 Thanks, so this is one of the outputs from the working groups that you've heard some of already and you'll hear more of over the course of I guess this afternoon and certainly tomorrow related to family history. After hearing Reed Tuxin and the payers discussion I decided to put breakthroughs in healthcare as a subtitle for this group because the definition of breakthrough that I heard was something that would improve quality and take cost out of the system and I think family history really has that potential to do it in a very short period of time in the near term. So as you heard from the sequencing group we've had this group emerged out of the December Genomic Medicine 2 meeting and we've had four meetings including at that one. Our goals were to develop an agenda that would really help advance family history into clinical medicine and to develop ideas and concepts that actually might be responsive to an RFA or other funding opportunities either from NHGRI or other funding sources. Now when Terry gave her overview of why we were here I noticed that in contrast to some of her prior talks that she didn't have a far side cartoon so I decided to make up for Terry's deficiencies and indicate you know certainly family history is underutilized. It's poorly documented in the medical record and has a significant opportunity to identify individuals at risk. Certainly many studies have documented the advantages of family history in identifying risk characteristics that GWAS has really missed out on with odds ratios 2, 3 and 4 for family history derived information as opposed to from some of the genome-wide studies we've seen. So that's the reason why we're pursuing this. Over the last three calls we've grown in size. We have a diversity of individuals representing a number of institutions and organizations that have participated in our discussions and I put the E to indicate those individual institutions and organizations that are part of Emerge because I think having electronic medical record integration as part of an objective becomes something that could be quite important for family history. So as you heard earlier I think from Rex that we came out of the December meeting with an interesting and diverse list of topics to develop a outcomes research agenda linked to family history implementation and to really to use the principles of implementation science to understand how one might put family history into the clinical workflow in a number of diverse clinical environments. We thought that we might coalesce into some type of advisory group that would help inform particularly NIH clinical trials and other studies of where the opportunities might be to introduce and capture family history information which is often not done and also to provide educational tools to both the patient community and the provider community on both family history, its merits and its importance. As you'll hear we also have spent some time thinking about how to explore electronic media particularly social networking media to help patients gather family history in the community and also how do we validate family history became an important question, particularly patient reported information, how valid is that and I think an ideal goal, aspirational goal is to take family history data, molecular data, clinical data and build the ultimate risk model. And so as we thought about these over the last several calls the red indicate where we really prioritized our efforts at least up until today and I think what's highlighted in blue are really our correlative goals that I think we could achieve if we approach the three that are highlighted in red. So one of the first topics that came up was well what is the landscape of family history tools that are out there? And of course the Surgeon General's tool has been mentioned here and is familiar to I think most of you and a number of organizations have created their own and I think you may have heard us present on a family history platform that we've developed at Duke University Intermountain Healthcare has developed one of their own and several others including the University of Virginia were mentioned but we decided one of the things to do was to have a bake off meaning a way to compare amongst all the stakeholders in our working group at least give them an exposure to the opportunities so we had a webinar in which we looked at both the MeTree tool as the Duke University tool is called and the Intermountain Healthcare is our family health tool. So just briefly for those of you that couldn't participate, MeTree was developed around 2004 and 2005 and is a web based tool that is where patients will enter their family history data perhaps with some guidance from a navigator or some type of counselor in the office if they need it. The goal is to collect three generation family histories on as many individuals as possible. The software is set up to handle 48 disease areas. Our clinical decision support tools have been developed for the four areas that you can see here three cancers and thrombosis and the platform generates a pedigree, a tabular family history and provides a report both to the provider as well as to the patient and I'll show you an example of those in a moment. In two minutes 2003, 2004 origins it's a pretty boring user interface right now using radio buttons to enter information but I can tell you that there's an iPad version that will be launched sometime in the next few months that is pretty nifty. So I'm just going to take you through a couple of screenshots that are pretty obvious about entering information about your relatives, their names, their ages, whether they're alive or dead and whether you actually don't know and also who you might have talked to to gather your family history information and then at the end when you exit the program there's a number of surveys that are done to look at your understanding and comprehension of what you did, how it might have helped you in some way and also some process measures that we can talk about later. So the report, one of the reports that's generated as I said is a fairly standard family pedigree that you're quite familiar with and then there's this tabular version of the same report that is also generated and these are generated for the providers and interestingly enough and I think this has been found by others that providers actually pervert this way of representing family history over the pedigree most particularly in primary care most providers really just don't understand the circles and the squares and a bunch of other things and it's very hard for them to distill it down into something that's meaningful not that I'm not sure what meaning they got of this but they certainly prefer it. As I mentioned in the Metrie tool there's a patient report that is really meant to encourage the patient to take action so it really tries to explain to them why they should be talking to their physician about something that was triggered in their family history, but perhaps it's some of the rationale for it and also where they could seek out other information to become more educated about this. And at the same time the provider gets a similar type of series of information that is very top line actions that they should be taking and if they're interested in drilling down further why those actions are recommended and even further what are the guideline basis for those actions to be recommended in the first place. So depending on provider interest there's lots of opportunities to go down this menu and I should say that in this particular family history tool the decision algorithms are based on either U.S. preventive task force recommendations or cancer society recommendations so it's really guidelines driven decision support that's underpinning these recommendations. So the other tool that was demonstrated was the Intermountain Health Care's family history platform which is accessed through the patient portal. I should have mentioned that the Metrie tool is accessed outside of a patient portal it's a stand-alone entity at the moment and it really is really a nifty tool very sleek and well done. I think this was really the reason why when Mark was at a mountain health care that this tool was created was to really snoop around and figure out who was related to whom but nonetheless they've really done a fantastic job when you look at this interface you have a number of choices of how to enter the family history domain either to just begin to piece together your pedigree or to just if you're not sort of graphically inclined you can just enter numbers of the people in your family and if you already have had your ancestry done you can directly import your ancestry data and in the background the software will assemble your pedigree and there's a lot of nifty drag and drop opportunities with these icons. The pro band is right here in this diagram and you can begin to add many many relatives probably more than you probably want to have in your family to this display and this is actually Grant Woods family he was very clear that this is okay to disclose his family tree I don't know if the information is actually correct. So you get this nice display of a pedigree it's available through the portal it's also on display for you and for your provider and you can import other information about your about your health other conditions you might have and there's a on the on the right hand side you can see there's a searchable there's a searchable feature in there where you can actually look for syndromes that you've been told you might have or your family might have and document those as well. So at the end of the day not only do you get a nice pedigree but you also get this all this this sort of filed this file type of report that again even in the in the Intermountain Healthcare System is seems to be preferred way of displaying family history to the to the pedigree illustration and if we look at these two software platforms side by side in many respects they compare quite well the information is patient entered from both is web accessible either at a kiosk in the in the waiting room or at home a number of the informatics elements are are in place for both the the metri tool I think has embedded in it algorithms would lead ultimately to a decision support mechanism that is I think quite attractive and I think that's that's in generally what we're all looking for but the Intermountain Healthcare tool is not that far behind a number of a lot of the work that's going on right now with our family health is implementing the algorithms and developing the CDS tools that will enable it to also function in that way within the Intermountain Healthcare System and perhaps others. So at least in we were able to accomplish one goal of really beginning to compare and contrast what types of platforms and and and speak and characteristics they have and begin to think about which ones we might implement in a future research project. So in the last teleconference our group had we we began to kick around well so what are the ideas what are the things that we really want to push forward as as opportunities so one and I think this came from a number of the groups that were using EPIC and potentially other electronic health records was to really think about how how would this integration occur how does the integrate family history collection software and decision support into existing electronic health records that are also being developed and implemented across many health care delivery systems today and possibly to do this in the context of an STTR or SBIR type of mechanism with EPIC or perhaps CERNR or others but the I think you can see this list of of really critical questions that need to be addressed for this to happen about standardization of the information both on the input side and the output side also thinking about what are the information gaps and the workflow gaps that need to be addressed for this to happen seamlessly so really critically looking at that that information flow pathway and how it occurs in the context of real world clinic visits and making sure that the information is captured and delivered at the right time points to be most effective. I mentioned the validation of the information that's collected from the from the patients and the idea that of the possibility of bringing in other applications like Mitri for example that is a third-party tool and how does that interface how do we create the notion of interoperability between these possibly and making the family history readable in the electronic medical record all seem to be reasonable things to be investigating with some of the producers of electronic medical records. I think it was Mark and I'm also a friend of Mark's that made the recommendation that that there's a there is this series there's this group that is outside of what we're doing here is has developed clinical decision support tools and a clinical decision supports and consortium has has developed that would would be great to link to that as well as to make this open make anything that we're talking about open source so that many different systems can take the software and modify it to meet their needs and integrated into their local environments which I think are very reasonable things to be considering as well. So this was idea number one. Idea number two which really came from Jonas Almeida I hope I'm pronouncing your name correctly Amida at University of Alabama is really to take the social networking media that we have today Facebook type of applications and the sort as a as a way and an opportunity to capture family family health history data. And so visiting both you can see at the bottom of the slide some of you that there's a there's a website for a YouTube video that Jonas made to demonstrate this concept at least some of the early phases of the development of the of the mostly the informatics mechanics to allow this to happen. So the applicant API has been established there is a there's a prototype it uses the cloud in ways that I could not describe to you but maybe Jonas can and it really allows the patient and their families to capture the information in a in a diverse and effective way at least that's the goal to use the surgeon general's tool is at least one of the ways to do this in a standardized way. So Jonas if you have a second do you want to elaborate on on what I said because I'm sure I didn't do it justice. Sure. So the social media world has been developing and maturing. And now we actually have something we call social computing. So there is an infrastructure we can use in our applications and family history is a natural fit or genomic history for that matter it's an actual fit to this sort of architecture. So the for those who like this technical details is called open authentication. There was a first version that was very awkward we explored last time we met and since then the this protocol has enabled a different and a much more abstract use of social computing. So to give you an example for instance if you have relatives that like you you can ask them to feel their part of your medical history the same way that you feel their part of their medical history. So and you can imagine the same thing for the way a family history would interact with the genomic core facilities. So the genome is somewhere which requires quite a bit of storage. And again this external entity could be a partner that is incorporated in this social computing. So what happens is that the the center of this network of dependencies as always full control and awareness of which web services are engaging or storing the data that describes the medical history. Thank you I mean to me this this sounds like a very cool idea one that is certainly going to take advantage of of our of the networks that we were already developing maybe we're not as network with our families is this type of strategy would require but but you never know and I think we're going to talk about it I think a little bit later tonight. So the third idea and the last idea really that I wanted to talk to you about was really had to think about a family health history intervention that measures certain outcomes and again I mentioned this before but we really want to think about a project that would optimize how we collect family health history data and how we bring it to the point of decision with the provider predominantly in the context of any HR that that's not a formal requirement and to measure and demonstrate that the that there are improved outcomes and we can define what those outcomes might be as a result of this intervention at various stakeholder levels and the stakeholders we're thinking about are the patient provider and the system. So we talked about a number of potential environments in which this could take place and primary care was certainly top on on on our list but one one interesting idea was also to think about how family how family health history might actually influence decision-making in emergency room in an emergency department situation particularly in the context for example of whether somebody might be having a thromboembolic event or a myocardial infarction or something of that nature. So there's a lot of more discussion to think about but that would be a pretty interesting and unusual area to explore. The notion of bringing it to other other environments such as rural practices underserved environments as well and even to the to help the next generation of physicians really learn the value of family health history to bring it to the practices where residents and interns and and other providers are being trained and to do it in the sense of to understand whether this is really working in the real world. Does the intervention work under usual conditions I think is the question that was that was asked and the kind of study design that we had envisioned was something that is called a pragmatic cluster randomized trial. The idea being that first of all pragmatic meaning it's in the usual care environment clustered meaning that some practice environments might have access to the intervention and others would not that would be called usual care and do that in some kind of randomized fashion that we can discuss later. And while we were discussing this this paper came out which was I think if I'm not mistaken I could be wrong in the first publication of any outcomes research on family history. I don't know if anybody wants to differ with that statement. This came from Nadine Koreshi at the University of Nottingham and what they had done was essentially what we were talking about at the same time a pragmatic cluster randomized trial of 24 primary care practices that received family health history information about cardiovascular disease and the goal was to determine whether they could identify individuals at risk for cardiovascular disease more so using the family health history intervention compared to the usual practices of the providers in those groups. So the salient features of that was as I said the trial design about 750 individuals none of whom had previously diagnosed cardiovascular disease it was done in 24 primary care practices this was not an electronic intervention was all done on paper and they found 4.3 percent compared to 0.3 percent having risk of cardiovascular disease in the study which means if you a typical primary care doc might see 10,000 patients a year or even a practice might see 10,000 patients a year but nonetheless that means 500 patients were identified out of that 10,000 that otherwise would not have been using the family health care family health history intervention which is a not a non-trivial amount when you think about it in those terms but they hadn't they didn't take it the next step they didn't follow these patients long enough of course to see whether those individuals if they had an intervention in response to their risk factors had any changes and outcomes of course that would take quite a long time for this disease. So but this was really an important proof of concept that this could be done for us and I think it really paves the way for for studies like this across the breadth of topics that we're been talking about today I think so what we have been thinking about this is a very busy slide but I've just kind of call your attention just to the center part the color part which is just you know it's just a schematic of what a family health history intervention trial might look like collecting information at the outset as well as educating patients all done via the internet or web-based web-based design using METRI or other family health history intervention tools that provide a risk assessment clinical decision support so that at the time that the patient is actually interacting with their provider it's not about what is the information it's about what the treatment plan what the actions are so it really really jump starts the ability to do this without a lot of the cost of the interaction that takes place right now if you do a family history at the time of the visit and you could either go into if you're not at risk have routine screening whatever that is if you're at higher risk you might have a prevention strategy implemented or a screening strategy that it could include genetic measures or other measures and the boxes that you find hard to read here really are about some of the outcome measures and information both on the process side as well as on the on the on the clinical side process measures as well as clinical outcomes that would be ascertained throughout this process throughout this workflow and again this is also probably too much information for the for you to really read on this slide but as I mentioned at the outset this type of trial would really seek to look at patient provider and systems measures and if you think about it most of the academic types of studies that we do are really focused on the clinical measures in the patient but as we heard from the payers and others maybe there are other things we want to measure that have nothing really or very little to do with those clinical measures maybe it's the financial metrics of the system or whether we're really retaining our doctors because they're much more satisfied with the way that they interact with patients and so they're really happy and they want to see more patients I mean these are just hypothetical but but you can see there's there's a myriad of ways that we can really think about outcomes besides the box that we're normally programmed to think in so this is my last slide so the next steps would be tonight we're gonna gather around and discuss some of these opportunities and perhaps more we thought at the end of our last call that we for these three ideas that we would develop three subgroups like the like the genetics like the sequencing group had done but maybe as Rex said maybe we'll find that that is not not the way to go and we'll all come back together we'll see we hope that we will respond in some way using family history as a demonstration demonstration project for the RFA that we discussed this morning and we should really think about how to link this to some of the other working groups as you know certainly to the sequencing working group makes a lot of sense and as Marin and I were discussing earlier today putting sequence information in the context of family history could be quite powerful and really be informative about how to narrow the scope of where you should really be looking in the genome as opposed to looking at everything which I think was a topic that we've discussed at several points during the course of the day and then hopefully we can get some feedback and advice from all of you and our invited guests the other stakeholders. Thank you. Gene and then Mark. Do you have data on the two instruments as to the completeness of ascertainment across socioeconomic class educational achievement apps and fathers that sort of stuff? I can't speak to the Intermountain Health Care tool on that for the for the Duke system. We have had a diversity of socioeconomic groups and educational groups use this intervention with a high degree of success in capturing the information whether it's accurate or not still remains to be seen but I don't think that we've I think we still are fairly in a narrow scope we would hope to explore that in broader populations going forward and want to follow on as I mentioned to you earlier I wonder if there is a way of finding out how one can really identify families that you need to look into sort of a cage approach to whether you should take a family history a complete family history. I mean what's the trigger why would you do this in the first place and are there a subset of people that we should be really focusing on versus all commerce and I don't know if Marin or Mark or other people that have spent more time in family history than I have have want to address that. Yeah I think that conceptually it would be relatively straightforward as people were entering or interacting with the tool that if you define certain thresholds you could trigger ask drivers where you would begin to drill down and prompt them with additional questions much as might happen in the office where when you hear a particular piece of information from a patient use you know perk up and then tie that perhaps into more so just to use the breast ovarian camp cancer example that if you saw that the patient you know reached a threshold where there were two patients under the age of 40 with breast cancer then the tool would automatically go into say a breast ovarian cancer risk gap that would ask much more specific questions about that and would probably then trigger you know a recommendation that would look very different than people that would be interacting the standard way I think that's that's a reasonable approach it's one that has been thought about but it's one also I think that needs to be studied to see how it might work I wanted to just come back to the Koreshi study for to make two quick points one is is that even though the study was not intended to nor was powered to detect any differences they did find that in the intervention group there was a statistically significant difference in patients who either ceased smoking or reduced smoking even in the relatively small numbers at a point zero zero one level and that there was actually increased aspirin compliance based on the risk and attract with the risk that they were presented so they actually did detect some at least secondary outcome measures that have chains of evidence to the primary outcome of incident cardiovascular disease which was quite interesting the second point that I think was much more important was the accompanying editorial to the paper which was written by Al Berg who of course chaired the NIH state of the science conference on on family history which fairly well trashed the current level of evidence and importance of family history who in print eight crow which was very satisfying to those of us that know Al basically saying you know I that this study has proved me wrong that I didn't first of all I didn't think a study like this could ever be done but the second of all I didn't think it would actually show benefit and so what he outlined in his last paragraph is as a practicing physician this is what I want and what Jeff articulated in terms of the synthesis of the collection and synthesis of family history in the clinical decision support that works in the electronic health record is what Al asked for and I say if Al asked for something by God we should give it to him right I was just gonna say that we have developed a rather short tool eight questions I presented it last time it's embedded in our electronic health record at the VA and it is a I would call it a screening tool for for cancers family history of cancers and the follow-up is just making a referral for genetic services so it seems to be working pretty well yeah what's the accuracy of self-reported family history it depends on the disease and there's not great data on that for things like diabetes heart disease it's actually in the studies that have been done it's pretty good for things like mental illness and in particular substance abuses you might expect it tends to fall off now that being said I think it's also important to recognize that all the risk classifications that have been developed have been based on self reported family history so the we're dealing with their usual empiric risk that we're getting out of that so in some sense if we have validated family history we're gonna have to redo all our risk estimates because they're all off and we've actually done that in colorectal cancer utilizing the Utah population database which actually shows that in colorectal cancer the the risk estimates that are in use are reasonably good empiric compared to the actual validated cases but the interesting opportunity is particularly to build on the social networking ideas is if you begin to connect family members particularly within the context of either a single EHR or in a health information exchange where you actually can identify the individual and know what their diagnosed diseases are you can actually not only validate the information you could pre-create the family history if you have enough of that information so I think that's another interesting area of exploration that I know at Intermountain they're intending to to pursue using some tools that they have access to actually it's a perfect follow-on and I am not a friend of Mark's I've met him and I'm not impressed yeah all day yeah the question I have is particularly with the social networking has anybody looked at what becomes the obligation beyond to the pro-banned and it just seems like there's a potential major ethical and care issues there well I would agree I mean actually I was thinking about you and when I was presenting not other times but just when I was presenting that that you know the whole concept of social networking and also that you know how we use health information the context of a Facebook like of application sort of has a series of questions that probably you'll have a great time with but no seriously I think there's a there is a policy and ethics agenda that has to be thoughtfully conceived at the time that we really put out there a social networking tool to capture family history but I certainly don't have the answer to your specific question yes just few words so I also don't have an answer to your question the the good news is that the way we treat governance is now being objective mathematical treatment and people publish papers with mathematical descriptions of these dependencies obligations and what's called instantiations of user operators so the relationship between a user or usage and the data entity so the good news is that the level of the discourse is becoming more interesting more abstract and w3c is paying close attention to this all the world wide web consortium so there are web standards that are emerging to address these issues did you a question yeah Jeff I had a question about linking up with epic and because within the pharmacogenomics network we've also talked about you know can we begin to work with these major in our providers and so I guess I'm just curious whether that's sort of a hypothetical or you've actually had conversations and they're interested sorry but no this is this was an idea that was raised just a few weeks ago on our last call by Kathy McCarty I don't know whether she's had specific conversations on that Rex did you have you well yeah yeah so the merge network had not only Cernar but and not only epic but also Cernar and GE at steering committee meeting three times ago or something trying to engage them and then I know that some folks from Northwestern and I think some folks from Mount Sinai have been very actively involved with their genomics working group in terms of moving forward there was just a meeting last week in terms of actually thinking about putting data into electronic health record so there's already something of a relationship and the thing that's really going to change the landscape there is the meaningful use phase two criteria which actually articulates that one of the meaningful use goals will be representation of family history and electronic health record and really the vendor community right now is wholly consumed with creating products that are going to be able to hit the meaningful use category so that people can get reimbursed for implementation meaningful implementation of electronic health records and so if that persists in phase two we'll have a much better way to engage with the vendor community on this okay so Erwin yeah I just wanted to comment on the epic question and as Rex pointed out we at Mount Sinai and folks at Northwestern been actively engaged with epic and you know from our experience they're very receptive to developing custom connections with some external tools I think that's a very feasible proposition with you know some payments that you make to them that are not excessive but certainly it is it is feasible and certainly we've gone that path that is certainly I think a worthwhile investment and I think you know that's something to consider but the the the danger here is that if each of if there's a number of modifications to something like an epic tool over time it becomes a unique tool to whatever system it's being used in and it doesn't communicate across networks like we're trying to do so I guess my plea is that we try to have this as a coordinated conversation and I think as customers of epic we probably are a powerful force and could actually negotiate well I'm also not sure if it qualifies a small business I think that's why it would be an STS STTR so so as an epic user I actually pulled up the family history tool in epic while you are talking because I can access it from here obviously it doesn't actually look I'm I actually would like a little clarification of how you would work with them to improve their family history tool because it's actually very similar to what you're presenting certainly that's coming out in the sort of tabular form if you look at it and so I was actually unclear as to what you were proposing with that yeah let me I'll just make well the specifics of the epic proposal are really to think about what's missing you know so you just took a snapshot of it but I think we might really want to consider in different practice environments different disease areas to try to understand what the gaps are and help fill in those gaps so we have something that we all at least have a consensus is the right information to collect and of course what epic doesn't do now is provide the decision support downstream of the collection which is something that I think is desperately needed for these for the information to be used and the collection tool only allows you under one brother one sister one grandparent and it doesn't define sides of family and there's an infinite number of deficiencies in that particular web form and the number of diseases that are represented as structured data elements is very very small so it the the the improvement the improvement needs to be start over I think we'll move on coming