Is your research equitable?


TheRISE Equitable Research Guide, adapted from theUrban Institute's Guide for Racial Equity in the Research Process, offers questions for researchers to unpack at every stage of the process. Below are a handful of examples.


1 What problem does this research address? 2 Is this problem exacerbated in communities of color or in systemically


divested populations?


3 Can this project be completed with integrity without including sub- 4 Are the inclusion and exclusion criteria of the study broadly defined


analyses of underrepresented populations?


with intention to avoid systematic exclusion of underrepresented populations?


5 What populations or groups have been left out? Are they See the full guide at pledgetorise.org.


acknowledged? How are these populations affected by this problem compared to the study population? (Are they more or less affected?)


References


1. Bokor-Billman T, Langan EA, Billmann F. The reporting of race and/or ethnicity in the medical literature: A retrospective bibliometric analysis confirmed room for improvement. J Clin Epidemiol. 2020;119:1. doi.org/10.1016/j. jclinepi.2019.11.005.


2. Okah E, Thomas J, Westby A, Cunningham B. Colorblind racial ideology is associated with the use of race in medical decision-making. Health Services Research. 2021;56(S2):89–88. doi. org/10.1111/1475-6773.13844.


3. Fawzy A, et al. Racial and ethnic discrepancy in pulse oximetry and delayed identification of treatment eligibility among patients with COVID- 19. JAMA Intern Med. 2022 Jul 1;182(7):730–738. doi: 10.1001/jamainternmed.2022.1906.


4. Gottlieb ER, Ziegler J, Morley K, et al. Assessment of racial and ethnic differences in oxygen supplementation among patients in the intensive care unit. JAMA Intern Med. 2022;182(8):849–858. doi:10.1001/ jamainternmed.2022.2587.


5. Mustapha JA, Fisher BT, Rizzo JA, Chen J, Martinsen BJ, Kotlarz H, Ryan H, Gunnarsson C. Explaining racial disparities in amputation rates for the treatment of peripheral artery disease (PAD) using decomposition models. J Racial Ethn Health Disparities. 2017;4(5):784–795. doi: 10.1007/s40615-016-0261-9.


transparency. With a baseline of data transparency, the medical research community can finally begin to allocate resources toward achieving representative research cohorts. In addition, racial/ethnic data transparency can encourage HIPAA-compliant data collaborations to power systematic reviews or meta-analyses and facilitate meaningful subanalyses to aid health disparities research.


The #pledgetoRISE movement offers resources to help physicians take the first step, such as an implicit bias test and a research guide with tips on how to work toward equitable research. The research guide was adapted from the Urban Institute’s Guide for Racial Equity in the Research Process and acts as a collaborative, living document.


The guide focuses on four key areas: literature search and team forming, study design, data collection and analyses, and communication and publishing. Each section contains questions that researchers are encouraged to ask themselves and


their team, in order to investigate the intentions behind each step of the research process, from “Is this problem exacerbated in communities of color or in systemically divested populations?” to “Are researchers who have considered this research topic from a racial equity perspective cited?”


Making your pledge The first step in advocating for health equity in medical research is by sharing the demographic breakdown of research cohorts by race and ethnicity when possible and appropriate. The #pledgetoRISE movement invites researchers to share this data— and even if there is no inclusion of underrepresented populations within your study, the transparency is critical to helping the medical research community better understand the lack of representation.


Learn more about advancing health equity in medical research at pledgetorise.org and #pledgetoRISE today!


6. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447–453. doi: 10.1126/science. aax2342.


20 IRQ | SPRING 2024


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