**Transcript of Cyberseminar**

**VIReC Clinical Informatics Seminar**

**Integrating Measurement Based Care into the VA Mental Health Workflow with COMMEND**

**Presenters: Steven E. Lindley, M.D. Ph.D.;  Dan Y. Wang, Ph.D.**

**December 18, 2012**

**Integrating Measurement Based Care into the VA Mental Health Workflow with COMMEND**

**December 18, 2012**

Moderator:     Welcome. This session is part of the VA Information Resource Center's ongoing clinical informatics cyber seminar 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 speakers at the end of the session. A brief evaluation questionnaire will appear when you close GoToWebinar. 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 speakers for today, Steven E. Lindley, M.D. Ph.D., and Dan Y. Wang, Ph.D. Dr. Lindley is the director of outpatient mental health for the VA Palo Alto Healthcare System and assistant professor of psychiatry at the Stanford School of Medicine. Dr. Wang has his own software company, Medcisive LLC, and has a WOC appointment at the VA Palo Alto Healthcare System. Without further ado, may I present Drs. Lindley and Wang. 

Dr. Steven Lindley: Okay, thank you. First of all, thank you to everyone for attending our talk today to hear a little bit about the work we have been doing in the last few years to try to build a tool that will help us increase measurement-based care within the VA mental health workflow. Before getting started, we are going to ask a couple of questions of you to see who is out there. 

I think you are going to show the questions. The first one is to describe what category best describes your interest in this talk. Is it clinical, research or administration? As we are doing this we will have the votes tallied. I think those will be presented on the screen. 

Moderator:     Yes, just give me a couple of seconds here. The responses are still coming in. 

Dr. Steven Lindley: Sure. 

Moderator:     There we go. 

Dr. Steven Lindley:     It looks like it is a fairly even split here. It would almost appear to be a third, a third, a third between clinical, research and administration. Great. The second and final question is popping up on the screen. This is to assess how many of you are involved in mental health, either as a clinician, a researcher, or in administration. This is a yes or no response to see who is out there so we know how to tailor what we are going to discuss today. Okay, most of you are involved in mental health. That is useful information. Let me turn it back here. 

The outline of what we are going to go over today is first a brief review of some of the reasons for developing COMMEND, and describing some of the barriers there are currently to measurement based care within mental health. Dan and I will co-present some of the design features of our tool COMMEND. We are going to describe some of the lessons we have learned from our initial deployments that we have done to date. We will finish up with a brief discussion on some of the directions for future development. 

First is measurement-based care in mental health. So that we are all on the same page, and I know that most of you are involved in mental health, what we are talking about is the systematic collecting and recording of treatment interventions, outcomes, and medication side effects, and the manner in which it is saved in our electronic medical record so that the data can be used to inform treatment decisions for individual patients into the future. As was prescribed in the recent review by Harding, this type of approach of measurement-based care is essential to providing excellent mental health care. 

The reason for that, when you talk about looking at individual care, is that measurement-based care among other things, can prompt changes in interventions if needed when things are not working or the addition of other services or interventions when things are not working as well. On the flip side, measurement-based care can prompt stepdown in care after functioning has improved. The last two points were something that was key to our development, in that it orients providers toward outcomes. This is an issue that we struggle with sometimes, particularly within the VA. Some of our treatments and therapies can be a bit non-directive. Having a tool that emphasizes us going toward an outcome will be an important advancement. Overall, it increases interest in evidence-based care. 

Stepping up and looking at program administrators such as myself, what measurement-based care can do is help us do more frequent program redesign or targeted program redesign. It focuses our attention on outcomes. It increases our interest and attention to evidence-based care. It enables administrators to perform performance evaluations of staff, clinics and treatment programs by giving the data in our hands that we need, as well as allowing for more evidence-based negotiations with leadership. 

In a 2006 Institute of Medicine report on the U.S. quality of mental health care it was pointed out that despite the availability of effective mental health treatments, there are significant deficiencies that exist across the United States, including unjustified variations in the types of care provided, safety issues, and significant deviations from evidence-based care. In the 2011 Rand Corporation report that was requested about VA mental health care, they found that the quality of care for veterans with mental health or substance use disorders is the same or better than in the community. Quality of care across facilities does vary for unclear reasons. There are significant deviations from evidence-based practices within the VA. 

This report went on to suggest a list of solutions. One was to develop informatics tools within the VA that would help us have the ability to create clinical registries of patients. There should be lists to begin to compare patients with various diagnoses, both by individual providers and by programs. They suggested tools that can be accessed in real time without assistance that minimize additional data entry, are easy to use, and that would allow for high-level tracking of evidence-based care. 

With that, why are we not doing it? Some of the barriers that have been identified are from the 2007 VA consensus about informatics in general. They identified among other things information overload. We have so much data available to us now that it is hard to get the data that we need in the moment. There is inefficient data presentation that does not meet the needs of providers. There are organizational policies and procedures that impede use. We will describe some of those that we have come across ourselves. 

Other publications, studies, and opinions have identified negative impact on workflow in measuring outcomes as well as informatics, duplication of work, lack of buy-in of clinical leadership, insufficient training of providers in using these tools, lack of end-user involvement, unresponsiveness to end-user feedback when developing tools that do not meet the needs of providers, and barriers to rapport with patients which is a particular issue in mental health in that sometimes they do not fit within the way we interact with patients, and measures are not relevant or useful to clinicians. 

As part of our project we have done some surveys of providers, including this one of outpatient mental health providers, asking them various opinions about measurement-based care. What came across from the group is that providers generally rated tracking patient outcomes as very important, as you can see, but only 53% of them actually reported doing so with standardized measurements, even 20% to 30% of the time. They think it is a great idea but they are not doing it. 

Some of the reasons that were stated for not using standardized measures was that entering data into the clinical tools is way too time consuming for their workflow. About half of the providers in this survey did use individualized measures, reported using individualized measures to make treatment decisions but the majority of those recorded them in their note, which was available for them to go back and look at, but not for others, or to compare across time or for program managers. 

That background was the reason why we entered into this project. We started with funding in 2010 with a grant from the VA Greenfield Innovation Program. We have received some additional funds this last year from the Office of Mental Health. A big part of this tool is that we have leveraged the knowledge and expertise of a set of successful computerized decisional support tools developed within the VA for hypertension and opiate management, called Athena Decision Support System, developed under the direction of Dr. Mary Goldstein here at the Palo Alto VA. After seeing this tool, I thought this would be great to apply to mental health. 

Some of the design features that we have emphasized in the development of COMMEND are ease of use, trying to minimize additional data entry, making it relevant to patient care, fitting within the clinical workflow, and clinically useful data presentation for clinicians. With that I am going to turn it over to Dan, who is going to describe to us some of the COMMEND architecture and its features. 

Dr. Dan Wang:     Okay. Can everybody hear me well? Okay. This is a review of the COMMEND architecture. One of the main [inaudible]. When we look on the right hand screen, we view a daily [inaudible] in the early morning hours for all of the patient appointments in the clinic [inaudible]. This is where we [inaudible] data warehouse. We also get data in the diagrams [inaudible]. 

Moderator:     Dan, I am sorry to break in, but your audio is breaking up a bit. I am not sure if you are on a speakerphone or what. We are not getting the greatest audio quality from you. 

Dr. Dan Wang:     I see. Let me try this. Is this any better? 

Moderator:     That is a little bit better right now, yes. 

Dr. Dan Wang:     Okay. I am off speakerphone. Maybe there is an issue with the speakerphone. 

Moderator:     Okay. Thank you. 

Dr. Dan Wang:     Okay, sure. As I was saying here, the COMMEND does the data extraction in the early morning hours before the clinic begins. We get data like the history of the encounters so we can calculate things like history of missing appointments. We get a lot of data about their outcomes previously, either collected by COMMEND or through the mental health assistant. We also use [inaudible] primarily to get all of the previous progress notes. As you will see, we save certain custom data through the progress notes. All of this history of data is basically analyzed and then put into COMMEND's own SQL server database, shown in the middle diagram here. 

That is all prepared so that when the user actually needs to access it, they do not have to do any work. It is already prepared for them, as you see in the slides. A central server is shown in the middle box. We have basically a Web server and I will not go into details here. The Web server is basically going to access data in the COMMEND server database and show you the data. 

On the client side, on the provider's desktop, we have a COMMEND client. That actually consists of two components, a listening component that listens for CPRS selection of patients and log in, and opens up so that it works in synchronicity with CPRS. When the listener finds that the provider is a registered provider, then through this Web browser it connects to the central server, the [inaudible] server and brings back the Web pages that it displays. That is a brief overview of how COMMEND works under the hood. Next slide? 

Users do not actually have to click anything to start COMMEND. They just log on to CPRS and the listener picks it up and opens up COMMEND. There are really two reasons: one is that it makes it very convenient. It is kind of like working within CPRS. The other reason is that we are really relying upon CPRS for authentication. That was a major concern. We wanted to make sure that our users could see this patient data and that if you close CPRS, that COMMEND will also close. Before delving into the slide a little bit, I will also say at this point that all of our slides are simulated patients. We are only displaying simulated patient data. Next slide? 

If you click on the panel review button here, you will get to what we call the COMMEND panel. This really shows all of the patients who have appointments within a six-week window, for all of your registered clinics with that particular provider. This panel is geared at this moment toward looking at PTSD patients. We have a particular emphasis on looking at PCL scores. We show the last PCL score and the first PCL score. You can tell how someone has progressed from the time they were first entered into the system. As you can see, there is also data about the last appointment and the next appointment on the right hand side. There is also a column for the percentage of missed appointments in the last year. That helps provide information if someone needs more attention in terms of just getting to the appointment. You can sort all of these columns, for example, by the last PCL score. You can find the patients who are probably doing worse and may need a little bit more attention. You can sort them so you can see them at the top. The right hand side button, the storage button, allows you to search for a particular patient by name. Then if you click on the name, you see that the names are all underlined. They are actually links. You can reach a patient's detailed information by clicking on the link. Next slide please? 

Dr. Dan Wang:     Okay. Here you see the front page, looking at a patient's detailed information. It consists of tabular information as well as graphical information on the left. The right hand side tabular information gives you, at a glance, all of their latest outcome scores, some of which are collected by the mental health assistant. Some are collected in COMMEND itself. I will show you how that is done in a little while. You can see standard measures like PCLC and AEDC. Then there are some non-standard measures, like handwashing, which is useful for an obsessive/compulsive behavior. That then allows you to store and save, which is very useful. We also allow for things like side effects, which might be useful for people who are more interested in how they are doing with their drugs. 

The graphs show a history. As I have said, we collect all of this data historically. There are really two graphs. The top graph shows the outcomes and the bottom graph shows treatment. Treatment can either be in the form of therapy modes or in the form of drugs they are taking. We actually look at all of the psychotropic prescriptions and display them.

If you were to click on the measures bar, that actually allows you to choose a particular type of outcome that you want to display. We have four categories. There is the standard category. There is the goal tracking using our predefined measures. There are custom measures. We will talk more as we go along, and side effects. You can choose any of these. Then you will get a complete graph. The idea is that by looking at the treatment over time versus the outcomes, one hopes to be able to collate that and see if someone is actually making progress due to any type of treatment type of intervention. At the same time I have been told that these graphs are very good to show the patients. They get a sense of how well they are actually doing. 

When we go onto the next slide, which talks about how we collect the data, you can do that by clicking on the link that says treatment monitoring. That opens up this box here. The buttons on the left hand side allow you to actually enter certain things. Let's say you click on therapy mode. This actually brings up a little dialogue box. It allows you to choose a particular type of therapy mode for that particular session. There is something like 30 possibilities. They are grouped under certain categories like cognitive behavior therapy, care management, or pharmacological focus. You could describe in reasonable detail what kind of therapy that was prescribed. You put in the duration and modality. If you think you’ve done two kinds of therapy you can choose a primary mode and a secondary mode and then save it. Next slide please? 

Dr. Steven Lindley:     [inaudible] individual group or telephone contact, whether it was face to face or telephone. 

Dr. Dan Wang:     Before we go on, I want to show you that when you enter data here, it actually confirms for you on the right hand text box. What was entered in the therapy mode now shows up in the right hand. This is just a convenience feature, so that you can very quickly verify what you have entered. Then we also allow you to save some standard measures..... Next slide please? 

....through the system functioning scale button. Here you can enter things like the PCLC, the PHQ9 and the BPRs. You can add AEDC and BDI too. These are the standard assessment scores. We basically assume that the patient has been given a paper form and they have filled it out. Here all the therapist is doing is basically entering the total scores. Next slide? 

Again, if it is entered it gets saved. Then we have some predefined measures that you can use. These are called the goal tracking measures. Next slide? 

Here you are able to record certain positive behaviors, like socializing and recreation, at the same time some negative things like depression or anxiety. We have some standard questions about how well you are doing. This all counts toward the frequency. How many days of exercise? How many times per week did you exercise for 20 minutes or more? You can enter from zero to seven days. That allows you to keep track of how that person is doing. Next slide? 

Okay. Here we go to the customized goal tracking. Next slide please? 

This allows you to enter basically the idiosyncratic goals or problem behaviors that you want to use with a particular patient. Here on the right hand side you can actually create the goal. You can enter the name. You enter the question. Then you can select a type of scale. It could be a Likert scale. It could be a frequency, like how many days in a week or how many days in a month that you do something. Then it could just be a range of any kind, any range that you can define. Then you can hit create and the goal shows up on the left hand paddle. You can then click. If you select it, then it shows up as a question on the bottom. You can then enter the particular value. For example, here someone has entered how many times per day you have been washing your hands, even when they were clean. Here someone entered seven. This is a useful feature for tracking certain things. At the same time, I think that occasionally people have particular measures that we did not put in as a standard format. They can put it in here too, for use. Next slide? 

Then for a psychiatrist, you can also enter things about side effects. Next slide? 

You can enter various issues, either concerning the nervous system, gastrointestinal issues, skin issues, or sexual functioning. Again, you can basically put in how many days these side effects bothered you and choose in particular the most severe one. Next slide? 

All of this data gets entered at this point into COMMEND's memory system. Then when you actually save a note as part of the session, to record the session, that is when it all gets saved as part of the progress note in a structured format, into the note itself. Here is our note template. As usual it starts out at the top where you have to select the encounter. You have to select the note title. Then you have to enter some information about the treatment coordinator and time of the session. This is only the top part. We actually have many sections, some of which are required. The ones that are required are opened by default. The ones that are not required are shown on the left, the blue arrow, that you can open up and you can enter data. Of course you click the green button that saves the note to CPRS. That saves everything that you have entered, plus the structured data into the progress note. One of the good things that we do is that anything that was a previous COMMEND note, the system takes what was previously entered into the last note and fills it in for you, as a base for the next note. This is a very good time saving feature that providers really like. Next slide? 

As I said, the advantages of COMMEND note templates are that it automatically reloads the one from the previous note. If we are reviewing or editing that really helps providers save time. It really adapts to use, because it opens up sections that are used before. Sections that are not used before and are also not required are closed so you do not actually have to deal with it. It helps to streamline the note writing process. I think at this point I have gone over the main features from individual provider's viewpoints. I think Steve will show some other things in terms of reports. I will turn it back to Steve. 

Dr. Steven Lindley:     Just going back where Dan was going with the note templates. We are really trying to build in features that will assist providers in doing their work, to make their life easier, than can provide a bit of a carrot in general to using COMMEND. A couple of other aspects that we have had built in use the advantages of COMMEND's data extraction to do things such as what is shown here. We have been able to build what we call workload reports. Basically they are the encounter data from provider lists that we were able to put together, so I’m able to compare all psychiatrists, psychologists or particular clinics, filling up their individual appointments, group appointments, telephone encounters and other appointments and comparing them against one another. We are planning to build this a little bit more, using that data to do some other analyses as well, displaying it over time. 

Among the administrators this has been very popular overall, to be able to compare providers against one another. We have a mixed report from providers themselves although some do like to be able to see how they are doing against others. Another feature that we have had has to do with more detailed displays of patient registries. This one was actually designed for those of us in mental health, you know about the OEF/OIF psychotherapy measure. We pulled in the encounter data to be able to pull up and show on a timeline patients who were on this measure. Those in the green completed the measure. Those in the orange are incomplete. Basically without going into details, these dots and symbols all reflect different types of appointments. You can see at a glance, once you get used to this, why particular patients may or may not be making this measure. You can click down and actually get actual encounter data by clicking on one of the boxes. It is quite handy. 

Okay. Moving into describing some of the lessons learned to date, this comes mostly from the initial deployment that we did within our PTSD clinical team. This is made up of psychologists, social workers, recreational therapists, and one psychiatrist who are providing evidence-based psychotherapies for PTSD, located in three different geographical locations but providing care overall through telehealth to all of our nine clinics. 

What we did was tap into one of their retreats and did and hour and a half training session with the team at the retreat. Then we sat back and observed their behavior in the use of COMMEND. We did this through data collection on usage both quantitative and qualitative. The quantitative data included the logging of user events and online surveys that we had them fill out. The qualitative data included real time comments that could be entered within COMMEND and face to face interviews that Dan conducted. 

The user events logs within COMMEND basically were to save all interactions of providers with COMMEND. We were able to track the frequency of use in general, which features they used, why they used them in combination with one versus the other and what types of outcome data were entered. It was all just a matter of extracting this data and analyzing it. 

What are some of the lessons that we have learned to date? What became apparent, and some of this is actually looking at the logging data, it seemed kind of odd. We asked providers later what was going on with that, without making them too paranoid that we were actually observing their behavior. What we found was that for instance one provider thought their patients were missing from their patient panel. In interviewing her we found out that she was unaware of the paging buttons or search features within COMMEND. Another example would be a provider who thought scores were missing, the outcome scores that he had put in. He did not know how to adjust the display of outcomes that we briefly showed you earlier, so those features were not apparent. We needed to design it differently somehow to make it more self-evident as to where those features are at. 

Some of these we knew about beforehand, but there are workflow impediments to the use of COMMEND as it is currently designed. The first point is that it is not designed to meet the initial intake assessment. Therefore, providers who do not use it from that point do not start using COMMEND afterward. That is something that we will need to correct. It is currently a bit too cumbersome when cross-covering patients or doing brief evaluations. Therefore they are writing their notes within CPRS rather than within COMMEND. And something that we are currently addressing: many providers, because of the need to close their encounters within that day, they routinely do not write a note and therefore they close their encounters in CPRS and they will go back to write a note in COMMEND. As we will describe at the end, that is an issue that we are currently addressing by building a new feature that will allow them to do that. 

Organizational impediments that we have come across have to do with our performance measures and various other requirements. For instance the current performance measure for OEF/OIF patients to have a PCL from the mental health assistant, because they have to do that already they do not want to continue to use COMMEND between appointments because they have to remember when they have to call the mental health assistant or others. That is a bit of an issue right now. I have down here the need for telehealth consent. This is a minor issue, but it is one where there is a verbiage that we have when we are doing telehealth that we did not initially build within COMMEND. Therefore they have to go back into CPRS to try to meet that requirement. 

Currently the patient panel that we have shows all patients seen within a six week window. That may or may not be the patients that are assigned to that provider. They will sometimes get confused by saying we are showing them patients that are actually not part of their caseload. There is not an easy answer to this, but part of it with the data that is being entered by the mental health treatment coordinators may partially address some of this. COMMEND can only analyze notes saved into COMMEND. As I said, other providers are saving notes into CPRS or providers are going back and forth. Some of that data will not be available for COMMEND at this point. 

This slide points to motivations and procedures that we think will need to be altered. The tool in and of itself will not create universal measurement-based care. For one example, we have here that some providers are not motivated to save treatment interventions. To paraphrase that, providers are saying they know what they are doing. They know how they are treating their patients. There is no use for them to record the therapy mode because the treatment history is well known to them. Those same providers did go on to acknowledge that it would be useful to others. That is resetting their expectations and motivations. 

These are some of the useful features that providers have found. Some did feel like it has enhanced their workflow. They like the automatic display of previous note text for editing, for instance. This makes it easier for them to create their progress note. The ability to sort panels by outcome scores allows providers to see who needs more attention. This is something we thought they would find. We have had reports that this has been useful to them. There is the ability to check which patients have missing appointments. That percent of missing appointments has been found to be useful. We showed you test data. Basically with real patient data you can see the percent of missing appointments within the last year at a glance, which is helpful. They are able to see all of the outcome scores across the panel. Providers have felt that has given a fuller picture of the patient's state. There is the ability to review their own workload. Some providers have liked to actually do that, probably the ones that are doing better than others. 

These are some features that have been requested and since added to COMMEND. These include having a note backup or draft in COMMEND so they can come back and edit it later. Additional standard assessment scores have been added and will continue to be added based on the requests of providers. The ability to create variable custom goals was suggested, which we currently have in now. They can basically create a whole range of assessment scores. The ability to have complete management of the custom goals, to be able to add, update and disable it, where we had previously had that more as a centralized function. We are giving it back to the providers to be able to do that. We enable a selection of note titles with automatic reuse. They can pick from the available note titles within CPRS. They can do that within COMMEND. They can match up that note to the note titles they are more accustomed to using. They can update the encounter list at the time of note writing. Previously we were collecting the data in the morning, but sometimes encounters get added during the course of the day. That is a shorter time frame when those encounters are updated. 

Okay. Finally these are some of the future directions that we have for COMMEND. The first has to do with our continual modifications of features to facilitate use based on provider feedback. Some examples of this are trying to build time saving features into the note template. We are creating what we call a Quick Note. This is the ability to quickly say basic information about the encounter. This allows providers to close the encounter like they want to do, yet we are saving it and they can come back and edit later. They were able to save some basic essential information within COMMEND. Integrating entry of the therapy mode and outcomes into the note template, as we have noted it was in a separate leaf. We do not know why we started doing that initially. It has been very useful to build that right in as they are writing their note, which is something we are doing currently. Another example is that we are trying to provide easier access to actual items. What we are referring to here is the patient panel, where we show the assessment scores. We are going to look into providing some red, green and yellow indicators instead, as a more obvious visual of how patients are doing; better, worse or the same. They can click on that to get the additional information. 

The second component for our future directions has to do with modifications of workload to facilitate use. What is not shown on here is that the current project we have is with a group of our clinical nurse specialists with a performance project they are working on. This is to record outcomes for the evidence-based therapies that they have been trained in, so they are a motivated group of providers to be able to be our next deployment. I have made references here to what we are currently calling the E-Clinic, which is in its early stages. It is like a group of early adopters, providers within the mental health clinic who are dedicated to use of not just new informatics tools from our mobile phone applications to the Web-based applications to home telehealth and to the use of peer support specialists. We are bringing that all together into one group of providers. This includes COMMEND as part of that clinic. 

Finally finishing up, I will make a note that VACO is working on a mental health clinical registry as well, that is trying to bring in some of these features as well, into a universal tool within the VA to develop a mental health clinical registry. With that, just finishing up with our design team we have had various help from colleagues at the National Center and others. With that I guess we will open it up to questions. 

Moderator:     Okay. There are questions coming in. Here is the first comment and question: Dr. Mary Goldstein's work is supported by IT infrastructure not available in the eastern U.S. from what I have heard. Variation in care and room for quality improvement is present in chronic opioid therapies throughout the VA. What recommendations do you have in modifying your work to improving evidence-based practice within the eastern PACTs for chronic pain management? That is a long comment. 

Dr. Dan Wang:     Right. I think that there are ongoing efforts at the moment to get the basics for architecture of Mary Goldstein's work so that it can be adopted more widely. The system that we have works. However, it is not at this moment recognized as part of the standard IT infrastructure. It can be moved with a bit of work and migrated. At the moment I cannot speak for all of the efforts of Dr. Goldstein, but I do know that we have some efforts to basically integrate into the national infrastructure. Those are still ongoing efforts. 

Moderator:     Okay. Thank you. Can you clarify whether the scores of measures are automatically retrieved from the mental health assistant or entered by the provider? 

Dr. Dan Wang:      The scores from the mental health assistant are automatically retrieved. At the same time, COMMEND allows you to enter some scores and those are also retrieved by COMMEND, but not through the mental health assistant. 

Moderator:     Okay. There appears to be some redundancy between the features available in COMMEND and those in the treatment planning program of the mental health suite, for example setting goals and objectives. What efforts can be made or are being made to link these programs? 

Dr. Steven Lindley:     We currently recognize that issue. That is part of the issue of developing new informatics tools within our current system. We currently do not have a plan to try to link those two, other than what we are trying to do locally, which is trying to shift workflow between how the mental health suite is being used to create treatment plans, versus the ongoing updated plans that we provide providers within COMMEND, if that makes sense. 

Moderator:      Okay. Would data collected in COMMEND then be available through CDW?

Dr. Dan Wang:      Yes. 

Moderator:     The corporate data warehouse? 

Dr. Dan Wang:     Yes. It is available, any data that is collected. I will also add that all of the COMMEND data is saved in the form of structured data within progress notes. There would be an additional layer that we can provide, to extract that structured data from the progress note itself. It is saved as much as any progress note is saved in the CDW. 

Moderator:     Okay. Can this COMMEND be used by the evidence-based practitioner program to provide note templates, track delivery of EBPs, etc.? 

Dr. Steven Lindley:     Yes. As I mentioned in passing, that is our next group. It is going to be for the CVP for depression providers that have been trained within our system. That will be the next group to be able to use COMMEND to do their work. 

Moderator:     Okay. How are teams using COMMEND with treatment planning? Is there any plan to incorporate building treatment plans in this program? 

Dr. Steven Lindley:     Certainly the thought has crossed our minds. We are also mandated to use the current treatment planning software. Like a lot of things, we are working locally as to how things could be adjusted over time. 

Moderator:     Okay. Can you provide a non-optimistic estimate of the timeline for COMMEND to become nationally available? Several other programs have tried to incorporate measurement-based care into VA IT, but without success due to the IT administrative hurdles. 

Dr. Steven Lindley:     Dan, do you want to comment on that? We are standing in line. We have no idea exactly how long that line is. 

Dr. Dan Wang:     Yes, we have talked to various analysts who are shepherding us through this process of going from stage three to stage one software. It is class three to class one software. It goes pretty slowly, so I really cannot give an estimate. We’ve done the paperwork. 

Moderator:     Right. At this moment there are no more questions. They might be currently getting typed in. Let me say thank you to you both very much and also announce to the audience our next seminar Tuesday, January 15th. Alyssa Russ, Ph.D. will be presenting on prescribers’ interactions with medication alerts at the point of prescribing. I do not see other questions. Let's give people another minute to type them in. Thank you both very much. It is really interesting. 

Dr. Steven Lindley:     Feel free to contact us by e-mail after the fact. 

Moderator:     That would be great. Well, I guess no one is typing. I guess we will sign off for the holiday. Hold on. There is one more question. Is there an opportunity for other providers to become involved in beta testing? 

Dr. Dan Wang:      I think it would be easier if that provider were in our VISN or site in Palo Alto, just because of various technical setup needs. That does not mean we cannot to migrate to other places, but it would take some more effort to do that. 

Dr. Steven Lindley:     They are policy rather than actual technical barriers.

Moderator:     Okay. They are coming in. Will there be another presentation of this in the future? 

Dr. Steven Lindley:      We would love to come back to share our progress. 

Moderator:      Okay, good. Thank you very much. Let's hold on for just one more minute, since we have the time. People have to type quickly because otherwise we will say Happy Holidays. I think they are typing too slowly. If there are some more questions, I will say to the audience that we will get them, CIDER will get them. We will forward them to the speakers. Thank you both very much for presenting. This was very interesting. Happy Holidays to everybody. 

Dr. Dan Wang:     Thank you. 

Moderator:     Bye. 

Dr. Steven Lindley:     Bye.  

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