 2018;476:917-920.
12. Leopold SS, Beadling L, Dobbs MB, et al. Fairness to all: gender and sex in scientific reporting. Clin Orthop Relat Res. 2014;472:391-392.
13. Magnuson JA, Griffin SA, Venkat N, Gold PA, Courtney PM, Krueger CA. Postacute care readmission and resource utilization in patients from socioeconomically distressed communities after total joint arthroplasty. Clin Orthop Relat Res. 2023;481:202-210.
14. Templeton KJ. Editorial Comment: Diversity and Disparities in Musculoskeletal Care, Workforce, and Education. Clin Orthop Relat Res. 2023;481:224-225.
15. Thompson HS, Manning M, Mitchell J, et al. Factors associated with racial/ethnic group-based medical mistrust and perspectives on COVID-19 vaccine trial participation and vaccine uptake in the US. JAMA Netw Open. 2021;4:e2111629.
16. Vyas DA, Eisenstein LG, Jones DS. Hidden in plain sight—reconsidering the use of race correction in clinical algorithms. NEJM. 2020;383:874-882.