Hello and welcome. I'm Dr. Benjamin Druss, Professor and Rosalind Carter Chair in Mental Health at the Rollins School of Public Health at Emory University and the Health Systems Expert for SMI Advisor. I'm pleased that you are joining us for today's SMI Advisor webinar, Bipolar Disorder and Measurement-Based 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. Today's webinar has been designated for 1.0 AMA PRA Category 1 credit for Physicians, 1 Continuing Education credit for Psychologists, 1 Social Work Continuing Education credit, and 1 Nursing Continuation Professional Development Contact Hour. Credit for participating in today's webinar will be available until July 11th, 2021. Slides from the presentation today are available in the handouts area found in the lower portion of your control panel. Select the link to download the PDF. Please feel free to submit your questions throughout the presentation by typing them into the question area found in the lower portion of your control panel. We'll reserve 10 to 15 minutes at the end of the presentation for Q&A. Now I'd like to introduce you to the faculty for today's webinar, Dr. Joseph Ceramelli. Dr. Ceramelli is an assistant professor in the Department of Psychiatry and Behavioral Sciences at the University of Washington School of Medicine and an attending psychiatrist at the University of Washington Medical Center. Dr. Ceramelli's clinical and research interests include outpatient consultation liaison psychiatry, including telehealth and collaborative care in primary care settings, with an emphasis on individuals diagnosed with bipolar disorder. Dr. Ceramelli, thank you for leading today's webinar. I will turn it over to you. Thank you, Dr. Drost. Hello. As a beginning, I'd like to say I have no financial relationships or conflicts of interest to report for today's presentation. And for today, on the topic of bipolar disorder and measurement-based care, I'd like to accomplish three objectives. First is to describe principles of measurement-based care. Second is to describe lists and maybe somewhat contrast measures of bipolar disorder symptoms that could be used in measurement-based care. And third is to explain factors to consider when choosing a measure for use in clinical care. So to get to the first objective, I want to first describe a potential clinical circumstance that can occur sometimes when measurement-based care is not being used in practice. One of the things that can come up at times is individuals may present for care at different times, sometimes seeing different clinicians. And there's a potential risk that symptom assessment or just assessment of clinical status might be done differently or using different strategies. And if there is the potential of lack of consistent measurement of current symptoms at all clinical encounters. And if that occurs, it can progress on to setting up a circumstance where it might not be as feasible or as easy to consistently compare current symptoms or clinical status to past symptoms or clinical status, which at times can increase risk of clinicians not detecting deterioration or not fully appreciating a lack of improvement, which can then increase the risk of perhaps not having a treatment change or intensification of treatment in the circumstance where there's been a change in clinical status. So, again, this is something that can happen. It's not sort of a guarantee for usual care, but it's a potential risk when there's not consistent measurement. And so what measurement-based care does is a few things. One, it includes systematic administration of a clinical measure. In practice, that's most commonly involves use of symptom measures. So, systematically administering measures. And two, using the results of those measures to inform decision-making for individual patients. Using today's measures, comparing the past measurements, using that as part of decision making. And three, can increase the chances that non-response to treatment is detected. There are other clinical strategies for doing that, of course. Measuring symptoms as part of measurement-based care is an additional way to try to increase the chance that non-response is detected. And four, the other thing to think about, which I'll give an example of later on, is to think about population-level assessment. Getting a quick observation of what proportion of patients in your clinical population report high symptom severity, for example. That's a point that measurement-based care can help with. So, to move through these principles, I want to do three different things. One is just describe a high-level summary of a case that was published as a case report in the journal Bipolar Disorders. Two, describe results from a measurement-based care clinical trial. And then three, describe more of the population approach, as I mentioned, as one of the objectives of measurement-based care. So, for the case, I would say just a couple of high-level points, but mostly get on to the part about treatment and measurement. And again, this is published in a journal. So, briefly, a 37-year-old woman presented for psychiatry consultation in a primary care clinic and had described a months-long course of progressively worsening depressive symptoms, though the depressive symptoms had been chronic. Treatment was changed in primary care prior to the consultation with the psychiatrist. Ultimately, though, the course continued to worsen. At the time of consultation with the psychiatrist, the diagnosis included bipolar 2 disorder and post-traumatic stress disorder. And treatment was initiated in primary care, treatment directly by the psychiatrist and with a colleague in psychology as well. This person was enrolled in a clinical trial, which I can talk about in more detail later. But the trial was a randomized study, and this person was randomized to treatment with direct care by a psychiatrist and a psychologist in primary care. And here's a plot of symptom measure results that were used as part of treatment in primary care. So, the blue line shows depressive symptoms measured with a commonly used measure called the Patient Health Questionnaire 9, or PHQ-9, measuring of depressive symptoms. For this clinical trial, we developed a new measure of manic symptoms that we call the Patient Mania Questionnaire 9. That is a patient reported measure of manic symptoms. And each of the time points where there's either a square or a diamond shows an appointment in primary care with a psychiatrist or a psychologist to do treatment of bipolar depression and of post-traumatic stress disorder with medication treatment and psychotherapy treatment. And what we did in telehealth, we did this through telehealth, which I could talk about later. But in consultation and care was enhanced in this patient's care by use of patient-reported depressive, manic, and PTSD symptom measures, which aren't shown on this plot, but we also measured using the PCL-5. And at the clinical appointments, we discussed results with the patient to encourage communication about symptoms, reviewed graphs like this of reported symptom severity over time. And as part of measurement-based care, we used symptom measure results to inform clinical decision-making. And the other thing is that by obtaining measure results consistently during this episode of treatment over the course of approximately four months, we provided the primary care clinicians and the patients a potential opportunity to compare future symptom status to symptoms that had been reported in the past. For this individual, what might recurrence of a depressive episode look like? How might that be picked up with symptom measures? Having this observation during four months of treatment can help the patient and clinicians potentially detect recurrence in the future. Here's a case example of how that was used. And so what this turned into, in contrast with the original figure that I showed, is that in this trial where we were using measurement-based care, we consistently measured current symptoms. And that permitted or made it easier to make a comparison to past symptoms using the same measures, which helped to detect deterioration or lack of improvement and helped us as clinicians think about when to intensify or change treatment. For this individual patient, the patient had a favorable outcome. It opens up a question of how that might apply to larger populations in clinical settings. One point about measurement-based care that's important to make is that this patient didn't receive measurement-based care as treatment. Measurement-based care helped to facilitate treatments that are already known. There were specific medications that were used for treatment. There was a specific psychotherapy called cognitive processing therapy to treat symptoms of post-traumatic stress disorder. And there were changes in treatment that were made informed by symptoms and also reasoned through with the patient and the clinician. Measurement-based care is not just measuring symptoms. Measuring alone is not sufficient. So it's using measurements, again, to inform treatment decisions. So we just reviewed a case example. And now I'd like to just describe briefly one example of a randomized trial of measurement-based care. And I do want to get to the point soon that, again, measurement-based care can also inform monitoring panels or populations of patients. And it's very interesting because it can help clinicians or clinical leadership answer an important question of what proportion of my patients have improved. If one can define improvement as sort of results on a symptom measure or as part of improvement, that could be an answerable question if symptom measures are consistently used in a practice. Well, again, we'll get to that example soon. Now, a clinical trial, one example trial of a randomized clinical trial, I want to note this is in a population of individuals with depression, so not with bipolar disorder, but it illustrates a couple of points. And so in this trial, individuals with major depression were recruited and then randomized to two active treatments, to either standard depression care or to depression care using measurement-based care. And this trial was published in the American Journal of Psychiatry five or six years ago. And really, I think notable results is that not only did a greater proportion of individuals in the measurement-based care arm achieve either depression response or remission, but people improved faster. It's very interesting. Using consistent symptom measurement, linking those measures to inform treatment decisions, a greater proportion of people had response or remission and people improved faster. And again, it's not a specific treatment of depression. People in both arms were, I mean, there were some constraints in the trial about what medications were available for treatments, for example, but those treatments were available to people in both arms. But using consistent measurements, comparing those results to past measures, using that to inform decision-making led to significant improvements in the sample, or in the population in the measurement-based care arm. There's also an example, so again, that was in depression. There's also an example from bipolar disorder, not quite as easy to look at with just a plot like in the prior slide. But this occurred in the context of the large STEP-BD study, which was a large collection and network of clinical trials and studies in bipolar disorder treatment. And clinicians in this study, as I understand, used a measure called the clinical monitoring form as part of measurement-based care, which included clinician observed measures. And one of the secondary analysis report that came out of that trial looked at a phenomenon called clinical inertia. Clinical inertia is something that measurement-based care tries to address. It's what can occur clinically to many clinicians, continuing ineffective treatments, making a decision of, well, this might be sufficient enough improvement. It's something that can occur at times. It's not a trait of a clinician, it's something that can happen in clinical decision-making to everyone at times. And so one study in STEP-BD looked at clinical inertia and found that when this measure was used in the trial or in the studies, clinical inertia occurred infrequently, less than 7% of the time. It's suggesting that having consistent measurement, being able to make comparisons helps to overcome this clinical inertia phenomenon. And it helps clinicians to continue to intensify treatment or make adjustments to reduce symptom severity. Okay, here's a population example. I've alluded to this a couple of times. And this is getting, again, outside of bipolar disorder. This is looking back to individuals with depression, but there are principles that can apply to this. And this is an analysis that was done on observational data of a large statewide collaborative care program treating individuals with depressive symptoms in federally qualified health centers throughout Washington State. And as part of collaborative care includes measurement-based care. And collaborative care has other aspects to it, but it's one of the fundamental parts of collaborative care. And in this program, depressive symptoms were monitored with a measure called the PHQ-9, Patient Health Questionnaire 9. And in the dark line here, the dark plot shows sort of approximately, it shows how many weeks it would take to get approximately half of individuals receiving treatment to have a clinically significant improvement in depression symptoms. And in the dark line, it shows that in this large program with variability across sites, approximately 64 weeks to see that proportion of individuals experience an improvement, clinically significant improvement. When specific components of collaborative care and of measurement-based care were incentivized, that proportion or the time until that proportion of people experienced improvement was substantially shortened down to approximately 24 weeks. And things that were incentivized or process measures incentivized in this included a number of follow-up contacts, which included when measurements could occur, reviewing results and reviewing measurements with a psychiatric consultant, for example. So, components of measurement-based care, when incentivized as part of collaborative care, shortened the time until half of a clinical sample experienced significant reduction in severity of depressive symptoms. And I've mentioned the PHQ-9 a couple of times. Here's what it looks like. It's a patient-reported measure. It's very likely that most or many participants today have used this clinically. Patients can complete this at the time of an appointment or beforehand during an appointment, even, assessing depressive symptoms. There's one other point related to collaborative care and some measurement-based care that I would want to make about the PHQ-9 and about using measurement-based care as a key aspect of collaborative care. A group recently reviewed observational studies and clinical trials looking at effectiveness of collaborative care on depression outcomes for racial and ethnic minority populations in primary care. And again, collaborative care focuses on assessment and treatment of populations in primary care settings. But a fundamental component of it is measurement-based care, most commonly using the PHQ-9. And so, I think that's a really important point. And in this review, the authors found that high fidelity to collaborative care was discussed as the top priority for improving outcomes. And that includes consistent measurement-based care as part of collaborative care. One example study from this review, again, there were 19 studies included in that review. One example study here was called the BRIDGE study, which compared standard collaborative care to a patient-centered and culturally tailored collaborative care intervention for patients. And in this study, 27 primary care clinicians were included and 132 African-American patients with major depressive disorder from 10 community-based primary care clinics. Now, in this study, both arms used the PHQ-9 as part of measurement-based care as a component of collaborative care. And in both arms, in both study arms, patients showed statistically significant improvements over 12 months. So, again, one example study from the larger review article showing that sort of high fidelity to collaborative care using measurement consistently as a part of that can improve outcomes. Two recent reviews came out on measurement-based care. One from 2017, excuse me, published in the journal Psychiatric Services, identified 51 relevant articles on measurement-based care and found that brief structured symptom ratings have strong psychometric properties and that virtually all randomized controlled trials with frequent and timely feedback of patient-reported symptoms to clinicians significantly improved outcomes. And ineffective strategies included inconsistent symptom assessments and reporting results of symptom measures to clinicians at times that weren't linked to a time that the clinician could do something about it. Another review in the last two years is called Implementing Measurement-Based Care in Behavioral Health. This review highlighted many important points about measurement-based care, including calling out sort of a 10-point research agenda on measurement-based care. One of the points was calling on developing brief and psychometrically strong measures for use in combination, such that individuals with certain symptom domains might have measurement with one measure. If new symptoms emerge or a different type of symptom emerges, another brief measure could be added to that, for example. And we've talked a lot about symptom measures, for example, the PHQ-9 measure, and I wanted to say another point about symptom measures. Symptom measures can include structured instruments that patients use to report perceptions about symptoms. In one study, or in one review of studies, rather, symptom measures were equivalent to clinician-administered rating measures in identifying treatment responders or those who responded and remitted from treatment. It can help with efficiency of symptom assessments, accuracy, and consistency. If an individual is completing the same measure at appointments, it can become the person will sort of learn about it, expect it, see it as part of clinical care. And there are brief sort of symptom measures validated to assess different symptom domains, depressive symptoms, different symptoms of bipolar disorder, anxiety symptoms. So another point about symptom measures, but one important point, as was highlighted in one of the reviews on measurement-based care, is that it's really important to get the results of the symptom measures to the clinician and get them to the clinician at a time that they can be actionable. So the symptom, you know, whatever data comes out of the symptom measure should be perceived by clinicians and by patients to have a direct benefit to patients. Must also assess current symptoms, be interpretable in the setting that it's used in, and readily available during the encounter. There's also important parts of psychometrics that we'll talk just a little bit about later about reliability and sensitivity to change. Now back to bipolar disorder specifically, and remember that one of the key points from the more recent review about measurement-based care was to find a way to develop brief measures that can be used together. I think that can apply to bipolar disorder because of the commonly used PHQ-9 that's often in use in many clinical settings, which assesses depressive symptoms. But from clinical practice, many of us have observed and are aware that individuals with bipolar disorder can experience a high proportion of days with symptoms, even outside of a full mood episode. In fact, in some studies, individuals experienced subsyndromal or not full episode symptoms most days, and that was more often depressive symptoms or subsyndromal depressive and hypomanic symptoms. The other thing is in the context of depressive episodes in bipolar disorder, the majority of people experience one or more concurrent manic symptom even during depression. And the presence of any residual depressive or hypomanic symptoms during treatment or during treatment of an acute mood episode is associated with worse outcome, including sort of shorter time until recurrence of the next mood episode. So if an individual with bipolar disorder is experiencing a depressive episode, there might also, I mean, there's likely to be at least one concurrent manic symptom. And given that any residual symptoms are associated with worse outcome over time, it might justify measuring both symptom domains, especially if there's a brief measure to use for manic symptoms, maybe concurrently with the PHQ-9 measure, for example. So now we can get into measures of bipolar disorder symptoms specifically. I want to review one new option, which is exactly what we used in the clinical trial from the patient example I showed earlier. But I do want to note there are many options, and colleagues and I reviewed the options that existed in the literature, and I can show you that, too, and then points to consider with measure selection. Again, we had reviewed the PHQ-9, and in the context of the clinical trial, we had developed a new measure called the Patient Mania Questionnaire-9, which has a format just like the PHQ-9. And the context of this trial, I'll talk about this just for a minute or so. This was a large clinical trial called the Study to Promote Innovation in Rural Integrated Telepsychiatry, which we called the SPIRIT Study. And in this trial, we compared individuals screening positive for post-traumatic stress disorder and or bipolar disorder. We recruited approximately 1,000 individuals who were enrolled in the trial, and those participants were randomized to treatment with either collaborative care or to direct care by psychiatrists and psychologists through telehealth. And the site for this study, the sites, rather, included 12 federally qualified health centers in three states, and participants received 12 months of treatment. So a bit about the context for where we developed this measure and why we developed it. One of the things we had learned is that we worked with key stakeholders in these 12 federally qualified health centers and with experts in bipolar disorder. And in that sort of preparation for the trial, I developed a new manic symptom measure that could be used concurrently with the PHQ-9. The sites for this trial that the federally qualified health centers were regularly using the PHQ-9, it was important to concurrently use a measure that could go along with the PHQ-9 to support provision of measurement-based care in this trial in both arms of the study. So we developed new items based on DSM-5 manic symptoms, and we modeled the responses and interpretation just off the PHQ-9 to help with making the measure easy to interpret. So here's what it looks like. This is what we developed. It looks very similar to the PHQ-9, has nine items, and, yeah, assesses manic symptoms over the past week and has each symptom scored from zero to three, from not at all to several days, more than half a days, and nearly every day. And I think clinicians will recognize these points or these symptoms, feeling easily irritated, feeling overactive, feeling sped up or restless, and so on. So what I want to do now is move on a little bit to describing psychometric properties of this. But what we did in the trial was just administer this along with the PHQ-9. A person would come into the clinic for an appointment, would fill out both the PMQ-9 here and the PHQ-9, and then clinicians would get the results. And then in the collaborative care arm, for example, the care manager could help to administer these or give the measures to the patients, and the psychiatric consultant could review results in a registry as well. So here's how we evaluated psychometrics of this new measure. So again, it was new. We used it in a trial, and we looked at two different samples from this trial to evaluate psychometrics. So what we call Sample A was a group of 114 participants from the trial who, at the end of the trial, assessed test and retest reliability and concurrent validity of the measure. A test-retest looks at if the measure is administered and then it's administered later, are results similar over not too long of a timeframe, given that symptoms can change. And concurrent validity looks at how does this measure compare to longer-standing measures or measures that have been used and have valid psychometrics. And for this, we compared it to the Internal State Scale and the Altman-Mania Rating Scale. And Sample B, oh, one other point about Sample A. Again, in this trial, we included participants who screened positive for bipolar disorder or PTSD. However, not everyone who screened positive had a clinician diagnosis of either one of the disorders. In fact, for bipolar disorder, it was a little bit under 50% of individuals who screened positive ended up having a clinician diagnosis, psychiatrist diagnosis of bipolar disorder. So what we did for Sample A had individuals with a range of diagnoses, which is important for assessing those specific psychometric properties. However, for Sample B, we wanted to look at internal consistency and sensitivity to change, where it's important to be more confident about accuracy of diagnosis and look at use of the measure in individuals diagnosed with bipolar disorder. So we looked at a sample of 179 individuals diagnosed with bipolar disorder by a psychiatrist, used clinical data from treatment over 12 months in the trial to look at internal consistency and sensitivity to change. And the sample that we looked at here, Sample A in the middle column and Sample B in the right column are some demographic characteristics of participants in this trial, specifically in these subsamples that we looked at for psychometric analyses. And in Sample A, we found that the test-retest had a high correlation coefficient. This was a good finding. And that concurrent validity with the Altman rating scale was significant but low compared to concurrent validity with the internal state scale activation subscale, which is a measure of manic symptoms, where it was a much higher correlation. In Sample B, we found internal consistency showed high reliability. We also did a factor analysis of the PMQ9 and the PHQ9, which showed two separate factors and all nine items loading on the second factor for all of the nine manic items. Here's another way that we looked at change in symptom measure with treatments. I could walk you through this figure here. So the striped bars show baseline assessments and the solid bars show final assessments during clinical treatment using the PHQ9 and the PMQ9. So we called low depression scores under 10 on the PHQ9 and we called low mania scores under 10 on the PMQ9 and then high depression, high mania scores of 10 or above. And a baseline assessment, very few people, 5% were in the low depression, low mania group. But after treatment, that increased up to almost a third of people at 32%. Likewise, in the right column with high depression, high mania, that was approximately three quarters of individuals at baseline, decreasing to 41% at final measurements, showing sensitivity to change along with the PHQ9. So test and retest reliability and current validity were assessed in a smaller sample. That was one limitation. And the frequency of symptom measurement did vary across participants. But the measure demonstrated excellent psychometrics and generally good concurrent validity. And then combined with the PHQ9, we thought this could serve as a good clinical data source for measurement-based care for individuals with bipolar disorder. As I mentioned, there's 28 other measures that we found in a systematic review, 28 other symptom measures that assess manic and depressive symptoms in bipolar disorder. And we reviewed the literature and found those and described the measures, compared them in a systematic review that was published in Psychiatric Services in 2019. And we searched multiple databases. We also developed, to compare the measures, we developed something called a clinical utility score based on sort of measures of clinical utility, whether the measure was brief, whether the measure assessed suicidal thoughts, easy to score, if psychometrics were assessed, whether it was publicly available. And then we organized results based on what symptoms were assessed and on method of assessment. So here's the citation. And we found 10 measures that assessed manic symptoms only, eight measures that assessed depressive symptoms only, and 10 measures that assessed manic and depressive symptoms. And approximately half were patient-reported measures and approximately half were clinician-observed measures. And one of the things, because of some measures being patient-reported and some being clinician-observed, there were six total categories of measures. Manic symptom measures, both patient and clinician-observed, depressive symptom measures, patient and clinician-observed, and then measures that assessed both, that were patient and clinician-observed. And we ordered the measures based on what we came up with on a clinical utility score and found different options that could be helpful, informative, acceptable in some clinical settings. And in general from this, we found a mix of patient-reported and clinician-observed measures and that measures that were developed more recently tended to assess manic and depressive symptoms in outpatient settings, which contrasted with measures that were developed, older measures that tended to assess manic symptoms in inpatient settings or hospitalized individuals. And there were also several computer-adapted versions that were out. But given the number of measures, I mean, in the clinical trial that I described, we used a new measure. There are 28 other measures that we found in the review. And what factors might a group or might an individual consider when choosing a measure for use in clinical care? One point is that this may vary across settings, meaning some clinical settings might prioritize certain aspects of a measure, might prioritize certain ways to interpret results. And this may vary across primary care clinic, community mental health center. This may vary even within type of clinic. It would vary compared to a hospital setting, for example. So I think when looking through the different measure options, the initial decision to make or one way to approach this with the initial decision is, would a clinician or a group like to use a patient-reported measure or clinician-observed measures? I think this is probably the first decision, and there are strengths and limitations of both for patient-reported and clinician-observed. Examples of those include patient-reported individuals could complete the measure before appointments. Clinicians could even see results at the start of an appointment. For example, it can be informative to some individuals to read about symptoms and consider symptom severity in recent weeks and how that might apply to past weeks or months. Some clinicians may worry about objectivity at times, and that's where a clinician-observed measure may have additional strengths. Though I think for some of the clinician-observed measures, it does take practice in becoming familiar with administering the measures and having this internal reliability in how the measures are administered and interpreted. There's a potential risk, though. I think this is easy to overcome. There's a potential risk that results of clinician-observed measures may not be shared with the patient. Again, it would be just as feasible to, I think, look at a plot of symptoms or share results, talk about results with the patient. It just may require being intentional about it since the patient-reported measures would be completed by the measure. The other point or another point to consider is two measures or one measure. I think this is probably a second decision to make. Would it be preferable to use a measure that assesses manic and depressive symptoms in one measure, or would it be preferable to use a depressive symptom measure and a manic symptom measure? In the trial that I mentioned, we were treating individuals with bipolar disorder and without bipolar disorder, and the PHQ-9 measure was already widely in use in the clinics that we were working in, so we decided to use two measures so that the PHQ-9 could be used more broadly within the study, and so the clinics would continue doing the practice that they were already doing, and then we would add on the PMQ-9 when appropriate. But there may be some settings where one measure assessing both symptom domains would be preferred or appropriate. So how might a clinician or practice choose which measure to use? Consider the clinical setting. Consider is this a hospital setting, is it a primary care setting? Who might interpret the results? How often might the measure be administered? Consider current use of measures in practice, just like we did in the trial. What's happening already? What measures are being used? What symptoms are being assessed? And would the next step be to add on a measure, or would the next step be to pilot out use of a new measure, replacing whatever is currently in use? The other thing to consider is what is the estimated or known prevalence of bipolar disorder in the clinical setting? In clinical settings where there's a higher prevalence or greater proportion of people with bipolar disorder diagnosis, that might be a setting where a more detailed or a more nuanced measure might be appropriate. Maybe that's a setting where clinicians might find it more feasible to interpret more detailed measure results and make comparisons. And it might be a setting where a high proportion of individuals with bipolar disorder come into the clinic or have appointments. And so clinic staff and clinicians would be in the routine of administering the same measure to a high proportion of individuals in the clinic. So there may also be settings where there's high bipolar disorder prevalence and people continue to prefer and use what's already in use or what's commonly used in other settings to help to facilitate comparison, even across clinical settings. And I talked about this a little bit. Clinician expertise or a generalist with bipolar disorder might also influence what measures are preferred based on interpreting maybe some that have additional subtleties in symptom measurement. There's other potential factors to consider. Timing and duration of treatment. Is the treatment, is it actually more of like a one-time consultation and giving advice and recommendations? Is it more of a couple of days of treatment in a hospital setting? Is it longer-term treatment, like weeks to months in an outpatient setting? All of those points can influence which measures might be preferred. And patient preference. Do individuals in one setting have a preference for this measure? Is it seen as acceptable? Would people be willing to complete it? Do people see it as relaying or helpful information to clinicians? Other factors to consider when choosing a measure. So I think there's even practical matters to consider in practice. Who makes the decision on a measure? Would it be sort of the clinic at large? And if so, who is it? Is it a director of the clinic? Or is it an individual clinician? And there's trade-offs with that, especially if patients see multiple clinicians in a clinic. I think in that circumstance, if there's a high proportion of individuals seeing more than one clinician in a clinical setting, it would make sense to try to find a consistently used measure across the clinic to help to facilitate comparison of clinical status to past status, even when a person's seeing different clinicians. And we talked a little bit about this, where patients may choose the measure. We've reviewed that previously. When is the measure administered? Is it administered the day before an appointment through a secure messaging system? Is it administered at the time of appointment? Is it administered during the appointment? How are results consolidated? How do results get back to clinicians? And how do results help to inform treatment decisions? There's another point to make, as I'm getting towards the end here, about functioning or recovery measures. I've spoken exclusively about symptom measures in all of the preceding presentation, but this is another consideration. Some individuals express a preference for functioning measures or quality of life measures, recovery measures. This can be complicated at times, since many clinical matters and non-clinical matters contribute to functioning or to quality of life. There's some express a concern about functioning or recovery being slower to change compared to symptoms over time, which might make it less immediately helpful in informing a treatment decision, though that may not always be the case, but that's a potential consideration. In fact, to help to evaluate this point, colleagues and I are currently conducting a study on clinician preference for symptom or functioning measures in the clinical care of individuals with bipolar disorder, and we hope to move on to the next stage of assessing patient preference as well as we wrap up the study on clinician preference. In conclusion, I'd like to say measurement-based care involves consistent measurement and assessment and uses those results to inform clinical decision-making, and many options for measures exist, including patient-reported and clinician-observed measures, along with the new option of the PMQ-9 to combine with the PHQ-9, and points to consider include clinical setting, prevalence of bipolar disorder, current clinical use of measures, among other points, all of which can influence measure selection. And here's the bibliography that's available. It's also on the individual slides, and thank you. Thanks so much, Dr. Saramelli. That was really interesting and really useful presentation, so thank you so much. So for attendees, please feel free to submit your questions in the lower left of your control panel. We're going to have a little less than about 10 minutes to field the questions, and there are a few that were already submitted during the presentation. Before we shift into Q&A, though, I want to take a moment and let you know that SMI Advisor is accessible from your mobile device. Use the SMI Advisor app to access resources, education, and upcoming events, complete mental health rating scales, including some of the ones that we talked about, we heard about in today's presentation, and you can even submit questions directly to our team of SMI experts. You can download the app now at smiadvisor.org forward slash app. So now let's get into some of the questions. So there were a couple of questions, Dr. Saramelli, about there was a lot of interest in the PMQ-9 and questions about how folks might get access to that. Is that something that's currently publicly available? Oh, thanks for asking about that. Yeah, this is described, the PMQ-9 should be out soon, and maybe it's not going to be until the end of the year. A week or two. It was accepted for publication and in the Journal of General Internal Medicine and is on the bibliography as in press, but it's just not out quite yet, but it'll be out in an article. The measure is included in the article as a table, so it would be easy to identify or use. It'll be publicly available. That's great. I'm sure we'll be keeping our eyes out for that and looking forward to seeing it. So I just had a question. I really liked what you were talking about at the end about the potential for functioning, measures of function in measurement-based care, and it's great that you're beginning to look at preferences. I mean, do you see that as kind of a direction for the field? One thing that would seem to be an advantage of functioning measures is that they're transdiagnostic, which gets away from some of the challenges in trying to do kind of one diagnosis or symptom cluster at a time, but I'm just curious about where you see those eventually fitting into the world of measurement-based care. It's interesting. I am just thinking about this now. One thought that comes to mind is maybe using both. I mean, if there are potentially different objectives, if one's looking at maybe more of longer-term outcomes and one might be helpful for more acute episodes or monitoring a time of intensifying treatment in response to a presenting problem, that's potentially one idea. I hadn't considered that for a preference study before. It was more as opposed of what might be preferable to use in treatments, but it's something that comes to mind is maybe considering using both. I can say we included in our study eight different measures, four symptom measure combinations and four measures of functioning, and at least we surveyed a wide group of clinicians, psychologists, social workers, psychiatrists, primary care clinicians, so I'm curious to see what types of results we find. We also included a comment section to see what types of comments people would write in about the measures, but that's a next step to move on to in analysis. Great. Well, again, that's another thing for us all to keep an eye out for, because I think it's, you know, I wouldn't be surprised if you find, particularly among patients, an interest in looking at those kinds of domains over time. To that point a little bit, when you're looking at people with other diagnoses, so one question that was posted is about schizoaffective disorder. Do you have thoughts about how to use measurement-based care in those kinds of conditions where there's both an affective component and a psychosis-slash-cognitive element? That's interesting. Yeah, in the study I mentioned, there were, in the clinical trial that I talked about where we developed the PMQ-9, there were some individuals diagnosed with schizoaffective disorder due to the study entry criteria of screen positive for bipolar disorder or PTSD, but there were some individuals that were included. In that study, we continued to use the depressive and manic symptom measures. We didn't have a measure of psychotic symptom severity or cognitive functioning. That's interesting to consider. I think it gets at that point from the more recent review on measurement-based care of having brief measures that could be combined when appropriate. So it might be considering if there's a brief symptom severity measure for psychotic symptoms, maybe including it temporarily or in the long-term to make comparisons. And it may not have to be three separate measures. Maybe it could be combined into one page. So it just kind of reads as one measure with three separate subscores, for example. But I'm just thinking out loud about that. Great. No, that's helpful. There's a question about the article for the PMQ-9. I think that one, it's not, I think what we're hearing is that keep an eye out for it. And in about a week, if you look, and are you the first author on that paper, Joe? Dr. Saramelli? Great. So if you look it up, you should be able to get ahold of it. And I would gather at that point, you might be able to contact Dr. Saramelli for a reprint if you're not able to get that through your library. Yes, that would be fine with me. And it's included, I believe I put it on the bibliography as well as in press. Yeah. That's great. I think we have time for just one more question, again, about the PMQ-9. And the participant made the observation that the PMQ-9 just asks clients to consider symptoms over the past week, as opposed to two weeks. Was there a reason that you chose that timeframe? Yes, that's a good point. We were using, in the trial, we looked for a consistent timeframe across all measures, and we were using a measure of PTSD symptom severity that had assessed over a prior week. And the PHQ-9 in some of the sites was used as usual with two weeks, but in some sites, people were using over past week as a way of monitoring treatment rather than using it as a screening measure to pick up new depressive symptoms. So those were some of the reasons. The other thing is for some of the psychotherapies that were being delivered in the trial, the goal was to have weekly appointments. So we wanted to try to capture interval changes over the prior week. Right. Yeah, that makes sense. Thank you. 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Dr. Joseph Ceremelli

measurement-based care

bipolar disorder

clinical measures

treatment decisions

Patient Mania Questionnaire-9

manic symptoms

quality of life measures

schizoaffective disorder

treatment outcomes