Hello, and welcome. I'm Amy Cohen, Associate Director for SMI Advisor and a clinical psychologist. I'm pleased that you're joining us for today's SMI Advisor webinar, Physical Health Monitoring for Diverse Populations with Serious Mental Illness, Opportunity to Fill Gaps in Care. SMI Advisor, also known as the Clinical Support System for Serious Mental Illness, is an APA and SAMHSA initiative devoted to helping clinicians implement evidence-based care for those living with serious mental illness. Working with experts from across the SMI clinician community, our interdisciplinary effort has been designed to help you get the answers you need to care for your patients. And now, I'd like to introduce you to the faculty for today's webinar, Dr. Christina Mangurian. Dr. Mangurian is a professor of psychiatry at UCSF School of Medicine and the UCSF Department of Psychiatry's Vice Chair for Diversity and Health Equity. She founded and directs the UCSF program of research on mental health integration among underserved and minority populations. She is a community psychiatrist whose NIH-funded research program focuses on improving diabetes screening and HIV care of people with serious mental illness, particularly among underserved minority populations. Dr. Mangurian previously served as the chair of the American Psychiatric Association's Council on Minority Mental Health and Health Disparities. Dr. Mangurian, thank you for leading today's webinar. Well, thank you so much for having me, Amy. It's wonderful to be here. I'll just start by saying that I have no disclosures related to the subject matter of this presentation. I wanted to start with just the learning objectives for today. There are three of them. The first goal is to make sure that everybody understands the increased burden of physical health diseases among people with serious mental illness compared to the general population. The second goal is to know the gaps in screening for people with serious mental illness, which subpopulations with serious mental illness are particularly underscreened. We're going to look at these subgroups. The third is ideally to learn strategies to improve screening at the individual, clinic, and health system level. Those are the goals for today. First, I'm going to just make sure we're all on the same page and give you some background. In the U.S., there are 19 million adults living with severe mental illness. This is illnesses like schizophrenia, bipolar disorder, or very serious, a major depressive disorder. This accounts for 6% of the U.S. population. I believe there's been other talks on SMI Advisor by Dr. Ben Druss, who's an expert in this area about how people with serious mental illness die 25 to 30 years earlier than the general population. It's often from cardiovascular disease. We also know from the prior literature that there's poor adherence to guideline-recommended metabolic screening. I'll get into that some more. That's screening for things like diabetes, dyslipidemia, and hypertension. That's particularly important since there's such high cardiovascular disease. We also know that people with serious mental illness utilize community mental health clinics significantly more often than primary care settings. This is important because I imagine a lot of you may work in community mental health settings. That's really what my focus has been, is really meeting the patients where they are. My work focuses on leveraging really strong public academic partnerships to improve the public health care system that people with SMI already use. That would be specialty mental health settings, so working within community mental health. I've had actually a couple of different experiences in two large health systems creating these very strong public academic partnerships. The first was in New York State. That was with Dr. Lloyd Sederer. He was the medical director in the New York State Office of Mental Health. This is when I was on faculty at Columbia University. Dr. Sederer really wanted to improve basic health screening of people with serious mental illness. That was back in 2008. Together, we partnered and were able to successfully implement health screening for about 15,000 people with a serious mental illness served in New York State's Office of Mental Health community mental health clinics. That was some work that you all can look into. The work that I'm going to be talking about today is actually some of the work that I did in California and subsequently. As Amy was mentioning, I work at UCSF. When I moved out to California, I worked closely with Dr. Penny Knapp, who at the time was the director of California's mental health services. She had been working on a program focusing on improving metabolic screening of people with serious mental illness. She partnered with me at UCSF to analyze administrative data to examine health screening. That's what I'm going to be describing today as some of the findings we had evaluating health screening of people served within the public mental health system in California. Here we go. We're going to look at this. I'm going to first just describe the overall study design. This is, again, a partnership with our public partners where I'm a health services researcher. I was doing a retrospective cohort study. That means looking at a group of people over time. I looked back and the population was people with serious mental illness who were receiving services at California community mental health clinics. These were the inclusion criteria for them that we were looking at where they had to be adults. They were prescribed any antipsychotic medication. We were looking at two different time periods because it was before and after an intervention that Dr. Knapp had implemented. So those are kind of below here. I did want to note that although it was prescription of any antipsychotic medication, 98% of these were second-generation antipsychotic medications. Another inclusion criteria was that these were Medicaid recipients and they were not dual eligible for Medicare. Now I know a lot of folks on the call may have patients who are dual eligible the reason why we did not include dual eligible patients was because we didn't have access to the Medicare data. So another thing many people on the phone know is that oftentimes the electronic systems of care are separate. And so we were kind of pulling from people served in the community mental health clinic and using that electronic health records and then matching with Medicaid data in the primary care side of the house. We had various specific exclusions depending on the screening that we were looking at. So if we were looking at diabetes testing, we excluded people who had diabetes before, for example. Or if we were looking at breast or cervical cancer screening, we were only looking at women. Again, these were the two study periods that we were looking at. This was pre-program and post-program. This continues to be more of the overarching study design. These are our outcome measures. We had multiple health screening outcome measures that were specific to our study question. I'm going to pull that up in a second. We also were looking at diabetes prevalence. So you'll see some, most of my work is on screening, but I also estimated some prevalence rates for diabetes. And then we conducted Poisson regression with robust standard errors to account for clustering by county as there are multiple counties in California. These are the various outcome measures and CPT codes that we used for the different screenings that we were looking at. So we were looking at diabetes, what were the rates of diabetes screening, what were the rates of HIV testing, hepatitis C testing, mammogram screening, pap screening. And then were they going and using primary care or non-psychiatric medical visits? So that's less a screening and more a utilization of care question. There were a lot of challenges in data gathering. And so just for those of you who may want to do this kind of work, I'm happy to discuss later, but there's quite complex IRB approvals when you're collecting data on vulnerable populations like this. So we had IRB approval from actually three sources, UCSF, the California State Committee on the Protection of Human Subjects, and then through the Department of Healthcare Services, there's actually another independent IRB approval there, and that's a department within the state of California. As I mentioned before, we merged datasets. So staff that was running this intervention called CALMEND in the Department of Healthcare Services combined the community mental health clinic data, they call it CSI, and the Medi-Cal data, and then they gave us de-identified data securely to a UCSF programmer who cleaned and coded the data for analysis. Our sample size was large, it was close to 60,000 people served throughout the state of California. There's limitations to the data that I'm going to describe to you all today. One of the largest is there wasn't pulled a, let's say, frequency match control sample. So there weren't, there's not a comparison group, this is only examining this cohort of people. And actually, unfortunately, getting the patients identified as CALMEND program participants was complicated because most of the program ended up actually focusing on non-Medi-Cal recipients, so we weren't able to examine the impact of the program and more able to look at kind of what's the general state of affairs in terms of screening in the state. So here are some of the results that we found. I'll start with diabetes, which is what I've spent most of my career focusing on. And the long and short is that there's really low diabetes screening rates among people with serious mental illness. Only 30% of people were screened for diabetes in the state of California, despite guidelines being in place over 10 years ago. I imagine most of you are aware of the ADA and APA guidelines that were in place in 2004, and it really continues not to move the needle very much. The strongest correlate of diabetes screening was having at least one primary care visit, so that increased your likelihood of getting screened. But a notable finding that we had was really around young adults. And this is a theme that I'm going to come back to throughout our talk today, is young adults were less likely to be screened than any other category of older adults with serious mental illness. So it's hard to see this, but as you can see, this is the reference group. Here are people who are younger adults. And as you move up, the likelihood of getting screened increased. This was a small amount of people, and we imagine it's complicated here. But if you look just at the 28-year-olds to 67-year-olds, they were more likely to be screened, as opposed to the young adults that were less likely to be screened. As I mentioned, we also looked at diabetes prevalence. We found the prevalence to be very high. It was 32%. We did an adjusted prevalence for all racial ethnic minorities. And that, except for Asians, all the racial ethnic minorities, it was significantly higher than white populations with serious mental illness. And then using sophisticated methods of inverse weighting to reduce selection bias. In doing the sample, I work with a really phenomenal epidemiologist, Eric Biddinghoff. We were able to estimate the prevalence to be around 27% among those who had been screened. Again, it's a biased sample because those are the ones that were screened, and perhaps people were more likely to be screened who docs were worried about. You can read more about this in one of the APA journals in psychiatric services. We also looked at HIV testing. Now, Amy was bringing up in the beginning that I am interested in HIV testing. And this might come as a surprise to folks because I think most people think about screening their patients for diabetes, but don't necessarily think about screening for HIV. But actually, HIV prevalence among people with serious mental illness is 10 times that of the general population. I'll say that again, it's 10 times greater. So that's in the bottom here, you can see 6% versus 0.5%. And these are estimates. And this is because of high risk behaviors among this population, not just with drug use, but with risky sexual behavior among those who are having sex. Now, and so in this setting, we found only 6.7% of patients received HIV testing. Men were less likely to be tested than women. Asian Pacific Islanders were less likely to be tested. Black Americans were more likely. Again, utilization of primary care was the strongest predictor of, and I'm sorry, there's an error of screening, it should be. And importantly, again, as I said, this is a high risk population, but this HIV testing rate wasn't that much higher than the general population in California at the same time period. The story is true around hepatitis C. So here in this picture, here is a young psychiatrist, Dr. Evan Traeger. He was in my lab as a medical student. We examined hepatitis C testing. Hepatitis C testing is also more prevalent among people with serious mental illness, 17% versus only 1% in the general population. But we found that only around 5% of people were screened for hepatitis C, and this testing rate was lower than the hepatitis C testing rate in the U.S. at 12%. This was published in the American Journal of Public Health. I also worked with a fantastic chief resident at the time at UCSF, Dr. Monique James, who's now a psychiatric oncologist at Memorial Sloan-Kettering. She was interested in cervical cancer screening among women with serious mental illness. And what we found is that only 20% of our sample received cervical cancer screening. That screening rate was less than half of that of the general population of women in California during the same period. Again, if they went and used other healthcare systems outside of psychiatry, that was a strong predictor of screening. Again, this is within psychiatric services that you can read more about this. Same story regarding breast cancer. So, in this case, I've been working with two excellent physicians, Dr. Melanie Thomas, who's faculty at UCSF. At the time I was working with her, she had finished her chief year and was in fellowship. She did a project looking at mammography among women with serious mental illness. And she found, again, only 26% of the sample of women with serious mental illness received breast cancer screening. This was according to guidelines, guideline-recommended screening. And the screening was close to half of the general population. Again, those that are able to get themselves to primary care, it improved screening. And then I was invited to do an editorial for the Journal of Clinical Oncology. And I invited a chief resident. This is Dr. Allison Huang. She's the chief resident for research and is actually one of the new national clinical physician scholars that's going to be entering next year. She's a mentee of mine in my lab. And she and I wrote an editorial to a piece in the Journal of Clinical Oncology because there was some evidence that women with serious mental illness experience basically later presentation to care and delayed diagnosis. Basically what they found in the adjacent article that our editorial accompanies is that women with SMI were more likely to have more advanced disease, more lymph node involvement, more undifferentiated tumors, poorly differentiated tumors. And so this all points to they're not getting identified early. And so we cited our prior work together about the importance of early screening. And here again, I had a chance to work with a wonderful junior faculty member, Dr. Maria Garcia, who's an internist at UCSF. And during her early part of her career development award, we worked together and looked at primary care utilization and found that a third of people had no outpatient general medical visits during the study period. And some of the important findings that we had here, again, were disparities in care. Young adults were less likely than older adults to have a visit. Black Americans were less likely to have visits and people in rural settings were less likely to have visits. This is important because of what we were talking about before, right? That, you know, if you were able to make it to a primary care visit, then you were more likely to get appropriate screening. So subsequently, after I did this work in the state of California, I was wondering, you know, is this lack of screening just in the public health sector or does this happen also in integrated health settings? And I had a wonderful opportunity to partner with Kaiser Permanente's Division of Research and with Dr. Julie Schmidt Deal, who's here. And we received funding to look kind of more narrowly at diabetes screening and prevalence and actually treatment of people with serious mental illness. And so this was an NIDDK-funded study. A lot of the work that I described before was through my career development award through NIMH. And so this work with Dr. Schmidt Deal and DOR was looking at all patients served within their integrated care system. They were patients who were taking with serious mental illness, taking antipsychotic medications. This was about 15,000 people. And what was beautiful about working here was that as opposed to in the state of California, when I was looking at Medicaid data, here I actually had lab data, actual lab results. So the issue is that, again, as the systems are separate in the public system, you typically can't actually get for people served in specialty mental health find out the actual lab values. I could get diagnostic codes that were billed in Medicaid, or I could get a bill for a lab test, but I couldn't see the result. And so in Kaiser, what's beautiful about Kaiser is that I can see the result, I can see the A1C. And so that's what I'm gonna be sharing with you all today is more of the nuance of what I could look at with Kaiser. So our take-home here, right? This was a large sample. And you can see that it's better than 30%, but it's not perfect, right? My wish was that, well, this is an ideal setting. Everybody should be able to get screened. Well, only 55% received diabetes screening. But again, here we get to young adults. Young adults were less likely to get screened than those of other ages. Black Americans here were less likely to be screened. Interesting, smokers with serious mental illness were less likely to get screened than non-smokers. And those of you who are clinicians will know that's not good. We'd want to make sure that those at highest risk for cardiovascular disease were evaluated for all risk factors. But the unique thing that we could see in Kaiser is we could also see, did the DAC order the test? And here we see that 74% of providers did order the test, not 100%. So 100% of the providers did not order a test, but 75%. So it should be, there was a gap here where about, let's say about 20% of people had a test ordered, but just didn't get that test. And so I think what we do have an opportunity here to do is to increase our ordering of tests and also to target vulnerable populations who just, even if a test's ordered, have difficulty going and getting those tests done. So this was published in the Journal of General Internal Medicine. And then we were able to examine diabetes prevalence. And this work I've been really excited about. So here you can see the diabetes prevalence among adults with serious mental illness. It was up to 28% for those screened. Again, you can see this is the total sample and then among those who are screened. This is comparisons in Kaiser. It's 8% of the population and the U.S. population, 12% have diabetes. So even if it was as low as 17, this is much, this is higher than the general population and the Kaiser population. The other notable thing here is the increase in diabetes prevalence over years. And so these are the age in years and this is the percent of that population with diabetes. And then we divide by their race, ethnicity. So here are the white population. And you can see that even early on, there are differences based on race, ethnicity. So this blue is the Asian Pacific Islanders. The red is black, the black population and the green is the Hispanic population. So you can notice a racial ethnic differences in the diabetes prevalence. And that was published in Diabetes Care. Also, we were excited to look at the pre-diabetes prevalence and why this is exciting to me is because of our opportunity here. Potentially our opportunity to really do early intervention and prevent disease. So although it's disappointing and discouraging to see, pre-diabetes among adults with serious mental illness was the prevalence was about 47%. In the US population, it's only 34%. And again, you see real racial ethnic differences here. The opportunity is we know that we can treat pre-diabetes and prevent full-blown diabetes. And so this is a prevention opportunity, especially if we start paying attention to these younger adults and younger populations. So this was published in Diabetes Care. I also wanted to let folks know I did just recently, this is not here in here because it was only recently published, but I'd be happy to share this with folks. We publish on actual diabetes care among this population and found that basically within Kaiser's population of all adults with diabetes, looking at people with serious mental illness, the A1C, so that's a marker of good blood glucose control was actually better among the population with serious mental illness. And I imagine this would surprise a lot of people here who are listening to this. But the reason why I think it's better is actually because of the population health approaches that Kaiser uses for diabetes management and really active population health approaches. And so I think when you'll all be repeating this theme later but when my population, population with people with serious mental illness are within systems that leverage population health approaches, I believe they get better care. So there are many implications from the findings that I've mentioned so far that hopefully would influence you as an individual clinician, your behavior, as well as behaviors at your clinic or developing system level policies to improve the care of people with serious mental illness. So I'm gonna go into each of those with you all right now. So for an individual clinician behavior. So one thing that I hope you all get from this talk is add screening for medical problems to your problem list for every patient you have. And please don't just think about metabolic screening but also think about HIV, hepatitis C and other cancer screenings. So this is just something that I think should be on the problem list and that there's a date that you kind of follow up on this annually for yourself. I think really remembering to focus on young adults. Again, this is an opportunity for prevention. I think all of us when treating young adults are really focused so strongly on this individual who's often just been newly burdened with a really serious chronic illness, having challenges with it and we're trying to wrap around a lot of services for this person. Just remember to add medical screening to that list of wraparound services. The final thing I'd be bad. Doctor, my primary care colleagues would be not happy with me if I didn't mention treating nicotine dependence. This is in our wheelhouse. This prevents cardiovascular disease. Talk to your patients about stopping smoking, provide them with nicotine replacement therapy in a study that I'm doing actually with Kaiser now, we're about to publish on this. Some people with serious mental illness are given nicotine replacement therapy, but often by our primary care colleagues, not by psychiatry. And I really think that it's important for psychiatrists or our pharmacy partners or nurse practitioners to be doing some treating for tobacco dependence. And then the final thing is actually learn about initiating treatment for common metabolic abnormalities like diabetes and dyslipidemia and hypertension. This is actually available for free in SMI advisor for CME credits. This is what it is. This is a program that I created with Dr. Kerry Cunningham here at UCSF with the support of the California Healthcare Foundation. This is a really easy to use module, pretty fast and practical. This is for folks who, this is really for folks that you have who aren't connected well to primary care, but you know, still have hypertension or have pre-diabetes or early, you know, or dyslipidemia. And there's some things you can do that are safe and don't interact with your medications that you can start initiating in your clinic or if you're in another resource poor setting. So these are some tools that I hope you all will be able to use that might help you in treating your patients individually. Then I'll focus on clinical level interventions. So these are some things that might work for your clinic. These are some ideas that you should talk to your clinic director about. Some clinics, when I was in New York and I know here in California, the same, some clinics do health screening months so that everybody who kind of walks through the door gets weighed and, or campaigns about smoking cessation that month or awareness around pre-diabetes. Those are some strategies that people have used at clinics. Another strategy is onsite phlebotomy. This is a great strategy for those patients who are too cognitively disorganized to make it to the lab to get their tests. And so having onsite phlebotomy available for other patients like that is really a great solution at the clinic level. Some folks, I'm sure Dr. Dress talked about this. Some settings use care managers that are responsible for kind of coordinating medical care across different clinics. And so hiring an onsite care manager who's responsible for looking at all of the care manager or care managers responsible for paying attention to the medical care of the patients and examining that. And then onsite women's health services is another clinic level intervention that you could consider. And actually I mentioned Dr. James earlier and I'll mention this because it came through, it was promoted through Psychner News in the APA. We implemented a co-located OB-GYN clinic actually on our inpatient unit at Zuckerberg San Francisco General Hospital. That's one of UCSF's safety net hospitals. That's where I work. And basically once a week, an exam room on our unit becomes a mini OB clinic. And we bring the services to the patients there. Dr. James started this several years ago and it's still ongoing every week. And she wrote up our work in psychiatric services. It's been highly effective for our patients and receiving family planning as well as screening. And the patients report high satisfaction levels with this. They've actually replicated this in some areas in the East Bay. And I've presented on this work actually to a lot of gynecology teams who are interested in reaching this high risk population. And then I'll shift to kind of system level implications of this poor screening. Cause this is really where I think this is where we can have maximal impact. So I imagine many of you might work in systems that have addressed this by having a co-located FQHC primary care clinic, a satellite clinic. And these are great cause they're onsite typically in San Francisco, which is the one that I can speak the best to that the problems with it is often they're part-time clinics. So they're, you know, maybe a half day a week. So you can't kind of catch people when the iron's hot who come in, who they see their psychiatrist or their case manager, and they have poorly controlled hypertension. And you wanna be able to take somebody kind of live to go see somebody then. And part-time doesn't really work that well. Often also they're not fully integrated with the rest of the system. So our satellite clinics here in San Francisco, for example, chart in one electronic system as opposed to the electronic system for behavioral health. They also, I mentioned Ben Dress about the medical case managers located in community mental health settings. This has happened a lot in Atlanta, as well as in places in St. Louis and Missouri. These are great. The limitations of these tend to be, there's been a lot of primary focus on metabolic screening. Again, there's obviously this continued problem with lack of integration of the electronic health records, but there's also a lack of focus on women's health or infectious disease. So then I'm gonna bring up some other approaches that are kind of more emerging that people are trying out and that may work for your system of care. So some discussions I've been having here in San Francisco is operationalizing some system level cancer screening by bringing mobile mammograms. So literally bringing a mobile mammogram van to the specialty mental health clinic so that some of the patients there can, literally the services are brought to them. There are some high risk primary care clinics that are more drop-in focused. I think drop-in focusing is a really, and more urgent care focusing is really useful for our population. This is one that's focused on people who are marginally housed and have HIV. It's in Ward 86, which is a famous HIV clinic at ZSFG. And a lot of these patients tend to have comorbid serious mental illness and actually methamphetamine use disorders. And so they come in whenever they'd like, they know they can drop in and they can see a primary care doc and have kind of one-stop shopping. And then I'll discuss a model that I've been building, which is a reverse collaborative care model, which I call Cranium. And this is, you guys might recognize, this is Freud, but with a stethoscope on prescribing metformin. So this is kind of, this is an intervention that basically flips the traditional collaborative care model on its head and uses the main approaches that the AEM Center has had with a population health approach, screening recommendations and standardized treatment recommendations in building out a team, right? Where you would have a primary care consultant, but putting this within specialty mental health settings. So I've worked on this project. There's some publications of this in implementation science and psychiatric services. We used kind of implementation science frameworks to build this model within specialty mental health settings. And it's an inexpensive model comparative to other populations, other interventions, because some of the PTBI or the primary care behavioral health SAMHSA demonstration pilot projects were all quite costly and not sustainable. And so this is an intervention that is promising. I'm submitting kind of more of our findings of some of our outcomes quite soon, but there are major improvements in HIV testing, particularly as well as diabetes testing and high satisfaction by staff. So I'm gonna end there. That concludes kind of the main part of my presentation.

physical health monitoring

diverse populations

serious mental illness

health screening

disparities in care

medical problems screening

metabolic abnormalities treatment

integrated healthcare model