**Transcript of Cyberseminar**

**VIReC Clinical Informatics Series**

**A Patient-Centered Approach to Improve Screening for the Metabolic Side Effects of Second-Generation Antipsychotic Medication**

**Presenter: Julie Kreyenbuhl, Pharm.D., Ph.D.**

**October 16, 2012**

**A Patient-Centered Approach to Improve Screening for the Metabolic Side Effects of Second-Generation Antipsychotic Medication**

**October 16, 2012**

Margaret:Welcome. This session is part of the VA Information Resource Center’s Ongoing Clinical Informatics Cyberseminar Series. The series’ aims are to provide information about research and quality improvement applications in clinical informatics, and also information about approaches for evaluating clinical informatics applications. Thank you to CIDER for providing technical and promotional support for this series. Questions will be monitored during the talk in the Q&A portion of GoToWebinar and VIREC will present them to the speaker at the end of this session. A brief evaluation questionnaire will appear when you close GotToWebinar. We would appreciate it if you would take a few moments to complete it. Please let us know if there is a specific topic area or suggested speaker that you would like us to consider for future sessions.

At this time, I would like to introduce our speaker for today, Julie Kreyenbuhl, Pharm.D., Ph.D. Dr. Kreyenbuhl is a Research Investigator and Assistant Director of the Research Core for the VA VISN 5 Mental Illness Research, Education and Clinical Center (MIRECC) and an Associate Professor of Psychiatry in the Division of Services Research, Department of Psychiatry, University of Maryland School of Medicine. Without further ado, may I present Dr. Kreyenbuhl.

Dr. Julie Kreyenbuhl:Well, thank you, Margaret. Good afternoon, everyone. I am delighted to be here today to talk about a computer-based intervention that I have developed to educate Veterans about “Screenings for the Metabolic Side Effects of Second-Generation Antipsychotic Medications,” and I will sometimes refer to them as SGAs throughout this presentation. So for the next 45 minutes or so I plan to first provide some background on this topic, to then talk about the development of the intervention, to describe a randomized controlled trial that I have been working on to test the effectiveness of the intervention, and to present some of the preliminary results of the study.

Before I get started, though, I would like to ask a couple of questions so that I could have a better idea of who is in the audience today and how familiar you are with the topic of the presentation. So for everyone who is viewing the presentation on your computer via GoToMeeting, can you please indicate what best describes your position at the VA. Are you primarily a researcher? A clinician? An administrator or a policymaker, or do you hold another position at VA? And I will give you a few seconds to respond.

Moderator: Responses are coming in. I will give it a few more seconds and then I will close it out and show the results on the screen.

Dr. Julie Kreyenbuhl:Okay. And so, thank you, everyone, for responding. What I see here is about 30 percent of you are researchers. Close to 50 percent are clinicians; that is exciting. Eleven percent are administrators or policymakers and 11 percent have identified themselves as holding another position in the VA. So thank you for that.

I would like to ask a second question, and that is how familiar are you with the recommended screenings for the metabolic side effects of second-generation antipsychotic medications? Do you consider yourself very familiar, moderately familiar, somewhat familiar, a little bit familiar, or not familiar at all with the recommended screenings? And again, I will give you a few seconds to respond.

Moderator:And there are your results.

Dr. Julie Kreyenbuhl:Okay. I am not seeing them for some reason.

Margaret:What do you have up on your screen right now?

Dr. Julie Kreyenbuhl:Just my flags and the little control panel on the side. But I see it now because I just clicked the arrow. Sorry about that! [Laughter] 

So the results are that about 12 percent of people rated themselves as very familiar with the recommended screenings for the metabolic side effects of second-generation antipsychotics. Close to 50 percent consider themselves moderately familiar, 12 percent are somewhat familiar, 24 percent are a little bit familiar, and six percent are not familiar at all. So that is good. I am going to be going over these recommendations. And I thank you for responding. And I am just getting back to my screen. Yeah, so great.

So a lot of problem of serious mental illness like schizophrenia and bipolar disorder are relatively low. These conditions exact a very high toll on patients and their families in terms of disability, reduced quality of life and stigma.

Less well know, although awareness is certainly growing, is that serious mental illnesses are also life-shortening conditions, unfortunately. A relatively large body of evidence shows that individuals with serious mental illnesses experience much higher rates of morbidity and premature mortality than the general population, with some recent work indicating that these individuals are dying on average in their mid-50s, or about 25 years younger than their non-mentally ill counterparts.

Although suicide and injury do account for some of this premature mortality, about 60 percent of premature deaths in this population are due to natural causes, primarily cardiovascular disease and Type 2 diabetes. And so why is this happening?

We know from research as well as from clinical observation that the prevalence of several risk factors for cardiovascular disease is elevated in those with serious mental illness. For example, Type 2 diabetes occurs in up to one-fourth of individuals with serious mental illness compared to about seven percent of the general population; and upwards of 70 percent of those with serious mental illness smoke cigarettes compared to about 25 percent of the general population.

So while many individuals with serious mental illness do confess one or more lifestyle-related cardiac risks, there has also been increasing evidence that some of the treatments that we prescribe may also be contributing to their poor health outcomes.

Specifically, there are several classes of medications actually that we prescribe to treat mental illness including antidepressants and even mood stabilizers like lithium and valproate that can cause weight gain and other metabolic side effects. But it is the second-generation antipsychotic medications that have probably generated the most attention in terms of their ability to induce sometimes-significant weight gain and increases in blood sugar and cholesterol, which can obviously contribute to obesity, Type 2 diabetes and cardiovascular disease in these patients.

The propensity to induce these side effects, however, actually differs across agents with clozapine and olanzapine for lack of a better term being the worst offenders. Quetiapine and risperidone and respiridone’s act as metabolite paliperidone have an intermediate risk. And the newer agents, ziprasidone and aripiprazole—although they are not so new anymore, but they are newish—being considered metabolically neutral.

Based on available data, there are three newer agents that have been introduced in the past few years. They include iloperidone, asenapine and lurasidone, and they are also thought to be neutral from a weight gain and a metabolic standpoint.

So the growing concern about these kinds of side effects and their potential effects on physical health of patients who are prescribed these agents led the FDA in 2004 to mandate that a class warning about the increased risk for severe hyperglycemia and diabetes be included in the labeling of all second-generation antipsychotics regardless of their individual risks. The warning also required that a recommendation for regular monitoring for symptoms of hyperglycemia and in at-risk patients a recommendation for periodic testing be included in the labeling as well. And manufacturers at that time were also required to send out Dear Doctor letters about this warning, and the warning itself is listed on the slide.

That same year, in 2004, a joint panel of four professional organizations including the American  Diabetes Association, the American Psychiatric Association, the American Association of Clinical Endocrinologists and the North American Association for the Study of Obesity all got together and issued a consensus statement around screening for the metabolic side effects of SGAs. There was also that same year a separate consensus conference consisting of a group of schizophrenia researchers and clinicians, and they released a second, similar set of recommendations; and I refer to those as the Mount Sinai Recommendations on this slide.

I am not going to read through all of the recommendations in detail, but briefly it is recommended that screening of weight, blood pressure, blood sugar and lipids take place at the time a second-generation antipsychotic medication is initiated or changed, 12 weeks later and periodically thereafter, again as shown on this slide.

So one might ask about the extent to which individuals who are prescribed these agents are actually receiving the recommended screenings for metabolic side effects and whether publication of the warning and the guidelines had any impact on rates of screening. So on this slide I show some data from a recently published meta-analysis of 39 studies that involved over 200,000 patients in five countries including the U.S. Many of the studies were done in the U.S. All 39 studies examined rates of screen prior to the publication of the guidelines. Nine of the studies looked after the guidelines were published, and seven of the studies examined rates of screening in comparable samples both before and after the guidelines were published.

And so as you can see in the table, prior to when the guidelines were published, rates of screening were relatively low and only above 50 percent for blood pressure. Following the release of the guidelines, monitoring for weight did improve from a baseline rate of 48 percent up to about 76 percent of patients, and monitoring for glucose also improved from a rate of 44 percent to 56 percent of patients after the guidelines were released.

Rates of monitoring for lipids also improved. They were very low at baseline—22 percent of patients prescribed SGAs were getting their lipids monitored according to guidelines. And even after the guidelines were released, monitoring for lipids was only occurring in approximately 37 percent of patients receiving these agents.

So the general consensus has been that despite the growing awareness about the metabolic side effects of second-generation antipsychotics, rates of monitoring for them are still inadequate, especially for blood glucose and lipids. 

Even in the VA, where rates of monitoring are generally higher than in other settings, in part probably due to the integrated healthcare system that is available and people can get their blood monitored in the facility because of the electronic medical record—all of the reasons—rates of screening are higher in the VA; and the VA is interested in the topic and local facilities have enacted some programs mainly targeted at clinicians in an attempt to raise awareness about the need for screening and to actually increase the rates of screening.

However, since rates of monitoring have remained low despite programs being put in place in the VA targeted at clinicians, we decided to take a different approach by instead focusing on the patient as a possible change agent. So the conceptual framework that we used for our intervention is patient-centered care. In our example, we think that activating individuals with serious mental illnesses to become more aware of the need for metabolic screening and to advocate for themselves to get screened by talking with their prescribers will increase rates of screening.

These key dimensions of patient-centered care have been linked to a number of positive health outcomes which I have listed on the slide, and they include improved adherence to treatment, greater disease self-management, improved health status, and greater patient satisfaction.

Those are the studies that have looked at this framework or used this framework work for intervention have been done in medical settings with regard to medical conditions. This framework has not been investigated so much in people with psychiatric conditions and particularly in people with serious mental illnesses. And in using this framework which is consistent with the recovery paradigm in mental health, we are, I believe, challenging the notion held by some, hopefully not many, that individuals with serious mental illnesses are not interested in or are not able to participate in the self-management of their own chronic conditions, both medical and psychiatric.

In conceptualizing this project, we also considered the fact that the VA is a leader in health IP innovation beginning with being the first large healthcare system to have a computerized medical record all the way back in 1997 and more recently moving into more patient-centered technology applications like the *MyHealtheVet* website and some of the noble applications that a number of people are developing for Veterans including the *PTSD Coach App.*

However, a major consideration in the development of the intervention that I will describe in a few minutes has been that standard website design approaches are not particularly effective for people with cognitive impairments, which includes a significant proportion of individuals with serious mental illnesses. These individuals exhibit impairments in many domains of cognitive functioning, all of which are listed on this slide. But deficits in three domains in particular can make use of computers and websites and other types of technology particularly challenging for them.

For example, problems sustaining attention including focusing attention on a task and ignoring distractions can interfere with one piece of technology. 

Also, deficits in working memory, which involves the ability to retain and recall information, can make a number of tasks difficult, like following step-by-step sequences on a website, making category assignments, and interpreting abstract concepts.

Also, deficits in higher-level, executive-type functions can impact one’s ability to conduct searches and to problem solve, sequence task, all of which are important to website navigation.

And so one of my co-investigators, Armando Rotondi, from the VISN 4 MIRECC, has done some research in this area and has found that some of the following modifications, which are listed on this slide, can improve the ability of web-based applications for people with cognitive impairment including people with serious mental illnesses.

His recommendations include using shallow hierarchies, which means keeping people essentially on the same part of a website, not allowing or requiring people to go deep into a website and have the possibility of getting lost in the website and not being able to navigate back to a main page, using memory aids to support navigation, minimizing the need to think abstractly during navigation, avoiding decorative features that can be distracting, and using very brief but explicit labels in the text in a web program. This reduces the chance of users assigning erroneous meanings to more complex descriptors.

So before I describe the intervention, I first want to talk a little bit about the study and I will be doing that throughout the presentation. But the primary aims of the study are listed here, and they involve comparing the effects of exposure to a patient-centered, computerized tool versus an educational leaflet, which we also refer to as enhanced treatment as usual on a number of outcomes listed here which include: we aim to increase rates of screen by providers for the metabolic side effects of SGAs. We want to enhance recognition by providers of metabolic abnormalities associated with SGAs. We want to increase Veterans’ self-efficacy in communicating with their prescribers and we want to affect their preferences for participating in decision-making around screening. And we are also evaluating whether the computerized intervention has any differential impact on patterns of patient-provider communication around screening for metabolic side effects. That is, we want to know if patients are activated to talk with their prescribers about getting screened or the results of screening.

To accomplish these aims, I am conducting a randomized controlled trial in which half of the participants have been randomized to the computer condition and half to the comparison condition.

The study is being conducted at two VA outpatient mental health clinics, one in more urban, downtown Baltimore and one in a more rural area north of Baltimore at the Perry Point VA.

To be included in this study, Veterans have to meet each of the inclusion criteria listed on this slide including have any one of the psychiatric diagnoses listed here. And as you may see or as you are probably aware, the FDA-approved indications for SGAs have been expanding over the last  several years to include disorders such as treating refractory major depression, and there is a fair amount of off-label prescribing of these agents. And so rather than only including Veterans of schizophrenia and bipolar disorder, we expanded our inclusion criteria to include Veterans with a variety of psychiatric diagnoses because the metabolic side effects of SGAs can occur regardless of diagnosis and even at low doses.

You may notice that one criterion listed here is that the prescriber of the SGA had to agree, along with the Veteran, to have one research visit audiotaped in order for us to evaluate the effect of the intervention on patterns of patient-prescriber communication. This requires that I obtain informed consent from the Veterans as well as their prescribers.

So now I am going to talk a little about the intervention. The intervention itself is a web-based application that is presented to the Veterans on a touch-screen tablet computer. It is presented to them immediately prior to a visit with a psychiatrist or the nurse practitioner who is prescribing their second-generation antipsychotic medication.

The program consists of six pretty brief modules on each of the metabolic side effects of SGAs that are listed on this slide. Rather than going through the entire program, I am going to instead point out what I consider to be the key elements of the intervention using the blood sugar module as an example.

But before I do that, I want to mention some of the design features we incorporated to reduce cognitive burden and to enhance usability in the population we are targeting and this is using some of the recommendations that Dr. Rotondi made.

First, the program is audio assisted. People get to listen to my voice. So all of the text on the screen is read aloud to the Veteran. With the exception of this slide in particular, you will notice that each slide is very simple in format. It has minimal text. It has no particularly distracting graphics on it.

Because of the touch screen, participants do not have to be familiar with using a computer or a mouse to navigate through the program. The only requirements in terms of navigation of the program are, as you can see on this slide, to go forward using the Next button, or to go backward using the Previous button, or to Repeat the audio. And the audio also prompts the Veteran to advance to the next slide in case they forget that they need to do that.

So one key feature of the intervention that is consistent with the principles of patient-centered care is that it seeks to activate the Veteran to become knowledgeable about the metabolic side effects of antipsychotics and to become knowledgeable about the recommended frequency of screening, so that they can advocate for themselves to get screened if need be.

So as found on this slide, each module begins with a brief explanation of the particular side effects and their possible health consequences.

We also provide brief explanations of the screening tests themselves. For blood sugar in particular we explain the difference between a fasting blood sugar and hemoglobin A1c test. 

Each model also contains supplemental slides that the Veteran may choose to view if they are interested in having more in-depth information about the screening, such as the goal values for a test, as shown on this slide. When applicable, the goal values displayed are customized according to whether the Veteran has Type 2 diabetes or not. And because of the high rates of Type 2 diabetes in this sample, we test – well, we had a number of people who had Type 2 people who participated.

The supplemental educational slides also display for the Veteran the recommended frequency of screening for each metabolic parameter, as shown, for blood sugars supposed to be checked at least once a year.

A second key feature of the intervention is that it provides the Veteran with personalized feedback on the extent to which their care adheres to metabolic monitoring recommendations. Before each research visit, we obtain the Veteran’s screening history from their medical record and we input it into the program. And so this slide shows the message provided if the participant has not had their blood sugar checked in the past year, which is again – I just mentioned the recommended interval for this type of monitoring.

For those individuals who have received metabolic monitoring at the recommended interval, the program displays the results of their last test along with a brief interpretation. This slide shows the message that is displayed if the most recent test indicated that the Veteran’s blood sugar was high the last time it was checked. You may notice that the program does not provide the Veteran with a diagnosis per se, only that the test was, in this case, too high.

Those participants who have been screened at the recommended interval and whose test results are within normal limits, received the encouraging message shown on this slide.

The third key feature of the intervention that is consistent with the principles of patient-centered care is that it encourages the Veteran to begin a dialog with their prescriber about getting screened or to talk about the results of their screening if they have already been screened. All participants receive this kind of message regardless of whether they have been screened or whether the results of their screening are within normal limits are not. So everybody gets this message about talking with their prescriber about their screening, which again is a major element of patient-centered care.

To further activate Veterans to begin that dialog about metabolic screening with their prescriber, at the end of the program, they are given the option of printing out a summary of their screening status and all of the test results that were reviewed with them in the program. Two copies of the report are provided so they can distribute one to their prescriber as a way to facilitate a conversation with them and they have one copy for themselves.

And this is an example of what one of the printed reports looks like. This printout again reiterates a number of the key features of the intervention including educating the patient about recommended screening intervals. It provides them with personalized information on their own screening results and status. And again it encourages them to speak with their prescriber either about getting screened or to talk about the results of the screening.

So in the study everyone continued to receive their mental health and medical care as usual at the VA. Individuals who were randomized to the comparison condition received the printed educational brochure shown on the screen. Like the computer program, this brochure provides a brief explanation of each of the metabolic side effects and their health consequences and the recommended frequency of screening for each of them. Unlike the computer program, however, it does not provide the Veteran with any personalized information from their medical record on their screening status and it also does not encourage them to speak with their prescriber about metabolic screening.

So in this study, getting back to the study again, participants viewed the computer program or the brochure immediately prior to an outpatient mental health visit with the psychiatrist or the nurse practitioner who is prescribing their antipsychotic medications. So all research visits coincided with regularly scheduled visits with the prescriber and took place in a private room beforehand.

Participants viewed the computer program or the brochure up to three times over the one-year study period, but they did this no more frequently than every four months. We did not want to overburden the participants with this program at every visit if they were coming in more frequently than every four months. And again, they saw the computer program or the brochure at times that corresponded with regularly scheduled visits with their prescribers.

As I mentioned, I – one of the aims of the study is to know whether the computer intervention activates patients to discuss metabolic screenings with their prescriber. And because of that, I had to obtain informed consent from those prescribers and Veterans to audiotape one visit after the Veteran had viewed the computer program or the brochure. So I was very fortunate that all 15 prescribers in Baltimore and all six at the Perry Point VA agreed to participate in this study, and I am very grateful for their willingness to help me out.

In terms of Veteran recruitment, between March of 2010 and October of 2011, we were able to achieve our recruitment goal of enrolling 240 Veterans in the study with approximately half randomized to each of the two divisions as you can see on this diagram. As I have noted several times, research visits where participants used the computer program or the brochure took place before regularly scheduled visits with prescribers.

We hoped that most participants would have the opportunity to complete three visits over the one-year study period, but knew that some would not be able to do this either because they did not have that many visits scheduled or because they were not able to attend scheduled visits that occurred over the one-year period. But in this diagram, you can see what happened. You can see that a majority of Veterans completed at least one research visit; that is, they had at least one visit with their prescriber over the one-year period. About 80 percent had two and about 50 percent had three exposures to the computer program or the pamphlet.

We are not quite finished, but we are almost finished with 12-month followup interviews and to date we have completed about 75 percent of them, so we are not finished yet.

And the primary reason you will see on this slide is that about ten percent of Veterans were withdrawn from the study, the primary reason that they discontinued treatment with their antipsychotic medication during the study and so they did not meet inclusion criteria and the information we were providing would not have been relevant to them.

So because we are not finished with the study and have yet to analyze all of the data, today I am only going to be presenting some selected findings from the baseline interviews and some basic analyses of patient-prescriber communication patterns from the audio recordings. As such, I need to say that none of these findings has been peer reviewed and they can really only be considered preliminary and should not be distributed widely.

So in terms of a description of the sample, the mean age was 53. The majority are male, which would be consistent with VA demographics. Over half are non-white and most are living in an unsupervised housing situation. As opposed to other SMI samples, well over half of this sample has ever been married and completed more than 12 years of education, which would be consistent with being in the military. But similar to other seriously mentally ill samples, only 20 percent are working for pay and around half are receiving a military service-connected benefit or other disability benefit.

In terms of primary psychiatric diagnosis, the majority, 65 percent, either have a psychotic disorder like schizophrenia or a bipolar disorder. About 25 percent have major depression and 12 percent have only PTSD. And what I mean by “only PTSD” is that individuals with psychotic disorders, bipolar disorder, and major depression may also have PTSD.

We are using the Basis 24, the Behavior & Simpson Identification Scale, as a measure of self-reportive psychiatric symptoms. Each of the items are measured on a five-point scale. Higher scores represent greater symptom frequency or severity. And consistent with the diagnostic heterogeneity and clinical stability of those enrolled in the study, mean scores on the subscales measuring psychosis and emotional ability are actually pretty low to moderate with some variability.

So in terms of which second-generation antipsychotic the participants were prescribed at baseline, quetiapine, risperidone, and aripiprazole were the most commonly used agents. A not insignificant proportion of participants in this study were also being prescribed more than one second-generation antipsychotic concurrently; and not represented here are some of the individuals who were prescribed second-generation antipsychotics who were also being prescribed a first-generation antipsychotic concurrently.

So in the next set of questions we examined Veterans’ self-efficacy in communicating with their prescriber and their preferences for participating in decision-making around getting screened for the metabolic side effects of SGAs. These are consistent with my aims. These are constructs that we hope we are able to affect through the intervention.

And so in terms of their preferences for obtaining metabolic screening, at baseline the majority of participants reported being somewhat or completely interested in being screened.

Similarly, the vast majority of participants also reported being somewhat to completely interested in finding out the results of metabolic screening.

And most participants reported being somewhat or completely interested in talking with their prescribers about the results of metabolic screening.

Along those same lines, most participants rated themselves as having a high level of confidence in their ability to ask their prescribers about getting screened for metabolic side effects. So that was all encouraging.

However, even though most felt relatively at ease asking their providers about getting screened, when asked whether they preferred to leave the decision about getting screened up to their prescriber, close to 40 percent agreed with this statement.

So as I mentioned earlier, we had some concerns that the cognitive impairments in many individuals with serious mental illnesses may limit their ability to effectively use computer technology in health technology intervention. So in this, as a part of this study, I evaluated three domains of neurocognitive functioning. They included immediate memory, language, and attention; and to do this, I used the RBANS, which is the Repeatable Battery for the Assessment of Neuropsychological Status. Each RBANS index score is expressed as an age-adjusted standardized score. Each has a mean of approximately 100 and a standard deviation of around 15.

And on this slide, for comparison purposes, I display RBANS scores in those three domains from a study conducted by Faith Dickerson on samples of individuals with recent onset psychosis—individuals with bipolar disorder—and then a healthy comparison group.

So you can see that on average, my sample, which again is diagnostically heterogeneous and in the end I should probably separate them out by diagnosis, but altogether my sample tracks pretty closely with the bipolar disorder group from Faith Dickerson’s study, scoring almost one standard deviation below the control group, definitely in immediate memory and attention, doing a little better in the area in language.

There is obviously some variability in scores probably due to the diagnostic heterogeneity. But – so my intent would be scores – is – I hope to investigate whether cognitive deficits mediate or moderate the effects of the computer intervention on any of the study outcomes.

So as I noted earlier, consistent with patient-centered care, one of the aims of this study is to see if the computerized intervention activates patients to participate in the self-management of their psychiatric disorder, in this case by advocating for getting screened for the metabolic side effects of their antipsychotic treatment. The hope is that the intervention will activate them to begin a dialog with their prescribers about getting screened.

And so to evaluate that, as opposed to asking them retrospectively whether they talked about getting screened or not, we elected to audiotape the first research visit after which the participants were exposed to the computer condition or the educational leaflet.

To analyze patterns of communication, we are using a method called the Roter Interaction Analysis System or the RIAS. It was developed by Debra Roter. She is at Johns Hopkins University. She is a consultant on this project. The RIAS is a very widely used method for coding patient-provider interaction during a medical visit. It has been used in hundreds of studies worldwide, more so in medical compared to psychiatric settings, so that is an innovation of this study in that we are using it to analyze dialog between individuals with serious mental illnesses and their psychiatrists or nurse practitioners.

Essentially RIAS coders listen to the audiotapes and they assign each complete thought, or as they call them utterances, by each speaker to one of 41 different categories of communication which represent things like communication processes including who is giving information and what kind of information are they giving? Is it biomedical? Is it psychosocial? They also code who is asking questions and what kinds of questions are being asked? Things like that.

Because they are actually either listening to audiotapes in this case or viewing videotapes, they are able to rate the affective or tonal quality of the interaction. You would not be able to do this if you were just working from transcripts. 

And finally – or as another example, they also code the extent to which conversation is patient-centered or who is controlling the conversation.

In addition to the 41 standard RIAS coding categories, the coders also listened for and documented mentions of or conversation around topics of specific relevance to this study. And some of those examples are include on this slide. For example, they were listening for whether there was any mention of any metabolic parameter or any metabolic screening and if there was such a mention, they were listening to see whether it was the prescriber or the patient who first initiated the discussion. They were listening to see whether it was the prescriber or the patient who first initiated the discussion of past or future metabolic screening. They also quantified the extent or length of talk about metabolic side effects or screenings during the visit.

One other thing they did was they listened and coded whether there was any mention of a report, a list or a pamphlet such as the optional report printed in the computer condition or the pamphlet that was distributed to everyone in the comparison condition.

So we were able to obtain audiotapes of about 75 percent of the first research visit, as shown here. Similar proportions in each research condition. The primary reasons in each group that an audiotape was not obtained included tape recording errors; refusal to be taped by the patient and less frequently the prescriber, on the day of the visit; and the presence of a third party at the visit. Either a family member was present or another provider was present. And because we were not equipped to obtain informed consent from a third party, we could not audiotape those visits.

There were also six participants in each group who did not complete a first research visit or any research visit.

So next, I am going to present some very preliminary findings from the RIAS coding. They are hot off the presses. I am still trying to understand them. I am only going to focus on mentions of metabolic side effects and screenings. I think they are most relevant to our conversation today. And I am not going to be presenting any results related to the standard RIAS codes that I mentioned because I have not analyzed them yet.

These particular analyses are unadjusted Chi Squares. They do not yet take into account that patients are clustered within prescribers. So what you see here are comparisons of mentions of metabolic parameters or a report by a treatment condition. And what we found was that whereas there were no differences by treatment condition with regard to mentions of weight, blood pressure or blood sugar, we did see that there were more mentions of LDL cholesterol, HDL cholesterol and triglycerides in those exposed to the computer program compared to the control condition. And this is exciting, especially given the literature that I presented that rates of screening of lipids in particular is quite low.

In addition, there were significantly more mentions of a report, a list or a pamphlet in those exposed to computer programs, about 50 percent in the computer programs, versus 20 percent in the comparison group. So those are exciting preliminary results.

We also looked at when metabolic parameters were mentioned whether the conversation was first initiated by the prescriber or the patient. In most instances, you can see here that the conversations were initiated by the prescribers. We found few differences by condition in first mention of any of the parameters by prescriber, except that there was a slightly higher rate of prescriber first mentioning LDL cholesterol in the comparison condition. But again, these are unadjusted results that I really need to look into further.

We found a couple of differences by condition in first mention of metabolic parameters by the patient such that there was a trend towards patients in the computer condition being more likely to initiate the conversation about any metabolic parameter. Also, patients and the computer condition were significantly more likely to first mention LDL cholesterol during this particular visit.

So in conclusion, we found that at baseline, Veterans with serious mental illnesses prescribed second-generation antipsychotic medications were very interested in getting screened for metabolic effects.

They felt very confident that they could ask their prescribers about getting screened and they were very interested in obtaining the results of their screening and talking about them with their prescribers.

As I have described, we developed a computer program to educate Veterans prescribed these agents about getting screened for metabolic side effects. And this program was designed to accommodate individuals with cognitive impairments so as to increase the usability of the program.

In preliminary analyses, we have found that Veterans exposed to the computer programs had conversations with their prescribers that included more talks about LDL and HDL cholesterol and there were more mentions of a report about metabolic screening compared to Veterans provided only an educational pamphlet.

In terms of Veterans’ responses to the computer program, most have viewed it very positively, commenting that it was helpful, it was useful, that they enjoyed it, particularly Veterans who are older. And those who had not used a computer before, they really enjoyed using it.

There have also been a number of comments from Veterans around not knowing their results until viewing the program like, I did not realize my blood pressure was so high.

In terms of next steps, things that I have been thinking about include, although there is a fair amount of screening taking place these days in the VA, it is less clear what if anything is being done in response to the screenings, and whether physical health is actually improving because of the screenings, and so this may be one next step in this project.

Also, as I progressed with my analyses, I would like to begin thinking about the feasibility and acceptability of more widespread implementation of this type of intervention if there seems to be interest from administrators, clinicians and Veterans.

So I would like to conclude by acknowledging that funding for this study was graciously provided by the VA Health Services Research and Development Service through a Merit Award that I received that is listed on the slide. I would also like to acknowledge my co-investigators on this project including Lisa Dixon from Columbia University and the VISN 3 MIRECC; Armando Rotondi, who I mentioned from the VISN 4 MIRECC; Clay Brown and Deb Medoff, who work with me here at the VISN 5 MIRECC; and Debra Roter from Johns Hopkins.

I must also express my intense gratitude to my research staff. Without them, the project would not have been possible or as successful in recruitment as it has been. So thanks go out to Stephanie Tapscott, Mary Brighid Walsh, Elana Schwartz and Wendy Potts.

And please feel free to contact me with any questions or ideas. That is all I have, but I would be glad to entertain any questions. And I appreciate your attention.

Margaret:Thank you very much. That was a lovely presentation. At the moment, Julie, people have not typed in their questions, so we will give them a few minutes to do so. Maybe while we are waiting I will just announce our next VIREC Clinical Informatics Cybereminar. It will be Tuesday, November 20. The topic will be “Google Search Engine for CPRS.” Interesting. The speakers are Dr. Augie Turono and Dr. David Ebeling. So that will be our next presentation.

So I am not seeing questions. If we could just have another minute, let people type them in. It could be that everything was so clear ...

I want to just say one thing to our audience. When you do log out of GoToWebinar, we really would appreciate if you would answer the questions in the evaluation. That would be very helpful.

So, Julie, I still do not have any questions. I am glad you have given your contact information because it may be that people would rather get in touch with you directly.

Dr. Julie Kreyenbuhl:Okay.

Margaret:Here is a question, however. Okay. How long was the intervention for each patient in each room?

Dr. Julie Kreyenbuhl:I am not sure if you are referring to how long did the intervention take? Which I will answer that. On average, it took them about 20 minutes to go through the computer program. That varied depending upon whether they chose to look at some of the optional educational slides, and also how long it took them to kind of digest the information.

If you are talking about how long was the study, the study took place over a one-year period and we intervened on folks up to three times over that one-year period at least four months apart.

Margaret:Okay. And there are more questions, comments coming in. One comment is just, GREAT PRESENTATION, all caps. So. Thank you.

Dr. Julie Kreyenbuhl:Thank you!

Margaret:And then the next question is, Is there a plan to continue this in your facility? Any plans to extend in another area?

Dr. Julie Kreyenbuhl:I do not have any immediate plans to expand it, but that – I would love to do that. I would love to do that. I think I need to see the results to see what outcomes changed. Hopefully some do. I am seeing some preliminary results from the RIAS. I think that I would need to speak with some higher-level policy administrative types in the VA to see if it is possible to expand. I think what is good about this intervention is that it is – would be easy to, for example, the *MyHealtheVet* website. Or in some facilities that have kiosks that are in waiting rooms, that would be another way to expand. So I have ideas, but there are no concrete ideas to expand.

Margaret:Sounds great. You anticipated the next question, which is, Are you planning to incorporate this intervention into *MyHealtheVet*? So.

Dr. Julie Kreyenbuhl:I would love to do that if *MyHealtheVet* would be willing to take me on.

Margaret:Okay. Next question, they are coming in now. Do you know about anything that is being done in the VA to assess followup after metabolic screening and outcomes of screening?

Dr. Julie Kreyenbuhl:I do not know of any programs or monitoring that is in place to do that. But as I mentioned on my concluding slide, I do think that is a logical next step. As I mentioned, and I hear from some clinicians, that it seems like there is a lot of monitoring going on, but it is unclear what the responses to the monitoring are. And who should be responsible for following up with that monitoring. Should someone in Mental Health be responsible? Should referrals be made to primary care, et cetera?

Margaret:Yeah, yeah. Next question: While the intervention was intended to activate the patients, did it also activate the providers in screening for metabolic side effects?

Dr. Julie Kreyenbuhl:Well, it seems so in looking at the preliminary results from the RIAS in that it seemed like in most of the conversations the first person to bring up talk or a conversation about metabolic monitoring was the provider. So I think the answer to that is possibly yes. I think I should also, in the interest of full disclosure, say that this was not a blinded intervention. I had to obtain informed consent from the prescribers, so they knew the purpose of the study. Of course, that was the case in both conditions. But I am not sure I got what you are getting that because they knew the purpose of the intervention, were they more likely to ask about it or were they more likely to ask because the patient brought in a pamphlet. It is not really possible to tell. But that is a good question.

Margaret:Okay, another question: Were patients using the computer able to repeat any module?

Dr. Julie Kreyenbuhl:We did not provide that opportunity specifically. The only thing that they could do was to go backwards, which probably would not be satisfying. Of course, they did repeat modules if they had more visits with their prescribers—so if they came in, they had the ability to see the same modules again. But not in a particular session, no. And I mean one reason to do that—we wanted it to be pretty brief. We did not want them to have to sit there for a long time. And we were doing this immediately prior to a visit, so we had some time constraints.

Margaret:Okay. We are just about at the top of the hour and I do not see any more questions coming in unless somebody is typing madly. Thank you very much for taking the time to present this talk. It was a lovely talk. I want to remind attendees about our next Cyberseminar in November, topic “Google Search Engine for CPRS,” as I said before. And please take a moment to complete the evaluation. And thank you, Julie, very much.

Dr. Julie Kreyenbuhl:Thank you, Margaret, for the opportunity.

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