I'll be talking about the approach to achieving equity in pediatric critical care research. I don't have any disclosures. So we will define anti-racism and its importance in pediatric critical care research. We'll describe an approach to anti-racist research within the life cycle of a study. We'll summarize the literature, a couple of studies on how to study race, ethnicity in the context of racism. And then we'll discuss areas that need direct attention based on gaps in current literature. So just the basics. What is anti-racism and why is that important? Specifically, it's an active approach that seeks to identify and eliminate racism. And inherent in the word active is that there's actual effort and intentionality in that approach. For asking you to be anti-racist, it's important for you to understand what racism is in general. So the way that I think about racism is that it is a system of advantage that specifically advantages one group and inherent in that disadvantages another group. So it's important that we understand both concepts as we move forward. So why is this important in general? So we know that pediatric critical care researchers are now very, very interested in understanding racial and ethnic health disparities. And solely reporting racial and ethnic health disparities don't really move us closer to why those disparities are occurring. Specifically, we know that a lot of the literature that we look at in terms of racial and ethnic disparities specifically just talk about race and ethnicity, but don't really talk about the other factors that could potentially be contributing to the health disparities. We also know that race is a social construct. And so when you have something that is a social construct, it requires social context when discussing it. So it's important to think about that. When we think about race in general in medicine, we know that race was introduced into medicine quite some time ago, but specifically in the 1970s, when we think about racism and race in medicine in general, blackness was actually used to define a disease state. So race is not an accurate measurement. So it's not completely accurate when you look at one paper to another. People use different definitions in general. And then we also know that race in general is non-biologic. There are no genetic differences between me and someone else, just simply based on race. And we know that based on the Human Genome Project. So I'll focus on just two studies in regard to the current literature on studying race and ethnicity in the context of racism. So the first study I'll talk about is by Dr. Adrian Zerka, who specifically looked at an anti-racist approach when thinking about pediatric critical care research. And he made four recommendations. The first was that race and ethnicity should be evaluated as social constructs, which we just discussed. The other is that we should collect race and ethnicity in a way that's actually meaningful. So it should be sufficient data so that we can actually detect meaningful results. Inclusivity and adaptability are really, really necessary because, as most of you all know, health equity and our definitions and the way that we think about it are constantly changing as we learn more. And then lastly, it's all of our jobs specifically to think about and explore race in research in general, just because we are all researchers and our collective way that we think about patient outcomes requires us to all rigorously report and evaluate race and ethnicity. The second paper that I'll focus on talks about how we recalibrate the use of race in medical research. And so ultimately, this author describes two schools of thought. And they're pretty divergent. The first is that efforts should focus specifically on strengthening our measurement analysis and reporting of race. The second is that race as a measure should just be abandoned. And so while both of those are pretty divergent, they can also be held true. The latter is not specifically saying that we're not going to think about race at all. One of my colleagues always says that if we still live in a racialized country, that we still have to talk about race. And we do still live in a racialized country. So we still have to talk about it. It's just a matter of how we think about it and talk about it. We should be thinking about ways that we can use other variables that are more robust when we think about and define race and evaluate its impact on outcomes. So this author recommends two things, but specifically looks at past investigations versus future investigations. Because we know that there are previous studies that already use and identify race and ethnicity when thinking about disparities. And so for past investigations, the author recommends a systematic re-examination of evidence for things that we hold core to ourselves. So I put GFR because I think that's the one that everyone usually thinks about. The other one that I always think about is back in the day when I used to think about hyperbilirubinemia, one of the risk factors in how you stratify your bilirubin is actually if you're African-American, you're actually at higher risk. But race, again, has no biological evidence that it is related to health disparities. So we have to rethink how we're thinking about race in general with those things that we've learned to be core truths. And then the other is just to develop better variables than race in general, which is obviously more challenging to do. For future investigations, the author recommends that we consider in general why we're talking about race, why we're using race in our studies using a four-step approach. The first is to perform a systematic review. And the purpose of that systematic review is specifically to, one, see if we should just abandon race in general. Is it futile to keep looking at this in general? So we should review studies that have already looked at race and see if we can make that determination. The other is whether or not we can use some of the methods that have looked at race previously and see if we can apply those as we implement future studies. And then the last is just should we be thinking about novel hypotheses? Are there things that we haven't thought about in literature that we should move forward and think about now? The second is whether or to consider collateral variables and also think about how to enhance and standardize the way that we think about race in general. The third is to consider whether white race should be a reference standard, which I'll bring up again, or whether or not that should be the normative thing that we reference all of our disparities against. And sometimes it's relevant and sometimes it's not, depending on what you're researching. And then the last is to consider the potency of race-related research. So when we're examining race in general, there are certain things that come out of our studies that either point to how we can think about ameliorating these disparities. And some of them actually can cause us to increase or accentuate the way that we think about inequities in general. So those are the recommendations from this author. So ultimately, the question still remains, how do we use this anti-racist approach to think about research in pediatric critical care? And I think it's important that we take this approach, but it requires a couple of things. The first is for researchers to define the purpose of using race and ethnicity in their studies in general. The second is to name racism. That is what we're studying. We're studying racism. We're not really studying race because we've already determined that that's not measurable from one study to the other because we all use different ways to describe race in general. To avoid using biological reasons or justifications when we're looking at data that specifically looks at racial and ethnic disparities and outcomes. Excuse me. And then the last is to examine the drivers of disparities. But going beyond that, it's important that we use our research to think about how we can contribute to programs and policies that help mitigate racial and ethnic disparities. So I think about using an anti-racist approach throughout the entire life cycle of a study, so from beginning to end. And we'll go through that. So in the planning stage, the first thing that we have to do is have a health equity lens when we're planning our study. And that goes from aims, creating your aims, to creating your protocol in general. So first we have to ask, why are we studying race and ethnicity and how will that be used? And when we're asking that question, when we're creating our protocol and aims, we should answer that question. So that should be a part of what we're trying to answer in our study. The next thing we should ask ourself is what study population we will use and what the demographics of that study population are. And if we notice that our study population does not seem diverse, then we should ask ourselves how we can make our study population more diverse. Some of those things include very simple things, like if you're giving out surveys, making sure they are in multiple languages based on the study population that you're serving. And then we should ask ourselves whether our study could benefit from community involvement, which I don't think we do as much in critical care, but it's really important to consider the community because they can be helpful in sometimes your protocol development, helping you think through what variables make sense, or sometimes even what questions you should be asking in general because that's the community they live in and that's potentially the community that you're studying. And then the last thing is to consider a mixed method approach. So you want to be able to supplement your quantitative data to help us better understand why these disparities exist. So from the data collection standpoint, we first have to recognize and consider that bias in general can affect the databases that we're using and the algorithms that we're using. And so we have to ask ourselves in general, what databases are we using? What elements are contained within those databases? And that's important when we're thinking about race and ethnicity. The other thing that we should think about is what other variables we can collect. So can we collect other things like education or income that typically will point more towards systematic racism in general? And then we have to ask what data collection approach will be used to categorize race and ethnicity first. What categories are you using? But second, how are you obtaining that data? Is it self-identified data or is it data that someone else input based on what they saw phenotypically? So it's important to know that when you're collecting data. And then for data access, this sentence seems very simple, but I think it's a little bit more complex than what it reads. So we want to know who's going to access the data and why. And the way that I think about that is simply back to what I just described. So you have databases that have bias that are sometimes already built into them or algorithms. And so when you are making those databases essentially more public, so through your research and through how you report and disseminate your research, when you are making these databases in general more public, sometimes there are things that come out that can actually hurt communities that are already marginalized. The best example I like to use is my research is on neighborhoods. And I look at physical disorder and one element of physical disorder is graffiti. So if I do a study that shows that neighborhoods that surround the hospital are neighborhoods that have more graffiti and that somehow leads to poor health outcomes, then I disseminate that data. Now it's public. So does that lead to more policing in those areas? So that you have to think about what you're doing or what you're saying when you're disseminating your data and who will have access to it now. And then in the analysis phase, I will tell you I'm not a statistician by any means. I'm also not a data analyst. But I think it's really important that we think about this and that we include data analysts and statisticians that are used to working with this type of data and thinking about data and analysis with a health equity lens. So it's important that we use a health equity lens and a racial equity lens when we're analyzing our data. So the first thing is recognizing that you're not studying race and ethnicity. You are studying racism and the impacts of racism on whatever health outcome you're looking for or looking at. And then we should think about correlating the geographic context to outcomes. And the reason I think that's important is because that acknowledges some of the systemic injustices that we see in our country today based on redlining and such. And so it's important to think about things like the Child Opportunity Index or the Social Vulnerability Index as other factors beyond race and ethnicity that we can use to look at these disparities. The other thing is to disaggregate data. And I don't mean just by race and ethnicity. I also mean looking at race and gender, race and income, race and education. So it's important to also look at these other factors. And then, again, be mindful of that comparison group that you're using. Again, should we be using white as the normative comparison group? And then in reporting and dissemination, I think some of the stuff I already mentioned in terms of who gets access to our data, who our audience is, and how we say things is really important. When you're thinking about reporting in general and you're submitting your manuscript, it's important to recognize and write back from when you were in that planning stage why you were looking at race and ethnicity in general. And if you don't collect race and ethnicity data, you should probably say why. And as I mentioned, you should also think about other social factors to consider beyond race and ethnicity. If you don't think about those social factors, I would argue that that's a limitation of your study. And that should be included when you're reporting and writing your manuscript. If race and ethnicity were included, you should acknowledge structural racism when you're talking about that data and use that context when you're talking about your data and your findings. And then you have to use terms that are accurate and equitable. And as I mentioned before, terms change the way we think about health equity changes. So it's up to us to also understand that when we're writing our manuscripts and reporting our data. And then reporting your demographics for the proportion of participants in the study compared to eligible participants. Do you have a representative sample of your study from a demographic standpoint? And then lastly, strategically consider your audience. And that kind of goes back to what I was describing with the graffiti example. Who are you talking to? Where is this data going to be? It's really important to think about when you're reporting. At the institutional level, when you're thinking about IRBs or you're thinking about just research institutes in general, it's important to think about ways that we can better assess the impact of racism on health disparities. And so one of the things that we can do is have our research institutes require new databases to not just include race and ethnicity, but to also include social factors. So those are databases that you're creating from scratch. For databases that you're not creating from scratch and for more of your retrospective studies, it's important to include things like how data was collected on race and ethnicity. And if you don't know, again, you should add that as a limitation to your study. And then for prospective studies, again, requiring researchers to describe how race and ethnicity will be collected, why you are collecting race and ethnicity are also important. And then providing funding for people that are trying to study health disparities within the context of racism is also important. So lastly, I just want to talk about the current gaps in literature. And this will be quick because Erin went over some of the studies that I will bring up. So broadly, again, my research focuses more so on neighborhood factors and health outcomes in pediatric critical care. And so there's a study by Dr. Epteen at CHLA that specifically looked at neighborhood income and the impact on the PEM-2 score, mortality score. And he found an association, an inverse association with income and the PEM-2 or mortality score. Then we have Dr. Andrus out of Cincinnati. And Dr. Paquette went over that study that looked at poverty and PICU utilization or increased admission rates to the PICU. We have Dr. Grenwell, who's also a part of this panel but on the virtual side. So that's a plug for her to listen to her presentation. But her and Dr. Nahar out of Emory, they specifically look at respiratory failure and asthma and look at social vulnerability index and the child opportunity index. And they found that patients that have lower child opportunity or higher social vulnerability have that is associated with mechanical ventilation and critical asthma. And then we have Dr. Myers, who's now at Cincinnati, but studied, looked at patients at Hopkins and specific factors that are related to vacant homes or homes that don't have cars, et cetera. So those types of factors and found an association with increased PICU admissions. So overall, I think what you heard is that we have a lot of studies that show that there's increased PICU rate, PICU admission rates. We have studies that specifically say that there are disparities. But we don't really have a lot of studies that look at causal inferences. And so I think that is where our large gap is at this stage. And so specific individual and neighborhood level factors are what we should be thinking about and how those contribute to health outcomes and pediatric critical care. So overall, broadly, I talked about a lot of things. But ultimately, I think it's really important that we use an anti-racist lens when we're looking at our studies and thinking about our studies from top to bottom, so throughout the whole study lifecycle. And that researchers should start to evaluate the association between these health factors that are pretty much nontraditional, so neighborhood factors and social determinants of health and outcomes in pediatric critical illness. These are some of the resources that I used to create this PowerPoint. So I thought it would just be helpful to at least list them here. And thank you for your time.

anti-racism

pediatric critical care

health disparities

social determinants

community involvement