I'm Dr. Daisy Hassani. I'm the moderator for today's webinar. Today's webinar is Health Disparities in FDMRS and it's being presented by Dr. Kenny Brown. Dr. Brown will present for 45 minutes. The last 15 minutes of the webinar will be dedicated to Q&A. So a little bit about Dr. Brown. Dr. Brown is a Female Medicine and Reconstructive Fellow at Northwestern University and will be joining the FDMRS faculty at Northwestern in the fall of 2021. She is currently co-chair of the Diversity, Equity, and Inclusion Committee for the Department of OBGYN at Northwestern. Her areas of interest include health and healthcare disparities, surgical outcomes, and bias and racism in medicine and medical education. Before we begin, I'd like to review some housekeeping items. The first thing is that the webinar is being recorded and live streamed. Please use the Q&A feature of the Zoom webinar to ask any of the speakers questions and please use the chat feature if you have any tech issues. Dr. Augstaff will be monitoring the chat and can assist. And with that, I think we can get started. Thank you so much for that introduction, Dr. Hassani. I'm gonna get started. I think I have to say this, I have no disclosures. So I wanna start with just going over the learning objective and sort of my goals for this talk. So throughout this talk, I hope to review the definition of health disparities, social determinants of health, and how they impact health equity, as well as review the current literature on disparities in FPMRS related to pelvic organ prolapse and urinary incontinence in particular. And then I want to sort of review a framework or model for understanding these disparities, as well as discuss strategies for applying a health equity lens in FPMRS. My talk is not necessarily organized this way, and I will sort of signpost with them throughout, so bear with me. I think it will be more beneficial to sort of weave these concepts throughout, because it's not linear and it's pretty complicated. So I hope that you guys would just kind of join me for the next 45 minutes, and let's jump right in. So I do in general like to start out with just sort of naming things, calling out some definitions. And so according to the WHO, health equity is the absence of unfair and unavoidable, remediable differences in health among population groups defined socially, economically, geographically, or demographically. And we know that healthcare disparities are a barrier to health equity. I think everyone can agree with that. But healthcare, there's a huge, huge economic burden as a result of healthcare disparities. This study is a little older and always shocks me in terms of the numbers. So there's a study that was conducted in 2009 that found that between 2003 and 2006, 30% of the medical care expenditure for African-Americans, Hispanics, and Asians were due to excess costs from health inequities. And that same study also showed that eliminating those health disparities for minorities would reduce the direct medical care by about $229 billion over that three-year period. And so we also know that healthcare accounts for about roughly about 18% of the US economy, which is roughly about 12% of the workforce. And this is just expected to grow it fast, right? And faster than any other industry in the next decade. So I'm by no means saying that this is a niche industry, but I'm saying that it touches every patch of social fabric, which makes it a duty of health systems to really pay attention to health inequities. And we are part of that system as well. So that's my plug for saying that, I'm making the case for why we should care about this. But beyond the economic impact for health disparities, we know that there's a moral case to evaluate the roots causes in all medical fields and craft solutions to address these disparities, particularly in a field like ours that is centered around quality of life care, which, insert soapbox, doesn't mean effective care, in my opinion. So it's allowing individuals to really enjoy their life, right, and taking away things that are a barrier to that. I really do think that we have to pay attention to this and the impetus to really think about how to make sure that our care is equitable, that all our patients and all populations are benefiting from care. It's really important. So if no one has read this piece, I really love this article. It was, gosh, I can't remember what year it was, but it's from the American Journal of Public Health. And Dr. Jones makes an argument for the moral problem with disparities. This is just a little excerpt from the beginning. And she does a beautiful job, both bringing in some ethical principles and making an argument for why disparities are just morally wrong. And she says that healthcare disparities that exist in the U.S. are problematic because they exemplify and aid in perpetuating century-old systems of injustices that are based on various demographics, whether you're a race, ethnicity, class, and that the consequence of these disparities is that the differences perpetuate like these preexisting inequities that are suffered by vulnerable populations so that these individuals, the individuals and populations that are affected or impacted by these disparities are not able to enjoy the right to life, liberty, the pursuit of happiness, the tenets of what our country purports as a right that every individual should have. And so I want you guys, I want us to sort of think about that as we move through the talk in terms of like why this matters, why we should care about it, I think why we should urgently focus on it and really pull our brainpower to really think about how we can craft solutions. So moving into some more reviewed terminology that I know that most are familiar with, but I do think that it's important to just level out the foundation with what we're starting with also because I'm gonna be using a lot of these terms throughout the conversation today. And so I wanna start with health disparities. And so health disparities according to Healthy People 2020 are systemic and avoidable health differences that adversely affect populations that experience marginalization in society. And so it's important to know that health disparities don't necessarily equate with health differences. Another way to say it is that all health differences aren't necessarily disparities. So for example, if we observe that basketball athletes have higher rates of ACL injuries compared to non-athletes, that's a health difference, not necessarily disparity. However, if you find that athletes from a certain group, particularly disadvantaged group, experience worse outcomes after these injuries compared to athletes from another group, then that would be a disparity. And in this definition, I make it a point to throw out the term or bring in the term health inequity, because I would argue that that's probably a better term than disparity. And a lot of social justice, scholarly work and circles are trying to sort of move and push towards using this term because inherent in the term health inequity is a notion of social disadvantage, right? And also the concern for social justice, which is really at the heart of why this demands attention. So I'll use it interchangeably, but we could argue that we should really be calling these health inequities. And then again, I know that we're familiar with what social determinants of health are. So according to World Health Organization, the WHO, these are the conditions in which a person is born into, grows, lives, works, age, this includes the health system. And more importantly, these are sort of the non-biological determinants of health. And in the conversation of health equity and health disparities, this is emphasized, right? The role of social determinants, the role that social determinants of health play in driving disparities. And so this isn't new, this is well-established in the literature. However, I would say that recently, I shouldn't say super recently, but we're also moving to, in addition to social determinants, really pay attention to structural determinants of health, particularly in terms of racial ethnic disparities, thinking about systemic structural racism and the impact that that has on these social and political and structural determinants of health, which brings me to my next term, which is systemic or structural racism. There's a lot of debate in terms of, are these two different things, that they're the same thing, we can lump them together for one. But basically, and again, another article that I'm gonna throw out, if you haven't read it, it was published in the Lancet 2018, I believe, by Bailey and colleagues. And I think it's, I'll refer to some of the content in this during the webinar as well. But I think they give a really salient definition for what structural racism is. And they define it as a totality of ways in which societies foster racial discrimination via mutually reinforcing inequitable systems. And when I say systems, think about things like housing, education, employment, earning, benefits, credit, media, healthcare, criminal justice, the list goes on, that in turn reinforce discriminatory beliefs and values, as well as distribution of resources. And first thing I want you guys to walk away with, and I hope that we are in agreement, is that the predominant root cause of racial and ethnic health disparities is structural racism. That's what I believe. And it's not more like an opinion, it is, and that has to enter the conversation about when we talk about disparities, particularly racial ethnic disparities. And then finally, this term equity, and I know that there are a lot of infographics that have been going around like in the past year that depict this point, the difference between equity and equality. I won't use these interchangeably because I think they are very distinct. Both are focused ultimately on fairness, and in promoting fairness, but from two different perspectives. So equality accomplishes this by treating everyone the same regardless of need, whereas equity is part of the belief system that people should receive what they need in order to achieve optimal outcomes. And so I put this in the conversation because equity as a framework is essential in healthcare because A, it acknowledges a justice-oriented framework that different groups may require different resources to achieve optimal health. And so before I dive into the main content of what I'm gonna be talking about today, I wanted to make a point about racial disparities because this will come up a lot in what I highlight in terms of the literature and why that is. So it's really a product of what the focus of a lot of the literature is. And that is not to say that there aren't other disparities that are not based on race. I think that's really important to drive them. And I wanna like upfront acknowledge that. I do think that racial disparities are heavily entrenched in societal systems. What I'm passionate about, I have a lot of criticism about it. So there's that bias of mine in terms of where my interests lie, but like I said, there aren't disparities just on the basis of race, ethnicity, even though a lot of the disparities that I highlight today will be based on that. So this is the first introduction to what I'm gonna actually build in throughout the webinar. And as opposed to doing a dump at the end of like all the things that I think we need to do in order to apply a health equity lens to FMRS, I wanted to weave that in throughout and keep going to it because I think these things, these concepts build on each other and are not necessarily distinct. They do reinforce each other. So this is gonna pop up throughout the talk. And so before we can even start talking about the drivers of disparities or begin to understand disparities and craft solutions to address them and address these inequities, we have to focus on the interplay between multiple factors, including individual and population level determinants of health, right? I think I sort of alluded to that, but I wanna bring that, like actually deliberately say that. And so this here may be familiar to some, this is the socio-ecological model. It was first introduced by Bond for Brenner and it posits that health and human development are influenced by factors at multiple levels from the individual to the macro societal level. And the frameworks that I like in terms of understanding health disparities are, do build on and are sort of modifications to socio-ecological models. So I wanted to introduce that first. So the model that I chose to talk about today and that I really do like, cause I do find myself going back to it in terms of how I think about disparities it's by Wernicke and colleagues. This is printed, this is what's published in the American Journal of Public Health in 2008. Dr. Wernicke has done a ton of work in disparities and understanding disparities. And the overview of the model states that, disparate health outcomes are typically a result of inequities in the distribution of resources that promote health outcomes. And a common pitfall is to reflexively attribute these differences or these disparities solely to inherent differences in groups that are affected, right? Which implies it's almost like a sole biological basis for a disparity and ultimately disregards a complex relationship of different and several external factors that place individuals and populations at risk for inequitable health outcomes. And so this model presents a framework for analyzing health disparities and actually looks at three levels of health determinants. And these are shown here on the left. So distal factors, intermediate factors, proximal factors and I wanna introduce those terms cause again, I'm gonna keep using these. So we'll start with the distal factors. These are the social conditions, the policies the policymaking bodies that impact social conditions in healthcare systems and are considered the fundamental causes of disparate health outcomes at a population level. I should have mentioned before I started that I think it's really important to, when we think about health disparities to really have a population perspective. I think it's easy to try to sort of go straight to like an individual perspective but we really need to think about it like in a population sense. And these distal factors include things like legislation and governance that facilitate things like neighborhood level discrimination, right? Systemic racism. That's not necessarily explicitly stated in this model. So in like this 2008 print version but when you look through it that's exactly where that fits, right? State sanctioned violence, political exclusion and these distal factors can impose downstream barriers that limit individuals at a population level from attaining optimal healthcare. I would argue that we need a lot of research here. Like this is like a, particularly in terms of thinking about research in FPMRS. This is really what's gonna drive where we start to craft solutions that are gonna make a huge impact. So that's my plug for people who think about this for us to be thinking. Not that it's not important to think in these other realms, right? But really to think about how we can build on stuff but ultimately we wanna be addressing these. And then the intermediate factors are the link between the distal factors and the individual level factors. And so they have the social and physical context and the social relationship structures that impact health. And then finally, the proximal factors are those that represent individual demographics, risk behavior, biological responses to environment and disease. So what I like about this framework and what I'm gonna advocate for is that this model assumes that health inequities don't occur as a result of one isolated factor. And instead they result from an interplay between multiple levels of determinants of health and underlying systemic factors like systemic racism. And it literally defines the importance of a life course perspective, right? So considering early adverse events, chronic cumulative social and environmental exposures, transgenerational transmission risk of both resilient and transgenerational transmission of resilience and really thinking about how that impacts health. So when I spend too much time thinking about it, my mind is like blown because it really is so complicated. Like when you start, spoiler alert, like when you start thinking like, how do you measure that? How do you craft these concepts into like, particularly like when you're thinking about research, I'll get to that. But also inherent in this framework, like when you really parse through it, you can already start, you'll start to realize that there are certain populations that may be structurally vulnerable to disparate health outcomes, because these groups experience a mismatch between the group and like in the system. And so here's what I mean by that to kind of illustrate the concept. I'll give you three examples. So a lot of like a huge group that experienced, in multiple fields experiences, disparate health outcomes, black women. And when you think of the history of slavery and system level policies that allow like neighborhood level discrimination and racial segregation, economic injustice, social deprivation, and the impact, all of that impacts the health care of black women in the United States. So if we were to take residential segregation, for example, right? And if you're thinking about, if you said, well, Black women in a certain population or in a certain area experience health disparities, and maybe this is related to healthcare access. Well, thinking about the structural factor, which would be residential segregation, right? This impacts utilization as well as quality of neighborhood healthcare providers, right? And you think about what neighborhood level segregation does in terms of chronic divestment of communities, which then results in this cascade of events like deterioration of housing stock, schools receiving insufficient fundings, local entrepreneurs are struggling to secure small business loans, this then cascades and has lasting effects and ongoing effects in terms of policies, practices, and ultimately impacts health outcomes for that area. Now, let me pause and say, this is not to generalize that all individuals in this group have the same experience. That's not what I'm highlighting. I'm just saying that if you think about it in terms of like a structural framework, right? And you encounter a disparity in this group, that could be one component. And that's how we think about how like already just because of that historical perspective, a certain population is at risk for experiencing disparate health outcomes. Another group that we could sort of do the same exercise with in terms of structural vulnerability will be native indigenous women, right? So the Indian Health Service is the agency within Department of Health and Human Services that's responsible for providing federal health services to federally recognized American Indian tribes in the US, right? But here's the problem. Not all tribes are federally recognized. And so this potentially excludes some native tribes from coverage under this service, right? And this service comes as a result of like multiple treaties. And this is supposed to be part of like the government's commitment to this group for like the historic egregiencies that this group has suffered. And now there's some groups that are not automatically are not able to participate or benefit from this, right? We also know the capacity for adequate coverage is also impacted by the underfunding of the IHS, which is documented in the literature. And so then it may then subsequently leave some populations to rely on CMS services, so Centers for Medicare and Medicaid Services. However, recent studies have shown that there's some reluctance from some tribes to and some individuals from this population to enroll in these services for many reasons, including trust concerns, particularly around sharing personal information with non-Indian government agencies. And so when you think about that, like before even engaging with the healthcare system, already at risk for disparate health outcomes. And then when we think about that, how does that impact access to subspecialty care like urogynecologic care for these populations that will absolutely undoubtedly contribute to the health inequities in that population. And then, I mean, I can go on talking for everybody, but I do think that there's one more group to sort of call out, and that's language proficiency, because I think it's easy to overlook this one. So there are many, many groups that are impacted by the unique challenges that arise from interfacing in the US healthcare system with low English proficiency. And often parallel within this experience is the experience of immigrants and the challenges that margin and the marginalization that this creates and its impacts. I'm an immigrant, and I just even think about my experience of when I first came to the United States. And I mean, it's just that we can talk about that, but let's go to another talk. But then there are challenges in communication, right, that are described in the urogynecologic literature in particular for persons with low English proficiency. And we know that this has implications for patient knowledge of conditions and provider-patient relationship, both of which ultimately can place a patient or population at risk for disparate health outcomes. So this study I want to highlight is a recent 2019 study that analyzed the readability of patient information materials in Spanish for pelvic floor disorders, including urinary incontinence that was available through organizations, professional societies, government agencies, and industry. And what they found in the study was that most of the materials were at a range of in terms of readability level that would be characterized as average to difficult reading level. In addition, none of the analyzed materials met the sixth grade reading level criteria that is suggested by the NIH and the AMA. And so, yeah, when you think about like an intervention to try to promote patient knowledge, right, for a particular group and what you're offering, so this is what I mean like in terms of thinking about equity, right? This is inherently inequitable. And then, you know, I'll highlight some studies subsequently when we start looking at disparities in knowledge of PFDs. Well, I mean, you know, for at least this population, this is contributing to it, right? And then these two were like kind of really disturbing studies, really well done. These, and they're both done in 2013. So the first evaluated communication between Spanish-speaking Latin American women with pelvic floor disorders and the physicians and found that the physicians commonly avoided medical terminology and instead used simple words when describing the patient's diagnosis. And P.S., this is, I love qualitative, you just get so much rich information from it. There was also a common theme that, or a common theme that was identified was the lack of Spanish proficiency among physicians with a common finding of physicians using inadequate Spanish during counseling of patients, in addition to speaking for several minutes at a time without pausing to elicit patient feedback and understanding. And they also found that in this study, at the end of this, the patients had poor understanding of their diagnosis. And at the end of the patient-physician encounter, often felt overwhelmed during the clinical encounter. And then the other study sort of highlights similar things, but also for sure that, you know, like at various levels of the clinical encounter, not just the physician, you have so interacting with the staff, with the translators. There were several communication barriers, which basically can create a marginalized experience as patients seek care and ultimately put them at a disadvantage in terms of both understanding their conditions, decision-making, and I'd say place patients at risk for disparities. So again, thinking about those distal factors, right? Those are the things that are fundamental causes and drivers for health disparities. So this is probably that I'm going to start to dive into, not the meat of talk, but a lot of the literature that we have. I structured this portion of the talk to go through the studies that highlight disparities in PFDs in these domains. Again, I chose to focus on mostly like urinary incontinence and prolapse, just because we could really just go on for days. We have limited time. And I think some of these things do come up, you know, for different disorders. This is not an exhaustive list of studies. There are studies that I didn't include. So this is not meant to be like a systematic review, but rather I chose to focus on studies that, A, highlight the points, some of the points that I made earlier. But also things that we can be cognizant of, areas where there are gaps, where we can be thinking of where we can push our curiosity and things that we want to investigate and targets for improvement, particularly as we think about Wernicke's model that I threw out earlier. So for women with PFDs, we know that they have been disparities in the literature described in knowledge, care-seeking, as well as treatment and treatment outcomes. And for each study that I go through, you know, I'll try not to editorialize too much. But I think with the conclusions to really think about those studies and the conclusions through that model that we talked about, both from a perspective of like, well, what's missing here? What don't we have? What can't we measure? So there are studies that, you know, there are a couple of studies that suggest that there are disparities in the knowledge of PFDs, right? This study in particular by Shah and colleagues is a little older, but I think it highlights some of the points that I was making earlier. So this group administered the PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, PIQ, the PIQ, PIQ to about 126 care-seeking women. And that tool has two domains, one for prolapse and one for incontinence. And what they found was that among care-seeking women, knowledge of urinary incontinence was higher among white women than non-white women. And they also looked at education and found that in addition to higher knowledge amongst white women compared to non-white women, women who had higher education levels were also more likely to demonstrate knowledge of treatment options for urinary incontinence compared to women who had lower education levels. That feels like a big duh, right? Like, but I think this is an important point that I want to drive in. So I think I'm skipping ahead a little bit. When you focus just on like the race, ethnicity variable, you may miss some key things in this, right? I think a huge driver of this is really education level, education attainment. And if you go back to Warnake's model, that is impacted by distal factors, right? Education attainment is a direct result of privilege, power, position in society, access. And so you start to think of like, we're seeing the disparity at the level of knowledge of PFDs, but really what's driving that is something much bigger, right? And much more entrenched in policies, exclusion, et cetera. And so just something to think about that. This other study, I think there's some really interesting things that they did in the methodology that I think that we should be pushing ourselves to do. I wish there was more of it. And I think for those of us who are interested in doing disparities, research in disparities work, this is an area that we can start to really try to develop and craft standards around. So this study looked at the same question before, again, differences in knowledge. But in particular, they wanted to see if SES accounted for any of these differences. So they analyzed the knowledge scores from about 212 community-dwelling women in the Boston area, and they were surveyed in focus groups. And they did this, this is sort of like savvy, sophisticated research methodology. They generated an SES score, which is a combination of the occupation of the main household wage earner and education level of the respondents based on the green method. And the original green paper has like an exhaustive list of occupation scores that were, you know, and if for some reason the occupation scores weren't available, then they just didn't assign an SES score. And that was only about 4% of the population. And so initially at first pass, what they found was that white women had greater knowledge about urinary incontinence compared to non-white women. However, this finding was no longer significant when they controlled for socioeconomic status. I think that's huge, right? This is, again, a plug for why we really need to pull those social determinants of health and structural determinants of health into our health disparities literature. Because if you just have one sort of dummy, one variable that's supposed to be a proxy for that, you miss all of it. And it isn't separate interpretation of the data. So I threw it out to just highlight those two points and to make those two points, which then leads me into like my second thing that I think that we all need to do when we're applying a health equity lens for MS is to really push past the race variable. And I say push past and not eliminate. We can talk about that later on. But I think it's really push, just trying to think beyond that. And that's because we know race categories are flawed. Traditional race, ethnicity categories, particularly in research, don't accurately identify populations. Race is a social construct. We know this. And these categories embody like significant ancestral heterogeneity. And they're, frankly, poor proxy for genetics and ancestry. And in research, race and ethnicity is not always self-identified, which is problematic. It often doesn't capture mixed ancestry, right? And the genesis of this classification criteria really is linked to like skin color and a bunch of other historic things. Like we can talk about that. So here's my husband, my daughter, and they're like a prime example for that. So David identifies as the Black man. If somewhere we're assigning his race in like a research study, they may be tempted to say otherwise, to like, already we have a problem. And to the typical or the traditional OMB categories don't really capture what my daughter Celine and David, like in terms of their genetic, well, their ancestral heritage, right? It doesn't capture that. It forces you to pick one of these categories. So it's not, I'm not going to say it's not meaningful, but it's like, why are you, what is it telling us, right? It tells us that we identify with a group for many different reasons, right? We're proud of that, but it's not telling you that, you know, that I'm Nigerian, American, didn't grow up in the United States. So race is flawed is my point. And it's important to not focus on race as the risk factor, right? But more as like the risk marker and acknowledge that they are social determinants that are commonly experienced by different groups. And these groups so happens to often be going by race, right? And if we only focus on that race variable, it limits our ability to identify what those drivers of those disparities are. And then I kind of alluded to that in order to really apply health equity, we need to start moving, start thinking about the challenges and actually capturing disparities. I've already mentioned some of them, but even just the measurement variable, like how do we come up with new measurements and cumulative measurements that take into account a bunch of social and structural determinants of health? We really need research in this area for sure, as well as complex modeling systems that can consider the effect of all these determinants in scale, right? As well as cumulative risk and exposure, because it's probably not the same. We don't know if you live in a chronically divested neighborhood for 15 years and experience exposure X for X amount of years, and you don't have these resilient factors, or you do have these resilience factors, none of these things are in our large databases. Let me just throw that out. So I think it makes it hard sometimes to just even capture disparities. So I put that there because again, people who are thinking about this, this is where we really have to start pushing ourselves to think about more because this requires more. And I already kind of stated why this matters, right? Because if you're focused on the wrong thing, the wrong output from these studies, then it shifts where you choose to focus your intervention. So if we think about those two knowledge studies, for example, if you just focus on the race, ethnicity part, you miss the structural issues. And you might say, well, the difference is that I'm not focusing on race, ethnicity, to address this, patients need more patient education materials, where really the issues like education and SES and the entrenched systems that create inequities in those external factors that then subsequently impact knowledge, right? So we know that knowledge probably impacts care seeking. 50% of women don't seek care for urinary incontinence. 25% of women with prolapse don't seek care. And that there have been disparities that have been described in this domain. We also know that many factors impact care seeking. There are many models for thinking about this for care seeking and healthcare utilization. A lot of the studies that are available in FPRRS around care seeking deal with access, the impact of culture and perception. I'm just going to highlight a few. So Berger and colleagues did a study that found that there were no differences in care seeking for urinary incontinence, right? Between women who were seeking care for urinary incontinence between Black and White women. However, for Black women, having regular pelvic exams, which basically implied having regular access to healthcare, was associated with healthcare seeking. This is not novel. This was also shown in this study in 2015 in the Green Journal that looked at care seeking or factors associated with seeking treatment for urinary incontinence during the menopause transition. And one of their key findings with it was that regular access to a healthcare provider was associated with increased care for PFDs. And so different populations with limited healthcare access are going to seek care differently, right? We know that. I think these next two studies are really insightful. This came from Duke and insightful in terms of different populations' perception for care. Oh gosh, my computer is trying to die. I'll charge it. Um, so the first study, they conducted 12 focus groups with about 113 community dwelling women. And the study found that while the experiences related to urinary incontinence was similar between Black, White, and Latino women, there were different perceptions around care-seeking, right? Specifically, Latino women maintained more secrecy around urinary incontinence and thus reported longer delays in seeking care, while White and Black women described discussing their urinary incontinence symptoms with close friends and family, which sort of normalized their symptoms subsequently prevented care-seeking, suggesting that there's definitely a cultural impact for seeking care for PFDs. And then there are a lot of studies that suggest that when care-seeking barriers are present, they may differ across racial groups. In the interest of time, I won't go through all of them, but I think they're worth, you know, if you get, and I'm happy to share my slides, my resources will be up there. But to, again, thinking about that framework in terms of structural vulnerability, different populations and how they interface with the healthcare system and how that impacts care-seeking. And so, which brings me to my fourth point, and, you know, again, this is probably like a no-brainer for people, but really in order to prioritize a health equity lens in FPMRS, we do need to individualize care, leverage culture, and really leverage community. And then I'll go into treatment. I'm just going to pause for a second so I can grab my charger so that this doesn't die on me. All right, so the webinar won't end abruptly. And so in terms of thinking about treatment, you know, there are studies that highlight, the results basically highlight who gets certain treatments, right? So for example, Boyle, for example, they have a study that looked at, you know, how many people get certain treatments, and they found that, you know, the results basically highlight who gets certain treatments, right? So for example, Boyle's, they found that 76% of women undergoing surgery for SUI between this time period were white compared to about 0.3% of women who were African-American. And Schar, in 2008, sort of found, had a similar finding. When this study from 2015 actually looked at disparities in use of sacro-neuromodulation over a 10-year period and showed that non-white patients were less likely to undergo treatment, this treatment modality compared to white patients. And then one of our co-fellows, Dr. Cadenas-Trowers, this year published a NISQIP study that showed that obliterative procedures were more likely to be performed in Black, Hispanic women, and women of, and other minority women. And so, you know, thinking about this, like we, I mean, I think it forces us to examine our care, but just put that on pause, because I do have the takeaway from this in terms of what's missing from these studies, like what, you know, these are large database studies and what we're not able to capture that's really, that's driving these, right? And thinking about this in terms of Wernicke's model. And then, you know, there are some studies that suggest that insurance coverage impacts that. So Washington, Dr. Washington and her colleagues in 2011 showed that women with Medicaid or no insurance coverage were less likely to participate in pelvic floor physical therapy. And in 2016 studies disturbing Black and Asian women were less likely to report being offered surgical invasive treatments for UI. And Anger in 2007 found that among women who underwent surgery for stress union incontinence, this was in Medicaid beneficiaries who were over age 65, non-white women were twice as likely to have a non-neurologic complication. We also studied this with the NIAIDS database recently, our work is published in IUJ, I think it just got published, looking at complication rates after prolapse surgery. And we found that Black women had about a 20% increase in odds for complications compared to other groups. And that was after controlling for everything that we can control for in the database. So what's missing? What's missing is these studies were unable to account for patient preference, right? For treatment, what patients are being offered, surgeon bias, and then again, thinking about those structural factors, racism. And I promised that I would bring in this article and thinking about all of those treatment studies, next week, the thing that we have to do in terms of applying the health equity lens is to think about care delivery and really prioritize and push for care delivery that is free from racism and discrimination, right? I think we are a ways away from really being able to completely measure structural racism, but we know that it impacts health inequities. The databases are not gonna tell us that, we can talk about why we're not gonna be able to measure that with large databases. But in this study, this article, everyone should read it, it's really quick, it's not difficult to read, it's so beautiful. Cause it really goes through how structural racism really that ends up manifesting in policies can really impact health and lead to health inequities. And so to me, that's what's missing from the studies that we have that look at those disparities and treatment outcomes. And a lot of this, my co-fellow and I joke that a lot of these studies say more research is needed to elucidate the reasons for these disparities. And he went on a rant the other day and says, we don't need more research. He was like, it's just racism. And I said, you know, Sang, you're right. So it brings me to my sixth point and I'll try to fight this cause I do wanna leave some time for questions. As we think about equity, anytime that we're thinking about equity, particularly, like I said, for those of us who would think about advancing disparities, working at risk, we do have to think about diversifying the workforce. Okay, this rests on a lot of the studies that suggest that outcomes for minority patients may be different, maybe even better when there's race congruent, you know, congruence. So let me just highlight this study that I found fascinating. This was in JAMA last year. And this looks at the demographic ACGME data. And it has demographic data for all the trainees in like all the specialties and subspecialties, ACGME accredited programs. And for FBMRS in 2019, there were nine black fellows in the country. There were three multiracial fellows. The other category, you know, like, I just feel like we're not giving people the opportunity to identify themselves. Again, problems with these categories. And 21 trainees who identified as being Hispanic and 33 Asian trainees. So, you know, when I did the calculations and really thinking about, you know, this is, you know, each fellow year is we're pumping into the workforce, right? And really think about does our workforce, does our training workforce reflect the population that we're actually going to ultimately be able to serve? Or does it adequately equip us to be able to serve, you know, different patients from different backgrounds? I didn't even mention this, zero, zero trainees who identify as Native Hawaiian Pacific Islander. We got some work to do. You guys, people may have heard of the study in the Bay Area where they randomized 1,300 African-American men to either have a black doctor or a non-black physician. And what they found at the end of the study that it was overall increased in a lot of recommended preventative health services, including flu shot uptake. And they basically projected that with all the increase in the uptake of the recommended preventative health services, it would ultimately lead to about a 19% reduction in the black-white gap in cardiovascular mortality. And so this is not saying that patients, you know, minority patients can't see other patients, but if they want, there needs to be an option, right? And more importantly, if we can't provide that. This study is also fascinating because it was saying, okay, do patients actually choose physicians of their own race or based on race? And for black and Hispanic patients, there was a significant correlation between the patient's ability to choose their physician and seeing a physician of their own race. And in particular, these numbers here, nearly a quarter of black and Hispanic patients with racially concordant physicians reported that they explicitly considered physician race or ethnicity when selecting their physicians. And among the patients who identified as being Hispanic, 42% favored factored language into their choice of seeing Hispanic patients. So in terms of, you know, now the perception of what was driving that, like what patients feel that they will get from that relationship and that concordance in that relationship, I think it's a gap in what we could be studying, right? Like, you know, because that may be some perceived patient barriers, right? And that they feel may be alleviated, I need to go through this, by having a physician who looks like them. This was not seen amongst the white patients. And finally, there's an argument that minority medical scholars tend to study problems that impact minority communities. So this study for better or for worse kind of shows that. I could spend like another talk talking about the study, but this was a study that was looking at NIH awards, particularly R01 grant applications and looking at the funding gap between white and black scientists. But one of the things they did in the study was look at topic choice. And this word cloud is depicting the word cloud for the topic choice, for the proposals that was submitted by African-American scientists. And, you know, like in this cloud, there's like disparity, population, community. Again, just exemplifying in terms of like the interests, and I'm not saying that all minority physicians are interested in this or have to be interested in this, but we made this huge case at the beginning in terms of the importance of this work. And, you know, historically, a lot of times it does, not exclusively, scholars from minority backgrounds tend to be interested in this work. So it's a workforce of individuals who want to advance this work. And then I would put a plug in that we have to think of inclusive research practices. Let me fly through this very quickly. This is our study from the Uggs Disparities Group last year that looked at the race, ethnic representation in publications that contributed to the OIB diagnosis and treatment guidelines. And what we did is we looked at the demographic representation of these groups in the studies and compared them to their demographic representation in the population. And this set out, then we came up with a representation quotient is what we called it. And basically it was a number to sort of measure over-representation or under-representation in these studies. So the black line represents a one. If you were at a one, that implies that your representation in these studies is equal comparable to representation in the population. And as you can see here, the representation of black, Hispanic, native, indigenous groups basically indicates under-representation in these studies relative to their demographics in the population. We then looked at it over a 30-year period. Surprise, not much change. But I think what's stark and what's kind of very disturbing is almost a relative absence of native populations in these studies. So in order to prioritize health equity, we do have to include the perspectives of all groups that are marginalized and to really be able to craft solutions there. So plug for inclusive research practices. If you are not familiar with Dr. Dahl, she's a gynecology oncologist, University of Washington. She has a piece that talks about this very thing. And she gives some concrete strategies and things that can be done to really prioritize equity in research and that I think is worth looking through. But that also, a huge part of it is leveraging community support and partnerships to ensure that just even from trial design and study design, you have something that is in line with both the needs and that has the buy-in and approval of the community that you're trying to study. And finally, in order to apply health equitableness to FRMS, I would say that, I spent a lot of time saying focus on those distal factors, but you can think about your institution or your practice environment as like a mini ecosystem and then think about the distal factors in that. And really, oh dear. Shine code, three, four, one, 14th floor, Northeast. Okay, so I would push that you have to treat equity as a core strategy. Shine code, three, four, one, 14th floor, Northeast. I'm at the hospital, clearly. And these efforts have to be leadership driven and it has to be an equity focus in those QI processes. Shine code, three, four, one, 14th floor, Northeast. So I just put up here like our DEI committee structure. Shine code, three, four, one, 14th floor, Northeast. It's a giant code. I think it's gonna keep going. Oh my gosh, I'm so sorry, guys. Okay, maybe it ended. But to say that like, equity shouldn't be like a siloed effort. It really needs to be incorporated through every aspect in everything that we do. And so when we focus on patient equity in our department, we really have taken an approach of where we're like, both rethinking about, like I said earlier, those variables that we collect, like what do we need to start collecting to really get at the root of things that we can actually craft solutions around that are actually going to impact patient equity? So this is a recap of the things that I threw out. I did it deliberately through the talk. I threw these in as concrete steps and strategies that we can use to apply high health equity lens to FPMRS. And I wanna end by saying, equity is not hard. It's really not hard. You just have to be deliberate because it does involve sort of undoing systems that are really, really, really deeply rooted. And I hope that you guys will maintain a passion for this in everyone's individual space, really strive to really advance this in our field. And I'll welcome questions. These are my references. All right, thank you so much, Dr. Brown. That was a fabulous presentation. We have maybe just a couple minutes for questions. Feel free to submit them in the Q&A section. I don't see any at the moment, but we'll maybe give people a minute or two. All right, looks like we've got one here. So what models do you know relating to disparity research? Yeah, so like I said, they are different models. The socioeconomic ecological model is like a huge one. They are like more specifically the National Institute on Aging Health Disparities has like a research framework that really does build on that socioecological model as does the National Institute on Minority Health and Health Disparities Research Network. Their framework basically combines the socioecological model with the NIA's Health Disparities Research Framework. A lot of them all end up being similar in terms of ensuring that you're placing individuals and populations in the context or in the background of all these macro societal factors. And then like, for example, the National Institute on Minority Health and Health Disparities Research Framework has some bidirectionality in terms of really emphasizing that the effects of like these different factors like can wane over time, can change over time. And so that goes to sort of like the scale of the impact of whatever the structure determinant is, for example. So those are two models I can think of. And then there are models for like care seeking, for example, that are sort of similar but focus more on healthcare utilizations like the Anderson model. And then we have a couple other questions here in the chat box. So can you please talk about black or Latina women having obliterated procedures more often than white women? And sort of a secondary question to that, are they also less likely to have third line urinary incontinence treatment? Yeah, so Dr. Cardenas-Trauer's paper specifically looks at, touches on that, being more likely to have obliterated procedures. And that's, I'll talk personally about what I think that, or what could be contributing to that. So I think in a lot of the research that looks at treatment utilization, we almost never can account for what patients were offered, right? How the options were presented, what biases exist in that. And so I think that there has to be some contribution to that, right? The other thing that we can't necessarily look at in terms of like, and so like in that paper, they did, they controlled for some, all those other demographic factors and they still saw that. So I have to believe that there are some systemic issues in terms of either what's being offered or what options are available to these individuals or what biases may exist that may be driving these. And we unfortunately just don't have that in that data set at least, so look at that. And in terms of black women being less likely to receive third line UI treatments, there was that study that I highlighted in terms of sacronary modulation, didn't look at all third line treatments, but just sacronary modulation and non-white women, which included black women were less likely to undergo sacronary modulation compared to white women. Okay, great. I think that's all the questions we have and we're a couple of minutes over. So I think we can maybe wrap things up. Well, thank you so much again, Dr. Brown. Thank you. And then just briefly on behalf of us, I'd like to thank Dr. Brown and everyone for joining us today. Our next FPMRS fellow webinar will be held on Tuesday, April 27th at 8 p.m. Eastern time. And you can visit the OGS website to sign up for that. So thanks again, everybody. Thank you.

health disparities

FPMRS

social determinants of health

pelvic organ prolapse

urinary incontinence

systemic racism

research on health disparities

individualizing care

diversifying the workforce

equitable care