 Some of us were discussing Yogi Vera at lunch, which is an interesting cross-cultural discussion. But Jeff was talking about the theory of how this is going to work, and it reminded me of another Yogi Vera saying, which is in theory, theory is better than practice and practice it ain't. So we'll see how this goes. So we did the IT Bioinformatics Electronic Health Records group. I wanted to talk just briefly about the process that we used to come up with our prioritized list, because I suspect that different groups probably found their own way of doing things. So what we did was to discuss some more general philosophical principles to start with. I'm going to lead off with those. And then we articulated a number of things that we had heard through the course of the conference or that had been previously listed, and also new ideas that came up. We came together on shared understanding of what each of these is, which may not necessarily be immediately understandable to everybody in the group. So if there are some of these that need to be, I'll do my best to clarify these, but if there's some that need to be clarified, we'll do so. We used a voting process to prioritize, and I'll describe that as we get there. And I really want to thank our group. They bought into this and worked extremely well together, and it was just a pleasure. It's very difficult to do this in the short amount of time that we had, as I know you've all experienced. Okay. So the first thing is that we decided that our universe to discuss did not include anything prior to the creation of a VCF file. We know a whole bunch of stuff happens to get to the VCF file, but since we're on the implementation side, electronic health records, clinical stuff, we figured there are other people that can do that better, and we did not want to spend time creating solutions for things that are already underway. So that's one caveat. You can agree or disagree with that, but that was a decision that the group made. We also had a, there were a lot of conversations over the course of the last two days about standards. And so there was a fundamental question that came up, which is, if we as a group, which represents a substantial proportion of those that are in the genomic implementation space, if we chose to say, here's a standard, and we as a group are going to use this standard, there's a fairly decent chance that that could become a de facto standard. And so the question that was raised was, is it desirable, where possible, to identify a standard for a given class of data, description, definition, whatever, and as a group to decide, we would like to use, we are going to use this standard as we go forward with our projects. And overwhelmingly, the group said this is the desirable tactic, is to identify a single standard. Now we recognize that there are going to be some situations where that's just not going to be possible. We can't say, hey, we're all going to use ICD-10. So United States, time to turn that on, and those of you that are going to 11, come on back. So we want, but we wanted to avoid, you know, creating maps to different standards unless it was absolutely necessary, because the problem with mapping is that it can be done but you lose a certain amount of resolution and fidelity. And so that was just a philosophical decision that the group came to that probably doesn't lead to anything actionable, but might be useful in terms of informing how we implement some of the action steps that we're coming up with. So any questions about that philosophical discussion that took us about 10 minutes? Tim. Saying throw the BAMs away. No, no, no, we're saying for our discussion, for the purposes of our discussion only, that we are going to discuss data from the VCF file going forward. Nothing about throwing the BAMs away. Other people will solve the, and they may remap things and generate an updated VCF. Correct, which we will have to deal with. So we understand that there's work that's going to be happening over there behind the curtain and that we're going to have to deal with that because even if we decide, for example, we all agree that we're all going to call this variant this thing, that when you change the reference, that it may have a different name. And so we just didn't think that was something that this group would spend its efforts on. Okay, is that fair description? Again, you can agree or disagree with the decision, but that was the decision we made. Okay, so great. So this is going to be a little bit, this will go a little bit out of order. So I apologize for this. We just, in the three minutes we had between the end of the group and the presentation, here we didn't get a chance to put these in, reorder them. So you'll notice here that in the voting, there are two scores. Okay, so the first score was of all the things that we listed here, what are the things that you think are most important and everybody got to vote for three things? Okay, so a problem that we really need to solve. And that's the first score. The second score is how feasible is it? How easy would it be to solve this problem? And the vote was for how easy it was. And we asked people to separate those two problems and vote independently. I can only trust my members of the group that they actually did that, but that's okay. The interesting thing about this was, and then the complicated algorithm that I came up with is to add those together to get the total score, which gives us the prioritized rank order. So the one that clearly rose to the top of our group by a large margin was define the key elements that should be stored in the EHR. And by elements is purposely undefined, but it would include information relating to variants, phenotype, all of the things that would be necessary to actually make a clinical decision using genomic information. And so that was scored extremely important, and also it was thought to be very feasible. Number two, with 11 points, was to try and learn from others. We heard a number of groups from different countries over the course of the last two days, as well as consortia within the United States funded by NHGRI that are tackling a number of these issues. And so the group thought it would be important to study existing solutions and compare them in sort of an in vitro bake-off, if you will, to say of all the solutions that people have come up with for the problem of representing genomic data in the EHR, or for building a clinical decision support rule, or whatever, which ones are more robust and more generalizable? In other words, which ones could be more readily implemented across a group like this, and then use those to select as sort of best in class? And so this could be across a variety of different things, variant databases, meta databases, how we store VCF files, informatics pipelines, all these sorts of things. So it was felt to be reasonably important, but it was also thought to be quite feasible to do that sort of an aggregation. The third rank at 10 was to develop a global resource for actionable clinical variants. There is, this was deemed to be very important, perhaps less feasible, but certainly something that people thought was a very important thing to do. We had two at the number four position, collection and aggregation of gene and variant data, so we have examples of this, such as the Exon variant server, Exome variant server, and this should be HGMD, the human genomic mutation database, and there are others out there as well. This is thought to be extremely important, but I think everybody recognized that this is not an easy thing to do. And then also, with eight votes, define necessary federated databases that are needed to implement genomic medicine. So again, things like EVS, ClinVar, ClinGen. Now, you have recognized here that we did something that you can agree or disagree with. Here we basically said we want to have information about, you know, genomic information, but we also had one about actionable variants. And so I think we poached some of the votes from this into the actionable variant group. And so in some sense, the group agreed that these two things are separable and that it is more important for a group like this to focus on aggregation of actionable variants, however, that is defined as opposed to more general aggregation. This was not scored as being tremendously important, although people thought it was quite feasible. And let's see here. I'm sorry. I missed it. Oh, yes. And then there were two at number six, controlled vocabulary for a phenotype ontology and included within that it would be an inventory of existing ontologies. We've heard about a lot of ontologies and we should move those together. Everybody thinks this is really important, but I think they all recognize this is a very difficult thing to do, to create and then get everybody to agree to an ontology, although it has certainly been accomplished in some spaces. And then aggregation, clearinghouse of genomic medicine implementation guidelines. So as different groups actually implement genomic medicine, whether it be for pharmacogenomics or cancer or whatever, and we define here's the guideline that we're going to use to provide guidance to our clinicians to do this. If we could aggregate all of those, that would be a useful activity. Again, it didn't score very high on importance, but it was thought to be highly feasible. I won't go through the rest of them. They're all represented. Jeff, do you want to run your question? Do you want to run the actual voting process at this point? Yes, I'm getting there. I just wanted to say, do you want to take over? Do I want to take over? All right, great. You'll pry this microphone from my cold, dead fingers. So is there anything that we missed that we completely passed on that you think should be represented on this list that we did not cover? One that you have there. Studying existing solutions to IVs, so identify solutions. That was a, Jackie was trying to read my writing on the different. So this is the idea that we're implementing clinical decision support as an example in eMERGE-PGX. But each one of us is finding that we have to find our own solution to do that implementation. So part of the work that the EHRI group is doing as part of eMERGE is to compare the different solutions that we've come up with to say, is there a better way to do it that we can all learn from? And in fact, you've asked us to expand that to CSER to say, okay, we've got a CSER group doing this and an EHRI group doing this from eMERGE. Are there solutions that we all identify as saying, oh, that's a much better way to do it than what we tried to do. And then expand that to the much larger universe of attendees at this meeting to say everybody's trying to solve these problems. If everybody throws in their solutions around a certain problem that we identify as being important, can we identify what seems to be a best in class solution? So the idea being to identify best practices and then disseminate them somehow. We don't just identify them. Well, I think the idea would be that the dissemination might be as simple as a clearing house. So here's the different ideas and here's what we think. It wouldn't necessarily presume that we would say, hey, this is a great, everybody do it because we recognize there are local problems with that. Bruce, do you want to come down? No, you didn't have a question. Tim has a question. There's a discussion about these kind of databases so you don't have to all do it yourselves. The group in this room is kind of the academic group or the hospital group. It's not the commercial group that's now offering services. And as far as I can see, they're all doing these databases themselves. Are they being left out of the loop? Are they happy to do it themselves? Does anybody know what their state of mind is? I think it's fair to say, and I don't speak as one that's phenomenally informed. And actually, Heidi, why don't you talk to this? Because you've had way more experience with ICCG related to that. Yeah, so I think, I mean, those of us who are academic are also offering services, so they span both commercial and academic environment. But if you talk to the commercial labs, which we interact all the time with, they're in the same boat we're in. We all need better resources. And a lot of even the commercial groups are willing to share their data, and they want desperately a resource to draw from as well. I'm not talking about the commercial diagnostic groups. I'm talking about the companies that are now offering genomic interpretation services. They also want these databases. And there's some companies that I know of that are outsourcing curation projects and hiring people to go through literature and building massive databases. The problem is that there's not an evidence-based approach to the evaluation of that data. It's more of a collection process. And so the quality of what comes out of those pipeline processes is unfortunately not that high. But it is the only solution that the heavily bioinformatic-based companies have today. And absolutely, if they have a curated clinically-oriented database to draw from, there's no doubt they will be delighted, at least in my mind. I don't know if others disagree. So I think that that's good. I'm also being given the frantic time signal here that it is time to vote as they say. I am going to do this perhaps not the way Jeff would do it, but there was a clear winner from the workgroup. And so what I would like to do is to ask the group as a whole if you endorse the workgroup's conclusion that this is the one thing that we should take forward from the workgroup. And I'll just get a straw poll, yay or nay on that. And if there's a strong number of nays, then we'll go through and take a look at the others. Look at that. Is that like a one-month intense effort and you have your list and you're done? Or is this the kind of thing that would take a span of months? I wasn't giving any specific instructions, but what I told the group was six to 12 months, that this is something that would be achievable within a six to 12 month period of time. But that was only me. So Mark, I'm letting you have your way with the way you're carrying out the voting, but I insist that you have a second choice. Okay, fair enough. So you said we were going to come away with one from this group. I'm trying to make it easy on you, Jeff. So if you don't like the result, it's your own darn fault. So for number two here, how many would endorse this as that we got it right? How many would say yes to that? Just show of hands. Yeah, you can't vote yes and no on this question, all right? So hands down, now you see what I was dealing with in the group, all right? So how many would say no, this is not the most important thing. How many would endorse, would say that? Okay, so there are four people, five people that would say that this is not the most important thing. Most importantly, two of them are the people that are actually funding us. So taking that into account, we will go through the others. Welcome to democracy, friends. Okay, so what we're going to do is very quickly go through the other that are on the list. And quick show of hands, I just say yes, you only get to vote once, so I'm going to show the whole list, you get one chance to look at it, go through and I'll just select the one that has the most hands by my determination second time around. So again, we're not voting on number two. So what's the connection between genotype and phenotype? Determination, the location of clinical decision support to expand that a bit. Should it be located in electronic health records? Should it be located in the cloud? Should it be located somewhere else? Archiving and aggregation of clinical decisions, so decisions made using the information? No, because you don't know all the choices. Geez, I didn't go through all of them. So I just wanted to make sure that everybody, I'm trying to do this so that everybody understands, I know I am. So despite the problems, controlled vocabulary, you know we'd be done by now if you, controlled vocabulary for clinical activities, controlled vocabulary for phenotypes ontology including an inventory, what information should face patient and how should this be organized. That was the only patient facing, one to emerge. The federal databases we talked about, define different needs for germline versus somatic variation, collection and aggregation of patient level data, and automated family history from electronic health record analyzed and pushed to clinicians. Okay, so votes for what is the connection between the genotype and phenotype? Okay, determination of the location of clinical decision support. Well, I can't count that fast. There was one for the first one, there are, I was just going to say here's the most, but that's okay. Jackie, count, quick, very quick, all right. Archiving and aggregation of clinical decisions, zero. Controlled vocabulary for clinical activities, zero. Controlled vocabulary for phenotypes ontologies including inventory of existing ontologies. Two, what information should face the patient, how should this be organized? Three, four, define necessary federated databases needed to implement genomic medicine, all these listed here. Once! Yeah, so this is your second vote, right. One, two, three, four. Four, define different needs for germline versus somatic variation, zero. Study existing solutions that are more robust and generalizable around, we sort of define that a little bit more. Eight, collection aggregation of patient level data, collection aggregation of gene variant data, excellent variant server, nine-ish aggregation cleaning, clearinghouse of genomic medicine implementation guidelines. One, two, you voted twice. Automated family history from EHR, push to clinicians, one, and global resource for actionable clinical variants. That one has about ten, so. But there were a bit more multiple votes here. So the two that I saw was this one, the global resource for actionable clinical variants which actually maps to an existing activity, and then the ontology. I think those were the two that I saw that had the most. So I'm just telling you that in the group, I don't disagree with you, but the group said we should look at these separately, not together. Right. So, okay, I understand. I'm just reporting what happened. I'm happy to stop anytime. Great, thank you. Thank you all so much.