Welcome, everyone, to the AACP ACLEPS Companion Society session. I'm Amit Gokhale. I'm the chair of the Education Committee for ACLEPS, and I'll be moderating this session. Just a quick recap about ACLEPS. So ACLEPS stands for Academy of Clinical Laboratory Physicians and Scientists. It was founded in 1966. It was founded to encourage and advance the highest standards of education in laboratory medicine, to promote the highest standards of resident training and postgraduate education, encourage the highest standards of service, education, and research in laboratory medicine. The title of our talk today is Informatics Challenges in Providing Inclusive Care for the LGBTQ patient population. Today's program objectives include to summarize current concepts and technical challenges in incorporating sexual orientation slash gender identity in electronic health records and laboratory information systems, to identify areas of potential confusion and opportunities for adoption and usage of this information, and also to illustrate how research data from the transgender and non-binary population may be utilized to improve health care. And now it is my pleasure to introduce the speaker for today. Matthew D. Krasowski is a clinical pathologist and the Walter L. Beering Professor of Clinical Education at the University of Iowa Hospitals and Clinics. He currently serves as Associate Residency Program Director and the Vice Chair of Clinical Pathology and Laboratory Services in the Department of Pathology. He is board certified in clinical pathology. Please welcome Dr. Krasowski. All right. Thank you. Good afternoon. I'll list my disclosures here, not related to the material I'm presenting. And so what I hope to get out of this, to get out of the session today is to learn some of the challenges here. So some of these issues, as I'm going to show you, are pretty complex. I've done a fair bit of research with collaborators into the effect of gender-affirming hormones on lab tests, and I'll use that as an example kind of later in the talk, but show you that the way that gender identity, sex, and sex assigned at birth is going to be in electronic health records actually makes this pretty complicated. And so I want to just give some flavor of that. So a little bit of just terms, I'll go through this part fairly quickly. So the term sex assigned at birth, sometimes called birth sex, and so this is usually something that's pretty obvious on birth by visual appearance of sex organs, but sometimes you may need additional information, chromosomal karyotyping, biochemical genetic studies. You can imagine a scenario of an infant with ambiguous genitalia where you can't immediately declare the sex assigned at birth. So traditionally, this is divided into male, female, and then the other category would be intersex or differences of sexual differentiation, although medical records tend to just do this in the male, female. Legal sex is actually what most of you see in the medical record. It's the sex that appears on legal documents. It's typically the official sex in electronic health records. And what's common for a lot of systems, there's something like male, female, unknown. Unknown is often a transient category. Trauma patient. We've got some that are systems like outreach specimens where they just didn't send us who the gender was. And so in that case, it's unknown, but that ends up being a pretty small percent. Now legal sex is often going to be the same as the birth sex, but it can be legally changed. And I provide a link there to what is the process of doing this across states and territories. I'm in the state of Iowa. Iowa, for example, to legally change sex, there has to be a physical change, could be hormones, could be surgery or both, as part of that process, in addition to all the other legal stuff that's involved. Gender expression would be things such as clothing, mannerisms, and voice. Gender identity is a personal sense as a gendered person doesn't always correspond with birth sex. So you arrive at the term cisgender, where there's congruence between birth sex and gender identity, and then transgender would be a broad term to describe those as a gender identity that's incongruent with birth sex. Non-binary or genderqueer would be an umbrella term for gender identity that's not solely male or female. It's identities that are outside the gender binary. And someone could identify as non-binary but not endorse if they identify as transgender. That's certainly possible. And then a broader term would be gender expansive. The exact terminology for this is a little bit elusive when I looked across websites, but it's an umbrella term for those who do not follow gender stereotypes or who expand the ideas of gender expression or gender identity. Gender nonconforming is sort of a related term that you can hear. And so I'll use gender expansive sort of as a broader term when I get into some data later in the talk. And then pronouns are words that describe a person that's often gender specific. It's important to keep in mind that there are languages that don't use the gender specific pronouns, or that will have the same sound in written as spoken language, but a different word written. In the US, obviously, they're different. It's he and she. But some have heard gender neutral pronouns, they, them, is a common one that you often see now. And then sexual orientation would be enduring pattern of a romantic or sexual attraction or a combination of these. The person's opposite sex or gender, the same sex or gender, or to both sexes or more than one gender. A lot of different categories here, heterosexual, gay, lesbian, bisexual, other categories like pansexual and asexual. Okay. So how does all this relate to the electronic health records? And so traditionally, what you're going to see, and many of these are actually identifiers for patients, legal sex, legal name, medical record number, birth date are very common. Basics are demographic features. But electronic health records are increasingly including fields for gender identity, sexual orientation, sex assigned at birth, and preferred name. And a number of groups, working group recommendations, meaningful use guidelines, and promoted adoptions are what is known as SOGI fields, sexual orientation, gender identity functionality, and EHRs. Okay. So here's an example. It's a little bit hard to, maybe a little bit harder to see. This is actually from a publication. I will advise people here, if you take a screenshot from your EHR, be very careful that your EHR vendor approves that. So I'm using this one because this is published and out there. If you just take a regular screenshot, you'd be really careful in a public forum. So this is for sexual orientation is at the top, and you'll notice there are a number of options there. Very common in this sort of scenario that legal sex is sort of grayed out. It's not something the patient or someone else can just change directly because it requires legal documentation to do so. And then you have, for gender identity, the number of options here, male, female, transgender male, transgender female, non-binary. You also have options for sex assigned at birth, and then also for pronouns, the patient pronoun. One thing I want to point out here, though, is that in these sort of implementations, they're allowing you other choices than just binary choices or just several choices. So you will see things like don't know, unknown, choose not to disclose, other. And when I show some data later, these become really, really important because a significant number will endorse these rather than picking some other categories that are available. And keep in mind that one, in many of these scenarios, patients may not fill these out, right? They'd be blank. So choose not to disclose is actually a different option than just leaving it blank, as we'll see. Okay. So let's look at an application here, sort of a case that I'll round to. And in this one, you have a transgender man who presents for primary care visit. He was started on a testosterone transdermal patch 12 months ago, has not had any gender-affirming surgeries, orders sort of a common panel of chemistry and hematology tests, complete metabolic panel, hemoglobin A1c. So the question is, which of these tests are likely significantly impacted by hormonal therapy? If reproductive hormones are measured, what changes are expected and what reference ranges should you ideally display or at least provide information for? So one key here is that this individual has been on testosterone for 12 months. And from the literature, probably most of the changes on labs happen within like six months, even earlier, but 12 months is certainly long enough where it's sort of reached a steady state. The second case is very similar, but it's a transgender woman who's taking estradiol. Otherwise all the other pieces of the case are the same. So general issues here, one is, what laboratory tests are actually affected by gender-affirming hormonal therapy? Right? That's one basic question here. Are they even affected at all? And then if you're going to show a reference range, what should it be? What sex or gender should you use? Is it complicated enough maybe where you don't do that, but you show an interpretive comment or link to some other source? Let's just do this scenario where nothing's changed in the EHR. You just use the legal sex, assuming the person has not changed the legal sex. What would be the impact of that? All right. So this gets into the issue of transition. So this would be a social medical process to facilitate congruency between gender identity and socially perceived gender. It may include gender-affirming hormones. That's actually most of the data is right now in terms of how do gender-affirming therapy affect lab tests. And so testosterone, estradiol would be the most common. But additionally, some things like hormone blockers may be used and then endor surgery. So I will say in the existing literature, it's very weak in terms of those who have had like ovariectomy or orchidectomy. There's just not a lot of data. You can make some inferences from it, but almost all the data currently out there is with gender-affirming hormones. So now the options may be influenced by health insurance, finances, other practical constraints. And my institution has actually two LGBTQ-focused clinics. And this is something they navigate all the time. Insurance doesn't cover certain things. You've got to try this formulation because it's cheaper. And so there's going to be variability based on a number of other factors simply other than just doing hormones. So in terms of feminizing hormone therapy, estradiol would be the mainstay. There's oral. There's intramuscular. There's hormone patch, progestin sometimes. And then drugs that are androgen antagonists are broadly defined like a spironolactone and then finasteride. Spironolactone is just worth sort of keeping in the back of your mind because that affects electrolytes. In addition, it's kind of a messy pharmacological drug, so it has a number of other targets. And so there are cases where that's going to affect potassium and sodium. So that's a possibility. For masculinizing hormone therapy, testosterone is patch, topical gel, intramuscular. Worth keeping in mind, we've seen this a few times, topical gel can sometimes contaminate phlebotomy sites. And if it does, you'll get a testosterone of 2,000, so unexpectedly. And so it's always worth exploring when someone complains that your testosterone is way off in measurement, think of pre-analytical errors like that. So less common with patch. Intramuscular usually the issue is more timing relative to the injection. Okay, so there are examples of surgical interventions here. I just highlight the ones that would actually change hormone production, so orchiectomy or orchidectomy would be removal of testes. So that would obviously impact hormone production. And then for trans men, you can have ovariectomy with or without hysterectomy, and that would reduce estrogens. All right. So reference ranges. This is where things get complicated. All right. So if you think about it, I mean, how a reference range is typically designed. So some people often say, well, it's based on a group of healthy subjects. Many labs, many tests, we use like a 95% range, you know, plus or minus two standard deviations, you know, common for a lot of our common chemistry tests. Some of our tests we use like target values. I mean, lipids are a good example of that. If you actually use the 95% interval in the U.S., they would be much higher than the target values that are recommended. Other things like troponin, we'll use like a 99th percentile. And so obviously there's different ways to construct reference ranges. Now notice, reference ranges by and large are reflecting sex assigned at birth, right? They sort of make this assumption that that's what's happening, even though it's almost never going to be mentioned in the inclusion criteria. And so this can be an issue if you're using legal sex as a proxy for sex assigned at birth. This is where things can get complicated, right? So sometimes people will say, well, you know, what is the cisgender range for a test? And you've got to be a little bit careful of that terminology, because the range that for sex assigned at birth may apply to someone who identifies as transgender, but is not taking gender-affirming therapy, right? So just kind of be careful with that. Okay, so if you think about, well, what tests could possibly be affected by, let's say gender-affirming hormones, the logical place to look is tests that already have sex-specific ranges. And in fact, existing literature, retrospective, moving into prospective studies, that's pretty much, the labs that are affected almost always have, already have a sex-specific range. So we have a number of tests that just in general, I'm just talking about the standard reference ranges that you would see currently. There are tests like ALT, AST, kratnin, GGT, hemolytic hematocrit, LDL, testosterone, japonin. Typically males have higher, you know, higher values than females, right? And then there are some tests that are typically higher than females, estradiol, HDL, antiprobian P is another one. And now note that hormones may or may not be the main physiologic driver of these differences. In some cases it is, or at least it's, it's can, with through secondary effects it can. For example, if you look at hemoglobin and hematocrit, testosterone is higher than males and females in almost every animal species going out quite a ways, because of higher testosterone levels. And so, and in fact someone who's just, let's say a cisgender male who's taking testosterone supplementation, they'll drive up their hemoglobin and hematocrit because it's a strong driver. Okay, so what will happen with gender-affirming hormones? How could they possibly affect lab tests? So you have a number of possibilities here. One is that they don't change it, and then it just stays aligned with sex assigned at birth. You could have values that align with either affirmed gender for trans men and trans women. You could have a little more complicated case that aligns with one, but not the other. I have examples of that. And then you get sort of, well, it doesn't resemble either. It's either broader than either one, or it's sort of in between. This is actually what we see with some of the reproductive hormones. It's complicated, okay? So if you look at tests, and this is just a summary of some studies, I'll show some more graphical data in a second here. So if you look at tests that don't really change with gender-affirming hormones, many of the common high-volume chemistry just don't really change. Sodium, chloride, potassium. Spironolactone will affect sodium potassium a little bit, but that would only mean individuals taking that. There are some tests that align completely with the affirmed gender. The best example of this, and if you're going to take one test away from this, hemoglobin and hematocrit are the perfect example of this. It completely flips to the opposite gender, in terms of what the ranges look like. And so in that case, if legal sex hasn't been changed, you're going to be off in those tests because it's flipped to the opposite gender. HDL, LDL also show this trend, and then sort of newer data is troponin, NT, probi, MP also basically flip as well. But then you have some examples here where in one case it does align with infirm gender, but the other one in case it doesn't. And I think the really good example of this is keratinin in the so-called liver enzymes. And I was part of a collaborative group where we did perspective studies. A clue to this was seen in the retrospective studies, because what you found was is that in trans women, the trends were not consistent across studies. You kind of saw a little bit of change in one, but not the other. When you averaged them out, it didn't really change. Whereas, for example, for keratinin, it's a very robust finding that testosterone therapy increases it. Not a huge amount, but it moves it into the sort of standard male reference range. And same thing with liver enzymes. The question of how clinically significant that is is a more complicated one. For keratinin, I think effects on EGFR I think are going to be the biggest. But for liver enzymes, it probably doesn't impact clinical decision making a ton, but it could. And if you will react to just something being inside or outside the reference range, it could have that effect. And then values where it doesn't resemble either sort of standard reference range. Reproductive hormones certainly show this. So the data that comes from prospective studies, I list the publications here if you want to look at those. And let's look at an example here. So here, just to kind of orient you, for lack of a better way to describe this, I'll say the standard female reference range. I put it in quotes. That's the one you'll see in your EMR right now, right? And then male reference range here. What you'll find is, is that in this case, with taking estradiol, that the values will be lower. And so for transgender women, they will align with the standard female reference range. And in contrast, the values increase with testosterone. Transgender men will align with the male reference range. So that one, if you use sex assigned at birth, it would be misleading, because you're going to see the opposite. How about you only align with one gender? And this is kind of what I was alluding to for keratinin and some of the liver, so-called liver enzyme type tests. So for transgender women who are taking estradiol, the values don't really drop that much, like a little bit. And again, it was inconsistent across retroactive studies and didn't really see it in a prospective study where everything was standardized. And so there's very minimal impact here. It aligns with sex assigned at birth. In contrast, for transgender men taking testosterone, you're going to see it increase to the sort of standard male reference range. And then sort of newer data here is kind of exciting, is that these are baseline levels of NT pro BMP in healthy subjects. They flip to the opposite gender as well. And so in this case, actually, the female reference range commonly used a little bit higher. And with estradiol therapy, you drift up into that range. And then with testosterone therapy, you align with the standard male reference range. And if you look at the literature on this one, it's interesting. The strongest driver here actually appears to be testosterone. Testosterone is inversely correlated with NT pro BMP all the way from puberty on. And there's a variety of studies that have gotten that out. And then I put this under it's complicated. So here you have the case of testosterone. Let's look at the case of transgender men. We'll tend to find here is that and there's a lot of variability across studies here based on how testosterone is prescribed, the dosages, all that. What you tend to see, though, is sort of a wider spread of data than the sort of typical male reference ranges that would be published. And so it basically is aligned. And there's been some debate in the literature about like the endocrine society actually has some pretty specific testosterone targets. But when I've talked to providers who prescribe, they're often working with patients to see desired effects. And for some, that may be a value that is sort of at the bottom part of the reference range here. For others, it may be a much higher value. And that may be preference. And then in the case of transgender women taking estradiol, this doesn't really suppress testosterone to the level that you would actually see, for example, in cisgender women. In this case, without surgery, it's not going to get down in that range. And so there is a variable here in terms of using other medications, spironolactone, finasteride that in some way will affect androgens. But generally, this is kind of what you see. So if the goal was that you had to suppress all the way down to this range here, that's not actually what you see in most individuals. And then for estradiol, in transgender women, what you'll see is sort of a wider spread of data. Now, the question here is what's your comparator reference range? Depending on age, you'll probably be looking at a non-pregnant cisgender woman as a reference range. In transgender men, testosterone alone doesn't suppress estradiol down to the levels that you actually see in cisgender men. And so outside the U.S., there's more use of aromatase inhibitors that would block estrogen production. It's not something you commonly see in the U.S. I do want to tackle one issue here, just if anyone's thinking this. One of the most common questions I've gotten is, this is so complicated. Can't we just take the bottom of one reference range and the top of the other and just have a transgender reference range? It's a really common question that I get. It seems logical in some ways, but it's actually not a good idea. And I'll show you why. So let's look at the example here where you have this sort of scenario. So let's look at, this could be like hematocrit, for example, hemoglobin hematocrit. Let's look at transgender men on testosterone, right? And so the value here, I just put two stars, for transgender men on testosterone and for the standard male reference range, it's both in the reference range, you'd be fine. This value over here, which would be within the female reference range, is abnormally low. It's anemic. So if you just had one broad reference range, you'd be calling both of them normal. I mean, that'd be a hemoglobin reference range of like 12 to 16, something like that, you know, 11 or 12 all the way up to like 16 or something like that. And a similar thing with a transgender woman on estradiol, it's actually expected that testosterone, sorry, that hemoglobin hematocrit is going to drop. So this is within reference range. This is actually abnormally high in this context. And you would have just called it low if you still used male as the legal sex in this scenario. So yeah, don't just create one giant reference range. The other question people say is, well, can't we just have male, female, and then T as legal sex options? If that were to work, it would have to work that you would have, you know, this kind of broad reference range. And that's not what it shows. Okay. Any questions at this point here? Yeah. So the question was on use of these intervals for presenting in sports. Could you use it? Well, theoretically, yes. Politically, that's not where that question has gone, I think. I'll leave it at that probably. Yeah. But it is an interesting question to say, you know, is it within the range that you would see and is it a range expected? Yeah. Yeah. I mean, that's complicated because I think in this scenario, that person may have fallen under differences of sex development, sex differentiation, intersex type, or it may not. But yeah, that's a question. I mean, yeah. If you just happen to have a higher value, ultimately, I mean, I think for like Olympics and other scenarios, they're going to have to, at some point, they're going to have to make a decision. It's not simple at all. I mean, that's, yeah. I know the case you're talking about, though. So the question was, how do we, like, I guess, whatever gen excavation has, how do you put what's relevant for reference range in the ER? Yeah. I think, I mean, the data is sort of lacking there. All that we've shown so far is that basal levels switch a little bit. It doesn't say anything about 99th percentile, doesn't say anything about outcomes. I think with troponin, there's probably issues with like, it's, yeah, it's not totally cardiac mass. With liver enzymes, the liver, it may be actually a slight increase in liver mass that's causing it. But yeah, there's very little of this type of data that's out there. Okay. Oh, so the question was, I think, with the troponin, right? So what's the appropriate sex, basically, to assign to that? Because you may not actually see an increase in cardiac mass with gender-affirming hormones. So can the information in SOGI fields help? This may not be reassuring or not. I'll just, I'll show you what it is, though. So I think some variables to consider here, some of these I hadn't really thought about beforehand, which is that you may roll out this functionality in an EHR, but the question is, how often are people actually putting this information in there? How's it getting in there? So there may be differences in your overall patient population versus gender-expansive patients. I'll show data from my own institution where that's a huge difference. Do people understand the terminology? We did a study, retrospective study, IRB approved, that looked at this, and there's obviously patients who are confused by the terminology. They even indicate that in a comment. They don't understand it. And the other thing is that, in a lot of cases, what you really want to know is gender-affirming therapy, not just how someone may identify, but that's really what's going to dictate changes to labs. Okay, so I'll show a little bit of data here. So this is from my own hospital, University of Iowa Hospitals and Clinics. We're an 860-bed hospital. And then what I list here is active encounter in our system since 2018, which is when we first rolled out SOGI fields. Give or take, you're looking like, you know, upper teens, 20%, people who have input information, gender identity, sexual orientation, are sex-assigned at birth. These are 12 and older. A similar study at Rush, as we're not that far from Rush for ages, similar sort of design right at very similar figures. Okay, now important to keep in mind, if you go back further, of all patients in our EHR, going back decades, many of whom are not alive, very few actually had this in there, right? And some are no longer in our system or active. But if you're going to try to go back and data mine, you got to keep in mind, you're only going to get data when it was first entered. It's not going to be retrospectively put in. Now, we also looked at our patient population that had clinical encounters and ICD-10 codes that could be compatible with a gender identity of transgender, non-binary, or similar. And well over 90% have SOGI fields in there. And if we talk to those clinics, this is part of their workflow. They get a tablet before they register. They're encouraged to fill these out. The provider asks questions about it, clears up any confusion. That workflow doesn't seem to exist in any other clinic site in our system. So a few clinics actually had this as part of the check-in, but don't really follow up. Okay, now I'll walk you through this. This is complicated, but I think this is important. These are all the combinations you can get with our current build. Here is gender identity. Male, female, transgender male, transgender female, non-binary, other. This is choose not to disclose, or you just left it blank. Sex assigned at birth, male, female, unknown, not recorded, uncertain. Not recorded is not recorded in a birth certificate. Uncertain, not disclosed, or you left it blank. Legal sex is male, female, or unknown. All right. If you look here, there's the group that's predominantly, I guess you'd say cisgender, for lack of a better term here. Here's someone who's identified as gender identities, male, sex assigned at birth, male, legal sex, male. There's 14,000 that were in our study, but there were 36,000 who legal sex is male, and that's all they filled out. That's all that's in there. You're making a presumption, right? I mean, they may not be, but at least a high percentage are probably. There's a lot of combinations here that you hardly ever see. Okay, so the question is, how do people who are gender expansive actually identify, and how does that relate to hormones? So I want to spend some time on these slides. They're kind of dense. So pattern number one, I think, is that someone just identifies their gender identity. They choose one of these three choices, okay? They choose transgender male, female, or non-binary. We then chart reviewed as many as we could to see how many actually from clinical documentation identify as gender expansive, and it's almost 100% across every one of these categories. So we didn't see any evidence that people fill these out by mistake. You can always imagine there could be drop-down errors. That seems to be very rare. We do find, I put an asterisk by these. These are not very common, but they're errors, and what happened here, for example, this person meant to put transgender female. That's clearly how they identified in the chart. They just picked transgender male by mistake or just because of confusion, and we saw some other ones like that. We also have some combinations here. I highlighted with the box. These have presumably legally changed their sex, okay? So in this case, sex assigned at birth is female. Legal sex is now male. Some of them identified non-binary. Some is transgender, and so we see those, okay? Now, as we look at these, 99.2% by chart review are gender expansive, and almost two-thirds are on gender affirming therapy, but not all. So two-thirds, right? That's pattern one. This is where I thought years ago starting this project, I'm like, okay, we'll have things like this in the system. We know who to assign. It'll be easy, and yeah, it's not that simple. Second pattern sort of surprised me, which is that these are individuals who do not identify transgender. They don't put transgender non-binary, but the combination of male female for gender identity with the others helps you infer that they are, and so in this case, sex assigned at birth is male, identify as female, legal sex is still male, okay? Here's an example, though, where sex assigned at birth is female, gender identity is female, and legal sex is male here, okay? So of this group, 95% are gender expansive, and almost 80% are gender affirming therapy. Now, when I look at this, it made sense thinking about it, because like in Iowa, for example, people have gone to the work of changing their legal sex, had to go through a lot of steps to get to this point, and a very high percentage are on gender affirming therapy, and so that's what we see. Pattern three, this is the one that I didn't know what to expect looking at this. So gender identity of other, and we saw a lot of free text responses here, agender, genderqueer, demiboy, demigirl, gender expansive, a lot, and in some of these cases, quite a few actually from chart review are gender expansive. I didn't know what to expect with the choose not to disclose. We seem to get a mix of people where this question makes them upset, and they put it, but also quite a few who identify gender expansive and use this option, okay? And similar thing for sex assigned at birth. We see some choose not to disclose, okay? And so even within this group, you have some that there's an official change of legal sex that you can presume. In this case, about 40% of these are gender expansive. 17% are on gender affirming therapy. So if you go back, the single most common group that's gender expansive is the first one. This is the next most common. Pattern of male, female, and then the third is the least common. But this is still several thousand patients. So this is going to be tricky because there's nothing, if you're trying to assign the reference range here, there's nothing that's going to tell you, guide you very easily here. I mean, we don't review the charts on every one we put a reference. It's not, that's not feasible. Okay. So what are some challenges here? Well, one is that well, one is that there are a very large number of combinations here, and so this makes this issue very complicated. If this is the kind of design you're going to see across EHRs, you have a lot of choices. People are going to select different choices. So one thing that we found, other and choose not to disclose is actually pretty common among non-binary. And so in the other, when they selected other, often you would have those other designations, genderqueers, anything like that. Some patients provide free text, not understanding the terminology. We saw this with sex assigned at birth. And the question is, if it's not on your birth certificate, should you still be able to answer this? And what seemed to confuse people was, well, it didn't really say on my birth certificate, I'm just going to put it's not recorded on my birth certificate. And then I said small percentage responses are not logical. Other than our LGBTQ clinics, I don't think anybody audits this. Nobody checks this for consistency, and you're allowed to change this in our system in the patient portal. So you could change it, and even if it doesn't make logical sense, it would go through. But the other thing to keep in mind here is, let's say at our hospital, someone's already changed their legal sex, they show up to our hospital, and you have no other indication on background, that's the legal sex you'll use for all your tests and reference ranges and things like that. Okay. So in terms of reference ranges, I guess the three tests I think, or the three categories I think are the most important, like you could act on right now, or at least have the most, is keratinin, hemoglobin, hematocrit, and liver enzymes. I think those have solid data behind them. I hope we get there with like troponin and some of those. But these are the ones that are impacting, I think, in a meaningful way. We're in desperate need of both EGFR studies and outcome studies in the transgender population. They just don't really exist. You'll find case reports or series of where inconsistencies, like EGFR suddenly shifted because someone has legally changed their sex, but there's not too much beyond that. And what some of the EHRs do, including the one that we use at our hospital, is Epic, for example, has a function that will just detect if there's discordance between any of these variables and identify that. Initially I was like, is that really the best? That may be, in some ways, your best option on when to put a comment in or things for some of these tests. Because I think the combinations here are too great. If you looked back, well, do you have a comment that's based on transgender male or female? Or do you do... And the thing is, you can get into a lot of rules, a lot of complications, and get very complicated. Right now, that type of functionality just says there's some discordance. And you could either choose some rule that would act upon that. So I think there's some options here to think about. None of these are necessarily great, but for example, if you saw discordance, would you suppress the reference range and provide an interpretive comment? Now, here you've got to be careful. If you're going to suppress the reference range, but the test has clear abnormal flags or critical values, you don't want to lose those. We actually saw that happen in our system when legal sex is unknown, because we didn't have unknown programmed with critical values for everything, and occasionally you'll hit a combination like that. So that's one possibility here. The second possibility would be you still use a legal sex reference range, but I tend to comment about how changes that might occur. A template or something like that is like a reference range for this test is not displayed. Is there one or more differences seen here, the patient receiving hormone therapy? This testing is likely to be significantly impacted. The third option, and I know some sites have done this, is to create order codes that are specific for gender affirming therapy. I've heard of that most frequently with estradiol and testosterone. So that's one possibility. Part of me, I'm a little bit nervous about me creating a hemoglobin hematocrit that's I think that gets really complicated, and probably not the easiest of options. So other things to think about. So please don't construct just huge, broad reference ranges for both populations. I think that you're likely to run into trouble. I think the existing data is pretty sparse for the non-binary population. In the studies where we were recruited, non-binary has been a pretty small percentage of the total, even though we're actively trying to recruit transgender and non-binary. We have individuals, non-binary or otherwise, who are on lower hormone doses. Right now, the data doesn't really get to differences in doses, formulations, things like that. That level of data is not there. And then one thing, if you look at other areas of the lab here, is as more functionality exists over time in the LIS, maybe middleware, things like that, are there things that would be helpful on a specimen label for things like pap smears, for things like microbiology from genital sources, that could give you some clue that it may be impacted by gender-affirming hormones or otherwise. So that's certainly something to think about. Issues to think about with the SOGI fields, a broad issue I think about is what is the role of healthcare providers, the institution's resources, to understand, to try to encourage people if they're willing to put in this information, but also understand the terminology. And with a lot of different combinations out there, you know, should there be some level of verification or authentication? One thing that's also been talked about is should sex at sign of birth be something that's actively sort of elicited, or should it just be a voluntary declaration? If you make it voluntary, you're going to get some of these not recorded numbers, certificate, unknown, things like that. Many of the EHRs do not have any options for intersex or DSD currently. So certainly could add that, but that's not in there yet. And what we found is very limited functionality with LIS and middleware software. Middleware may be not such an issue. I mean, one could imagine if middleware rules fire for critical values that are sex-specific, you may see a little bit of that, but I think, but in the LIS, it could certainly influence if that's the labels that you're seeing. And then in terms of patient factors, there's a variety of reasons patients may or may not fill these out or how they fill them out, because there's a variety of concerns. There's real concerns about discrimination, affecting health insurance. I worked with a number of medical students on projects, and one thing I hadn't thought about was that as the SOGI fields were rolled out, certain sexual orientations were flagged in our system as high-risk sexual activity. And people were like, well, I wish I hadn't put it there because immediately, you know, during a patient interview, I'm immediately down this pathway, even just because that's front and center on the front page of the EHR. And so there can be previous negative experiences with the health care system. And then I have a lot of interest in patient portals and privacy and how that displays. This is a really, really tricky issue with adolescents and with privacy with parents who can access at different ages. So you'll often see sort of access sort of change, maybe around 12 or 13. Some systems, like at 14, the child can have their own system, but parents with limited functionality. But that sort of varies, and there's very, very real implications there. And then I didn't talk about it much here, but I am a huge advocate for preferred name. And what kind of started me down some of these projects was the co-founder of our LGBTQ clinics came to our department to give a, how could pathology do better for the gender expansive population? And the thing that was mentioned first was, use the preferred name when you call someone in the waiting area. And at our hospital, the busiest area for like lab-only phlebotomy visits is a shared area with radiology check-in, and they just shout out the patient's name. And we ended up at our system adopting preferred name before the functionality became easily available. It was a huge amount of work, and it was just such a big step. Just use the preferred name. And so that can be a big, in patient-facing areas, obviously transfusion medicine, cytopathology, other areas, you might. And so if labels can display that, or however you're going to call out patients, I think that can be a huge, huge bonus. And so the EHRs and LIS will increasingly have this functionality. What I think is likely going to be a challenge here is that that market is very fragmented. And the large vendors will certainly go a certain direction. The smaller EHRs may follow eventually or may have different functionality to display this information. It's going to be a challenge if you have an EHR but with a completely separate LIS that's not the same vendor, you know, that some of the functionality may not carry through well to the LIS. I think in general, health professionals should be aware of the terminology and limitations of this data, you know, to sort of understand, you know, that. For example, I mean, someone could say, well, I just want to find all those identify as transgender male or female. If you only look for those two options under identity fields, as I've shown you, you've missed quite a few. And so you have to be aware of that. And so, you know, things are a little more complicated. And then the clinical laboratory can play an important role here in education and clinical care. And so whether it's in terms of providing interpretive comments, things in an online handbook, targeted education, whatever, I think that people are aware of this and, you know, can certainly try to improve and provide inclusive care. So all right. We have time for questions. I just gave image credits. These are all open domain, but just so I don't know where they came from. So all right. Thank you. Yeah. So just to rephrase the question. So using a similar EHR or something like you ran into the same issue, there's a lot of options here. I mean, there's multiple design reference ranges. Could there be a flag for gender affirming hormones or surgery, all that? I mean, like in our system, there is, but it's not one that patients can directly fill out currently. What we found, though, is that actually that would be nice if that existed. But the challenge is only like less than 1% had filled it out. I mean, yeah, I think it's hard because like, I mean, trying to get out of the pharmacy records is fraught with problems. You know, one thing that's happening out there is that there's more, there's a growing business to do these hormones by mail order, try to get around difficulties in getting them prescribed by prescribers. So in that case, you wouldn't know easily. But yeah, it would be, I mean, if you had a flag that indicates you run some risk that someone's going to might stop hormones or change for whatever reason. So I mean, I think right now with the current, I mean, like creatinine and liver enzymes and hemoglobin hematocrit, probably that's covers a lot of them. I think the cardiac markers will follow. I haven't really seen people do a lot of this with like microbiology testing, although it certainly could. One thing I've learned looking at patient portal data is patients read those comments more than providers. I mean, part of it's how it's displayed, a patient portal will actually just show the result continuously, the result, and you know, like it may require a double click. And I actually realized this in sort of an amusing way, although it wasn't funny to the patients, which is that when we changed our syphilis algorithm years ago, we just had an explanation of what the algorithm was, but patients were reading through the result right into the comment, thought they were positive. No provider made that mistake because it just said negative, they were done, they didn't care what the comment was. And we ended up suppressing the comment if it was negative, because it was not informative, you know? So, but some of these calls got forwarded to me and I am talking to some of the patients and I said, can you just, I'm wondering how you arrived at this? I'm like, ooh. I said, yeah, that would be confusing. And when we changed that, it fixed it completely. So now if you put some comments on how it may affect your gender-affirming hormones, are there some patients upset they see those? It's a possibility. So I guess just for the online audience, does it just, are there ways you could pull other sets of data and not just the SOGI fields that could do it, or are there examples of other challenges in, I can't think of any, yeah, that's an interesting question, though. Yeah, so just to paraphrase that, current functionality requires discrete data. I mean, in our own system, because we have a number of affiliated hospitals using our EHR build, you know, like our case, and I'm sure others fall in this scenario, we have to be careful what kind of complicated changes we make, because it's going to affect all those sites. And then the, you know, the IT folks start saying, Dr. Krasowski, we can't do that. And certainly reference labs would have difficulty getting any of this data that would require them. So, yeah, it's a difficult problem. So the question is, is there training that would tell those who may be identified gender expansive that the data is being used to improve health care? Yeah, I mean, I will say, I mean, it's, the health care experience has been really uneven for people I know, unfortunately. You know, so, I mean, that is a risk, and maybe why some are, you know, like, in our system, and what I've seen at least is those who seek care at the LGBTQ clinics as their primary base, every, I mean, just like, you see this in chart review, everything seems to flow well from there. The referrals seem to flow well, things don't seem to get messed up. And more recently at our institution, we've done that for adolescents, I think, well, but elsewhere, I think you just hear is very uneven. And a number of the patients, we have patients that drive to our hospital like four or five hours just because they feel like they get better, they get better care in this one area, you know. Thank you. Thank you, Matt, for a great talk. I just had one quick question. So as you're, I think you were mentioning in your talk about using preferred name for laboratory personnel or phlebotomists, what are some other ways that we from pathology that especially patient-facing or forward-facing personnel, how can we better provide inclusive care for these patients? Yeah, I think preferred name is a big one. I think just having some education on terminology and like in our own institution, for example, high percentage of our phlebotomists are recent immigrants from other countries. And so one feedback we got is just wanted some exposure to this area to understand the terminology, understand it, because may or may not have encountered it elsewhere. I mean, preferred pronouns don't seem to have a huge impact on pathology. It's not something that comes up. It comes up in other contexts in health care, but the preferred name one was a pretty big one. But yeah, just being aware of that. I mean, it's, if you look at like phlebotomy, I mean, for example, an LIS label is going to print as preferred name, the legal sex, so that's what they would see, you know. But others like transfusion medicine, I think, are more complicated because some of the standards aren't quite clear. Like you see this with donation of blood and some of the terminology becomes complicated to someone who's transgender, like, and people can self-identify and that may influence sort of donor-specific criteria, things like that. So it'd be good to have it in the curriculum and we have a collaboration with MLT program and then we've incorporated some of this in that curriculum, I think it's, and then so just so people are aware of it. Yeah, so the, I'm trying to think, it's been almost 12 years since our institution started. Yeah, they kind of grew the LGT, the question was about the LGBTQ clinics, how fast did they grow? I think for a while they're able to keep up with capacity and then they've added more providers over time. And what I've seen more recently is that the ties to specialty consults, different surgeries, has gotten a lot, you know, that's been worked out a lot more, particularly sort of the, you know, whatever baseline labs are needed, they're getting done in the way that, you know, that would help for whatever surgery needs to be done and for other referral care. I mean, the co-founder of the clinic told us that, I mean, some of the experience patients had in different areas like gynecology, she's like, we've got to do better than this. I mean, like we're, they were saying, and so part of what they're offering is also routine women's care as well. Certainly there are patients who now feel comfortable, they've gone to other providers for different reasons or, you know, maybe make the drive to Iowa City, you know, once a year is a long drive, but yeah, I think it's been really good. I think it's really positive. Yeah. So the question is about with certain types of tests, can there be confusion because of what's ordered? I think it varies. I mean, some places I think estradiol testosterone may not have been challenged in terms of testing. It's definitely come up with PSA and HCG and some of those, some of those also run into downstream billing problems because they, you run into those, those issues as well. So yeah. So the question was for like some tumor markers and others just to remove reference ranges completely. Yeah. I don't think that's a good, that's a great. All right. Thank you everyone.

informatics challenges

inclusive care

LGBTQ patients

sexual orientation

gender identity

electronic health records

laboratory information systems

gender-affirming hormone therapies