Event ID: 1364430
Event Started: 6/12/2009 8:14:44 AM ET
Please stand by for realtime captions.
Good morning, everyone. Welcome back. [ Music ]
We're going to begin the morning with follow-up to discussions from our last meeting on direct-to-consumer genetic testing. And that chair, Sylvia Au, will summarize the report, which should be tab 5.
[ Speaker/Audio Faint or Unclear ]
Yeah. So -- as you can tell Sarah is reminding me --
[ Speaker/Audio Faint or Unclear ]
Honesty only goes so far. When we broke up yesterday we had agreed we would get back to David Bloom enthal. Marc drafted -- captured the thoughts in would we think would be a reasonable document to send back to him. What you will find soon at your place is a draft memo, but since they're meeting already on Tuesday what we would like is to get your agreement that is on target to go forward. We want you to pay attention to Sylvia, take a quick look at that and then we will get back to it and make sure it's on target. But first -- Sylvia.
Thanks, Steve. First I will present what the task force has been doing in the three months since the last time we had a meeting. Then we will have time for discussion of the draft paper. For those of you who have been on the committee you know this is superspeedy.I want to start by going through some of the background and intent of the paper and some of what we say in the paper and the recommendations. We established a short-term task force to look at direct-to-consumer genetic testing. The objectives were to look at highlights -- identify issues that are not addressed by our recommendations we've made and the committee might want to consider for future work. Of course, as with all activities, we have a wonderful educated, informed task force. I was telling Kathy I should have scheduled a 4:30 a.m. call on the east coast just for payback. Of course, I want to thank Kathy she's been wonderful. We have the most wonderful staff of any committee ever. The goal of this session is we are going to come to some consensus, hopefully some happy medium about issues related to direct-to-consumer genetic testing, recommendations and any remaining concerns that may require additional action by this committee.
Of course, we always try to limit the scope of our paper, we don't want to address everything under the sun. We decided this will be limited to risk assessments or diagnosis of disease or health conditions, information about drug response. We excluded forensic analysis, ancestry and paternity testing as much as possible. We also kept the definition consistent because the recommendations from the oversight paper address the definition. The intent of the paper recognizes that as usual not all of the concerns of direct-to-consumer genetic testing relate soully to the testing, there's great overlap. We also do identify issues that may be unique to this area. If a health provider is not involved in the testing and then sometimes government regulations that pertain to genetic testing may not apply to direct-to-consumer genetic testing because of the way that the testing is done.
We will start with the benefits of direct-to-consumer genetic testing. We identified many benefits. We feel that it offers increased availability to genetic testing. It promotes health literature, that was one of the things we discussed in detail. It would hopefully drive the consumer to learn more about genetic testing, it might drive their healthcare provider to learn more as well. It supports adoption of health promoting behaviors hopefully. They might change their health behavior to become healthier. It supports -- it provides an alternative route to medical research. There are research aspects to some of these companies, it might be a route to research as the Parkinson's disease foundation told us about yesterday. And it offers confidential access to testing to those that might be concerned there might be adverse actions against them if the results were known.
Our concerns about direct-to-consumer testing -- the unprecedented speed at which the technologies are evolving and being translated into products has raised concerns. As in our oversight paper, we do have concerns about test quality and analytical validity. We also have some concerns about the lack of standardized terminology, standards to select variants and standards criteria in assessing aggregate risk. We have, of course, as we did in the oversight paper, limited evidence of clinical validity and/or utility of certain tests. We also are concerned with false and misleading marketing claims and incomplete or unbalanced promotional materials that might only reflect the benefits of what you might get and not any of the down sides. The ability for consumers to evaluate the marketing claims and make informed decisions about testing is a concern. Ability of the consumers to understand the test results once they get back to them. And the healthcare providers being inadequately trained to help interpret the results once their patients bring in the test results to them.
We also have limited data on psychosocial impacts. We have concerns about protections for the research use of specimens obtained and the data derived from the specimens. There might be unclear privacy protections because of the way the testing is provided to a consumer. There are inequities to access because you have pay for the tests to get them. There's insufficient safeguards for third-party testing. When we went back over our old recommendations that we had made over the many reports that we have done we found there were eight recommendations that address some of the concerns that were raised. We found some concerns had no recommendations yet. Those are the ones we will bring up for future consideration. One recommendation on an lit validity, [ Speaker/Audio Faint or Unclear ], companies that skirt regulations, one recommendation and false and misleading claims is one recommendation.
I'm not going to read our recommendations again in detail because our committee likes to make very wordy and long recommendations. And you should all have this memorized. The new members should have it tattooed on their bodies somewhere. We know there's gaps in how analytical validity and clinical validity data are generated. We recommendationed to HHS they should ensure funding to increase the validity data. Continued for analytical validity, funding to establish and support laboratory consortium for a sharing of information and that HHS should continue to work to support development, enhanced public reference databases with this information in them.
Again, for analytical validity we have that HHS should provide the necessary support for professional organizations for applying the tests in clinical practice. We have the recommendation that the committee is concerned with the gap in oversight related to clinical validity and the FDA should address that all laboratory tests should to be take advantage of their current experience in laboratory tests. This would require a significant commitman of resources. Continued with clinical validity we had the recommendation that HHS convene a work group to look at the criteria for risk stratification, process for applying the criteria, et cetera. And also for -- to expedite the review process the committee recommends the establishment of the much beloved mandatory test registry that was a little controversial.
Then for clinical utility we have that HHS should create and fund a sustainable partnership to assess the clinical utility of genetic tests. It goes on with a long list that covers two slides on what that public/private partnership should do. I will not read every one of those points. Again for clinical utility, to fill the gaps of knowledge. The federal public/private initiative should develop and fund a research agenda to fill the gaps and disseminate the findings to the public via publicly supported website such as Gene Test. We get on to the education recommendations: Just like we talked about yesterday the HHS should work with all relevant government agencies to increase training, education for all of the key groups involved in genetics and genetic testing. And that should be culturally competent in many languages, et cetera, et cetera. The other one is to ensure that providers have appropriate education and training and be able to integrate genetics education into all areas of practice. Continuing with our education recommendations: The HHS Secretary should provide financial support to assess the impact of genetics education and training on health outcomes and incorporate genetics into relevant initiatives of HHS including the national health information infrastructure, which I think we talked about yesterday. Patients and consumers should have information to be able to translate -- to evaluate health plan benefits and so they can figure out reliable and trustworthy information and have federal websites with accurate information available to them.
And then we have our lovely CLIA recommendations. Hopefully CLIA look at the regulations and within their statutory authority expand their regulatory authority to encompass the full range of health-related tests and the FDA exercising their authority to its full extent. We had the recommendation that address false and misleading claims: Including direct to consumer tests. We must have been very forward thinking at that point to make that recommendation because it fits into our report now. We get to the part where the task force identified the concerns we could not find recommendations that we have in prior reports that would address those concerns. Some of the concerns, um, that we might want to consider for future action is that -- unclear or insufficient prioriticy protections, limited data on psychosocial impact, potential exacerbation of health disparates.The standards for terminology, selection and calculating variant risk is another issue that the committee might want to take up. So -- today would we would like to do is tell the task force are the issues addressed adequately? Do our prior recommendations address these issues? Are there new concerns that might require action from us? Our next steps are to decide whether this paper should move forward to the Secretary of HHS and if we decide to move forward we have to decide the timeline for the edits and when to transmit the paper and determine the action that the committee might want to take on some of the concerns that have not been addressed by prior papers or recommendations.
So, now we will open it up to complete agreement from the committee and move on. [ Laughter ] Opening the floor now to anyone that has any questions -- or comments. Marc, of course.
First of all, you did an excellent job. Taking the recommendations that are relevant from prior statements is the way to go. I didn't have any concerns or issues with the statement. Even it is, recognizing there's issues that may not have been addressed, I think it's important to move forward. The only thing to add to the list that have not been addressed would the issue of sample and data ownership. One of the other things that has come up with direct-to-consumer testing is if a company was sold to another company what would be the rules around transfer of those specimens, ownership, that type of thing. That's another area where there's no protections-relating to the consumer. That's the only thing we might want to consider doing more on.
Sheila?
I think you guys did -- this is very, very, big area. From this point we would go back and take a look at these and the prior recommendations and really scrub them to make them more relevant or updated?
We didn't want to change any recommendations. Because most of the recommendations here fit within the general topic of what we're talking about. The new recommendations that might need to be made then would take longer. What we want to do is move this quickly, because if we're making new recommendations it takes us a long time generally. Even though it's not directly aimed at direct-to-consumer testing the scope of the recommendations fit the concern of direct-to-consumer genetic testing. If the committee decides we need to hone in more those would be new recommendations we would move forward to make.
I have a couple of thoughts on that. First, I think there is a lot of confusion between direct-to-consumer advertising and testing and physician- ordered testing. I don't feel it addresses the issue as well as we could. I think this is something that people are looking for more specific advice on. Also, just generally if we will provide advice to the Secretary my recommendation is to update some of these recommendations in a way that is more useful to the Secretary and would get more attention and be implemented. I think it's very difficult through something like HHS should ensure funding for -- they only know what to do with that. It's important, but I think it's better if the committee can really give advice that can be implemented.I would propose that we would go back through these and really direct this issue to direct-to-consumer genetic testing and really walk through these again to see how we might reform late -- that might be a strong word -- but give the Secretary more directed recommendations that could be more valuable immediately.
Are you suggesting that we go back and reassess all of these in terms of genetic testing and do the kind of reviews that led up the recommendations?
I'm not sure what the process is in terms of where we are at this point. These are from reports that are broadly across the genetic testing landscape.
They're from different reports, not only oversight but coverage and reimbursement report.
These have already been made.
Right.
Correct.
I don't know to what extent they're implemented or not. If we're making recommendations on a more specific area I don't know it's that value to go back and sort of just plug in the older recommendations. It might be more valuable to take more time to maybe get a short list of things that would be directly associated with where the concerns are focused on direct-to-consumer testing and advertising. Making them more directedded and specific.
I mean -- I feel it could be -- I completely agree. First of all, you have a done a masterful job.
Challenging area.
On this area of education, we identified DTC as improving education, literature but also about misleading. We say we should fund better genetics education, which seems a little unrefined and also difficult to implement. I do think we can be -- we can edit down and make the linkages more explicit.
One of the things that the committee had wanted to do is because it's an interesting topic in the news sinceAmway is getting into it now --
[ Overlapping Speakers ]
Yeah.
I think one of the things -- this was thought of as a vehicle to bring up recommendations that were general, that crossed a lot of areas to the new Secretary. This will be the first -- besides the summary that we did, this will be the first issue that will be brought up to the Secretary. I don't know what the committee thinks about going back and narrowing all of the recommendations now. They are not really specific to direct-to-consumer testing. If we recommend education it crosses the board. We have an education task force.
Right. That's the question. Are we making recommendations about direct-to-consumer testing or just pointing out all of the various recommendations we've made across the board?
We're taking -- we describing the issue. Here are prior recommendations that are still in effect that would improve -- would try to address the concerns of direct-to-consumer testing, that was it.
Sam?
First of all you and the task force have done a comp hepsive job. That's the applause. Like Sheila and others, I believe this really needs more of a focus on the DTC issues. First, people understand it. We've seen it gone awry in the pharmaceutical industry when claims are not always backed up by science. I think that should be the pair mount focus. If you do that then under that theme we can bring some of the issues of consumer knowledge and education and clinical validity and scientific themes. I think what this document does is covered too broad a landscape. Focus would be lost. If you do focus on direct-to-consumer the issues that came up yesterday on the integrity of how samples would be used and consent and those issues are relevant. There's another dimension, that's where Marc was going, these are early-phase companies. What happens to samples and information when they don't succeed? Those are some of the safe gars that need to be built. I think we can focus on DTC, the safeguards, the clinical validity and the claims that are made. And then build around it. But right now we just taint such a landscape picture, I think it's less actionable than it could be.
I just see details, details, details. Great job. Your group has brought the issues together. I do agree in moving forward -- those recommendations, those points that you made that are future might be ideas for the future. I think you could focus on some of those. The impact on health disparates. A lot of those have not been addressed. Rather than leave them as potential future recommendations or topics we may want to work on I think focusing on some of those might be where we could bring something new to the discussion.
Okay.
I want to remind the committee the last we presented this as the outline for what we were going to do -- if we move to, you know, redo recommendations, add new sections, it will expand the scope of what this project is going to be. You know, if that's what the committee wants to do then I think we have to make some decisions based on staff and other resources. I just want to remind the committee this was not the outline that was agreed on.
[ Overlapping Speakers ] [ Laughter ]
Who invited these people, anyway?
They're going to have to bring more chocolates.
Can we give these back?
On the other hand you are also getting a new set of eyes on this. How do you make it more meaningful?
Marc?
I'm seeing a blended view here. One of the key points in my view is that the companies in many cases are trying to separate themselves out by saying we're not doing genetic testing, we're doing education. Or we're doing rec ree action. I think we can very rapidly say you are doing genetic testing and in fact you are subject, or should be subject, to the same oversight that anybody else doing genetic testing is doing. Therefore, the recommendations from the oversight report are extremely relevant. I don't know that we have to fully recapitulate them. I think it's important to say these things are very specific to them. That would be short-term. In the medium term I am resonating with son of the voice -- some of the voices to sigh there's some unique issues with direct-to-consumer that do deserve more study. The problem that I think we will encounterer is how much data is out there. I think in the long run it will come down to a lot of gut feeling about it. Perhaps a white paper that highlights the issues about what do we know and not know? And what are the existing standards around research where maybe these are falling short. Perhaps it's worth additional investment in time. That would be my recommendation, to go forward with the things that we know well that are relevant relating to the genetic testing of it and the oversight of that. And make a more tailored document relating to the more unique elements of direct-to-consumer.
Jim?
I think maybe we can reconcile the old with the new by taking a page from the discussion we had yesterday. I think that perhaps would we ought to do is draft a very short document, a one or two-page document, that says something about how DTC is getting a lot of attention and we are concerned. We're including as an appendix some work that the group already done. Here are some things we feel need to be on your radar screen, maybe four.
[ Overlapping Speakers ]
That's right. That's right. And we could -- I suspect pick a few of the things around the table, some of which have come up, that rise to that level. I would put out two things: To me clearly the most important issue in the whole arena is reconciling claims with reality. It could rise to the level of here's a bullet on that first page. I would expand a little bit from Marc, I don't think the issue is so much genetic testing as it is medical testing. If people want to get their ear wax type be my guest. But when they are doing the [ Indiscernible ] mutations for breast and ovarian cancer and then claim this is not medical testing that's clearly [ Indiscernible ]. We should pick a very limited number of such things, put it in a front piece and then say here's stuff we've done that address this.
You are suggesting the short letter, the previous work, and then taking the paper and expanding it --
A short front piece that says here are the three bullets that rise to the level, and attached is also work the committee has done and now extract it from prior work that address this general topic.
Those would be the recommendations part. The front part of the paper is the describing the whole area --
I would say have it all preceded by a one-page document with a brief preamble that says here's issues that rise to the level. Here's what extracts the past. All I'm advocating is overlayering the whole thing with a summary that has a few bullets we can decide around a table in short order that rise to the level of look at this. I suspect most people don't read after the first page.
I would be interested, too, to see what sort of recommendations they would be. If the biggest issue you see is the definition of testing.
And what the claims are.
Does that -- all of these tests should be run through CLIA certified labs. The next thing is our recommendation of rather saying -- they should be calling them -- here's what HHS can do. They can tell CMS --
[ Overlapping Speakers ]
Right.
CLIA certification corresponds to analytical validity. Whereas reconciling claims with reality gets to the oversight of the FDA, et cetera.
Be more specific like that, that's my point. We have all of the agencies here to give us input on what they can do, what they have been doing, what they could do and really assist them in getting attention for the efforts. But also define them towards direct-to-consumer advertising. We have a new Secretary and staff. There's a lot of publicity about these tests where there's publicity when you have prenatal testing. I think it's important to have the report part to define that for staff and others that want to go back in and delve. Particularly highlighting the work of the committee from the past because that's a lot of work. We've identified issues that you have identified that are important and perhaps we can hone in on several of those and say we recommend that you have some focus on this, you direct your agencies to focus on this sooner than later. These are other things that could apply generally.
Alberto wants to jump in.
I think that defining medical devices will be helpful. That puts the own Russ on the agencies that deal with them. It also may be good to perhaps let the Secretary know there's issues as to what laboratory developed tests are and are not. And what the different agencies are doing them that need to be dealt with. It is public there's a petition for us to deal with the tests within the FDA. That's something that the Secretary can look into and deal with as part of the issues that need to be dealt with.
Scott --
One particular strong point of the report that I think would be good not to be lost in terms of emphasis is that it does a good job of delineating personal and clinical utility. We found those two things are often confused. I just thought that was a strong point in terms of the education point.
Paul?
I wanted to voice my support for something along the lines of what Jim and Sheila were arguing for. I'm not aware we've ever decided that direct-to-consumer testing was a medical device. I have lots of concerns about that. I just want to be clear on that as a member. Two points, one is that the report -- one of the things that distinguished direct-to-consumer from other kinds of medical testing is the role of the expert in ordering the test. And that's not -- that's not addressed in this document at all as far as I can tell, maybe I missed it. It's a key distinguishing key characteristic. The direct-to-consumer folks says it adds to access and empowerment. We might say something about that difference, it's an interesting issue for study, frankly.The second point that I wanted to make is around the issue of privacy and protections, so-called protections derived by direct-to-consumer access to testing. I think it would be valuable to have a box or opinion as to whether in fact there are any real protections derived by ordering a test through a direct-to-consumer pathway that are different. As I remember, I studied this a few years ago, if information is subpoenaed they have to produce it. Basically they're governed by the same laws. That was my impression. We ought to say something about it definitive about it in the report.
Okay. These tests have clinical utility are medical tests. Is there agreement about that?
A subset are.
The ones that have clinical utility.
I don't think you need to say -- there's many of these tests that are clear medical implications.
Right.
I would suggest that you say that they make medical claims. That's what you want to say.
Okay.
[ Overlapping Speakers ]
They can claim they don't make claims but they're making claims.
[ Overlapping Speakers ]
Risk reduction.
Exactly.
There's no way you can --
You can reconcile the offering of high [ Speaker/Audio Faint or Unclear ] testing with the statement at the bottom of every page that says this is not medical advice that is not recommended to --
I understand.
They're just incompatible.
They also do testing that is not medical.
I understand. I want to make sure that everybody in this room is on the same page with this. That's a powerful statement that we have not made before. That gets us into these other things that they need to have the same types of oversight. Then we can get into the unique characteristics. Is that where people are?
How about the testing for vitamin use?
Making a health claim --
Do we have access to the NIH counsel's office? I think it's important to -- if we're starting to create new wores or definitions, what does that mean in terms of the framework that exists? I don't know we can -- if we're trying to recommend we parse these companies and say here's what we're going to say you should define as a health claim versus this. Are we trying to say these tests in general should be -- should be performed in a CLIA certified lab? What retrying to get at?
We're trying to limit what we're addressing are the tests that make medical.
We're not trying to create terminology. What we want to have rise to have very prominent position in our recommendations is --
This conference has less than three participants at this time --
[ Overlapping Speakers ]
And what they're actually doing. I don't think we're invoking new terminology.
I think would we're saying is the standards for the DTC, when you are making a health claim or indicating value in the health sphere need to be as high as for when they're done in the clinical ee ree in a. -- arena.That intermediary is gone, they're less capable about making a judgment about the test. We need to assure --
Differently enabled I would say.
We need to provide, make sure that the information available to them is at least good as what you would have in a clinical arena.
That doesn't mean there's not concerns when you do ancestry testing. They can still hold your information and sell it or whatever. It's just we're trying to draw a box around would we want to make recommendations about, not the ancestry testing. They do have concerns. I think Paul had something.
Thank you. I think what Jim is trying to have us do with the process of coming up with the one-page three-bullet memo is address the questions that people around DTC that are not addressed here, that crystallize the things on people's minds. This issue is one of them. My concern is we could all sit around the room here and generally agree, but it's a fairly important decision and things will flow from that decision that we make that will have consequences that will be fairly significant. And my concern is that it's worth taking a step back and having the working group look at this in detail, look at the legal implications, because while we may agree sitting the around the table it's such an important decision that it's worth having the working group look at it in great detail, look at the implications and bring it to the committee in some format with better documentation to make an informed decision about the implications of these kinds of central questions. I'm concerned that sitting around the table talking will not get at some of these concerns.
No.
I would just say -- I understand what you are saying. What I'm trying to advocate though is if there are certain subjects that we all do agree on in a way I'm not sure whether all of the implications and mapping them out and spending three months doing that is worth while. I think that there are certain aspects to DTC that rise to the level of obviousness such as the RCA testing as a meldcal testing that we don't need to spend three months on. It might be worth -- putting this out there -- highlighting those things that we all agree rise to importance without spending months on it.
You will not provide of guidance on how to deal with it. We're talking about what is included in your box. How do we identify which are clearly medical tests? And which are maybe medical tests? And which are recreational? My concern is that we do this right. And the implications here not only speak to the DTC community but also to the utility of this group. We have a really great report that took a lot of time and thinking. My concern is that by sitting around the table we will overshadow anything in this report that was considered over a few months by a decision without a more formal process. I'm not a big fan of waiting for anything in general. I think this is an important decision that is going to have implications for a variety of agencies and we need to do this right. And members of the committee have the background information that's been vetted that has been articulated well.
What I would say -- I want to do it right, too. The decision then around the table is I would phrase it as are there are issues that we can agree on that don't need months more? Or not? If not -- if we're happy with this report then so be it, we go ahead with the report. And perhaps -- or delay it and do more things. Again, I want to throw out for the consideration of the committee are there some things that rise to the level where we might want to say to the Secretary we have concerns about XYZ, I would throw out there that emphasizing there's a need to reconcile claims with reality does rise to that level, but I'm just one member of the committee.
You have to say more than these are concerns. The Secretary knows the concerns.
She does not.
These tests have not necessarily been considered medical tests. This is a significant change for this committee to say they are medical tests, when they deal with these medical issues. And need to be -- have the same kind of oversight you would for other types of medical information. That's the core. If we can get there today and get agreement I think we can get it back, and put this a page or two, highlight some of the other things that we have done, but keep it fairly focused. This would be a substantial change. And doesn't require a lot more research, if you will, for us to make a statement they should be considered in that context.
This would narrow the medical tests. We would explain --
This is a set of tests that are offered directly to consumers. Those that Jim just described -- that's what we're talking about here.
Perhaps a little history would help here. About two years ago when these tests began to come into the market, this is public, they came in and spoke with the FDA because the FDA wanted to know what kind of claims they were making. Most of them were [ Speaker/Audio Faint or Unclear ] were not medical claims. Now things have changed since then. Claims seemed to have changed. The tests have changed. That is on the record that they claimed these are not medical tests.
Do we have consensus on what a medical claim is?
Would we need consensus is are they performing some medical tests? I think the answer to that is obviously yes.
I can see us saying we want one standard for medical testing, but I think also need to be clear is there other testing?
Yes. We could say ancestry testing is not medical testing. BRCA is medical testing.
We can say that the gray area --
[ Overlapping Speakers ]
I have Marc, Phyllis, we have one minute.
I just would endorse that I think we need to move for. We've discussed the medical test issue. I don't think we need additional work on that. These need -- we need one standard. These companies are performing within their suite of testifies some tests that are clearly medical.
I want to address the point I think there might be some confusion on, that's that when we talk about DTC we talk about very, very big range of genetic tests offered to consumers without health providers. What some of us are talking about genome scans being done. These are two overlapping but not necessarily different arenas. There may be some discomfort in making a broad statement about what is medical -- you know it when you see it.
The point is that these whole genome scans, I agree, they contain many different things, but some of them are medical.
I agree with you. But if we're talking about specifically that realm of tests then we need to specifically say in terms of whole genome scans this is what we're talking about.
[ Overlapping Speakers ]
Those -- the subset of tests within these suites that rise to the -- to a level by which one would call them medical testing.
Agreed.
I would add medical and behavioral.
Health-related.
Yeah.
Okay.
I want to get to the next step of that. What does that mean? I think Paul was getting to that. Are we saying there should be a single standard? These testifies should be held to the standard of --
Yes.
It's not as helpful to just call them out and say everyone knows that you are making a medical claim and you are saying that you are not.
[ Overlapping Speakers ]
We could have a whole report.
Let me just get a --
[ Overlapping Speakers ]
I think we've gotten to a core set of issues. These are health-related tests, they should adhere to the same standards as if used in a clinical setting. And we can work on a relatively short document, a page or two, that will highlight that, refer back to what we mean when we say oversight. I think it's important -- a lot of work went that this, we've come a long way in this discussion, it's been constructive. I want some agreement from this committee that you are comfortable if we bring something to this group in October there's a Jen consensus. How many are on the same page with that? With a two-page report that says when they're health-related tests, they contain medical information, they should then have the same type of oversight as those that would be used in a med dal environment.
We wouldn't look at that until October.
You will get a chance to see it in October.
But it will go out before then?
No.
Okay.
We'll spend the next few months getting it in shape. I don't want to bring it back and have people say I don't agree these are medical.
We will say if they make health claims they should be held to the same standard --
[ Overlapping Speakers ]
They may not be making the claims. If they test for things that are medically relevant.
We'll have the task force come up with a definition.
That's the point.
It's a combination of what you raised earlier with creating an executive summary.
I'm happy to help. Since I'm the latecomer adding more work.
No.
It's unfortunately that Barry is not here this morning. It would be interesting to get information from him. Maybe we can circle back from him.
Barry --
From CMS.
They're looking at this area as well.
We dealt with a lot of those issues in the oversight report.
Is there anybody that has a problem with that general approach? You will see it again, you will have a chance to discuss it.
Steve, not a problem. Does it need also a focus on privacy, security -- in addition to that? Or will just by calling these clinical medical tests give us enough framework? Yesterday's discussion was really focused on that. Do we all sort of leap to those very great concerns?
It depends on how the testing is done.
I think when talking about here -- we'll need to get this back to a committee to work on. The oversight protections should be the same as in the medical arena.
[ Speaker/Audio Faint or Unclear ]
If the company -- HIPAA might not work.
We need new policies.
Yeah.
Do you want to expand that portion? Are we expanding the report at all with some of the other concerns?
I'm trying to figure out whether there's one over overarching theme. I didn't know if we wanted to include that.
I think it's implicit. We will need to work it through. We're saying they're medical basically. They're not just recreational.
If we say these are medical testifies then HIPAA comes into play.
Exactly.
[ Overlapping Speakers ]
All these ideas of selling the data -- a subset of information --
Clinical validity --
[ Overlapping Speakers ]
That will naturally follow.
You are probably right. We need to indicate what are the things that follow from that recommendation.
Right. That was my point from earlier.
To go back to the question -- are you wanting us to add new recommendations? The paper does discuss the problem with HIPAA. These companies are not a covered entity under HIPAA. Are you suggesting that we should also include for October new draft recommendations. We recommend that the entities should be covered unHIPAA, that's just an example. Between now and October are you also asking the task force to come up with new recommendations? Or do you just want to go with the paper that we have with the preface in front of it addressing this -- the medical claims -- medical test issue?
I want to make sure -- we have to take it back and really look to make sure that the appendixes really are germane. We can do that --
Right.
I want to make sure -- we have to move on. Are there substantive problems with the general approach, with the general statements that we've made? Hearing none --
Can I just clarify the scope. We're not going to do new stuff. No new recommendations.
This is a recommendation about this is medical testing.
[ Speaker/Audio Faint or Unclear ]
It came up that we should have a bullet about privacy, we could come back to the committee with that, too. It's not that we would be offlimitted from considering any of those things where we have concerns that we thought might not have been addressed.
But the committee is asking you to go back and make a recommendation around medical testing issues.
I get that.
Therefore it means deliberation in the group, more work and bringing it back for consideration and approval by the committee.
This has been great and helpful. The committee has done a huge amount of work this a short period of time. I think we'll be able to build and use what you have already done. We'll bring it back here for lively discussion the next time.
Steve, can I make a quick announcement? Several folks here were involved in a workshop in December on the scientific foundations. Those recommendations will be published in Stennistics & Medicine. Those results will be published in August in Genetics & medicine.
Next, clinical utility and comparative effectiveness. The purpose of today's session is to get us all to a common foundation of knowledge and understanding. The speakers will help us to understand what is going on in this rapidly evolving landscape and will highlight issues around genomics and where it fits in. There's lots of things going on, in particular ARRA allocated a billion dollars.There's significant resources going into this. ARRA has allowed the Secretary to contract with the IOM. We will hear more about those later on today. We will hear about that later. There's also creating a federal coordinating council.
Lots going on. What we will start with is where we are, definitions, then we will hear from some of the people that are shaping this environment. Gurvaneet Randhawa has been deeply involved with the issues as they relate to genomics for a long time.AHRQ has played the lead role up to this point, so Gurvaneet. We've eaten into your time. But you are a very efficient man, we look forward to hearing what you have to say.
Can you hear me now?
Sure.
My charge is to go over clinical effectiveness, clinical utility and comparative effectiveness. It's a fairly large set of issues, I can't go into them in any depth. I hope to give you a flavor and set things up for Dr. Sox to take it from there. Effectiveness, many good things come from Yogi Berra, I don't know if he said this or not. You can find this quote on the web. What is translation research? There are many steps involved in moving from [ Speaker/Audio Faint or Unclear ] that's been shown to work on the bench to using it in clinical practice. There are three major areas moving from the preclinical science to clinical efficacy, moving from efficacy to effectiveness, and moving from effectiveness to implementing programs and using it in practice.
What is the difference between efficacy and effectiveness? Whenever we perform tests or offer therapies in the average clinical practice you don't see the same benefits and harms that you would be expecting from efficacy studies. The big question is -- why? There are many patient factors that can influence effectiveness certainly. The foremost is biology. I think it's a part of it. Also the person's age comes into play. The sex of the person, the comore bidties, how does that change the effectivenessiveness? The disease has an impact, and of course genetic vary variations. Also the adherence to the drug therapies is important. Of course, drug/drug interactions that do occur that were not intended or studied in the efficacy trials.
Some of the other factors, I will highlight an actual history, this is a very foreign issue. Do we know the natural history of the disease? This is often where some of the controversies arise.There's also the related issue of surrogate versus health outcomes? What is really being studied? More often than not it's surrogate outcomes. When studying surrogate outcomes we need a good indication there's a good link to the health outcome. I can give you some good examples where lowering blood pressure in patients with high blood pressure were surrogate outcomes that the task force felt good about. But lower hepatitis C [ Speaker/Audio Faint or Unclear ]. Apart from the patient perspective then there are issues with the provider, the skills and the training of the provider and their experience. How many have you done? What kinds of patients have you done them in? There's provider preferences on devices they implant. What is the coverage and reimbursement? There's issues about hospital, or maybe health system in general, what kind of a hospital it is? What kinds of facilities are available? I will give you an example of warfarin to highlight these issues for you. In warfarin we know that it is an effective drug.It's one of the most commonly prescribed medications in the U.S. But it has a narrow index. In this case the effectiveness of the drug is measured by looking at INR. Which tells you the amount of anticoagulation in a person at that point. If the INR level is too high there's a risk of bleeding events. If it's too low you are not really reducing the events for the future. The challenges are how well do we monitor a patient's INR? Often drug/drug interactions, diet interactions, and adherence. As an example of personalized medicine -- there's been trials in pharmacogenetics -- can the patient do their own INR monitoring? There's been studies showing if you do weekly monitoring about 80% of the patients will be in the target INR range. If you do it only monthly it's more around the 50% range. The question is can the patient monitor their own INR at home? There was analysis done in 2006 that looked at 14 control trials, 2 in U.S., 1 in Canada, the rest were in Europe.Here's an interesting result of the outcomes. What was found in the studies is for the people who were monitoring, SM is self-monitoring, there's an increase of people that have INR in the target range. The studies were reporting this differently. All 11 of the studies had trends in the same direction, and six of them had similar results. The recent coag trial had patients in the same range.
More importantly, this analysis showed there's a decrease of events in these patients and fairly impressive decreases. How do you distinguish the effectiveness from efficacy trials? We had a report three years ago where we came up with criteria that can be used when a systematic reviewer is looking at studies to see if a study is an effectiveness or efficacy trial. Is the patient population in a clinical setting or a hospital setting? The second is the stringency of the eligibility criteria. Most of the trials have fairly stringent criteria. Health outcomes -- because of the time spent on the trials most of them do not have their own health outcomes they usually focus on the sur gaycy outcomes. The other aspect is the length of the study. Again, it takes time to identify long-term effects. The trials are designed to do that. Another criteria is the trial assess the adverse events? Another one is sample size -- is there enough of a population to identify the outcomes? I actually think -- yes -- there's a different slide set that I created. I think this is the older one. It's okay. I'll ad lib. What wanted to do was move on to utility from effectiveness. There is confusion in the field when we say clinical utility. What I want it get across here there's a term called [ Indiscernible ] that is used in the health services field that looks at a patient's preference. If you are in perfect health your [ Indiscernible ] is 1. If you are dead it would be 0. There's different ways of assessing utility.
What I wanted to get at is the utility itself is an outcome measure. It can be used to compare different interventions, or to derive life years and disability life years to compare the outcomes of different therapies or different treatment choices. Where there's confusion in the field is talking about clinical utility. It doesn't seem to be outcome, it's a decision. Looking at the e-gap wording, a plug for genetics in medicine, the January issue had several papers on e-gap. There was a paper on method. It looked at effectiveness and net benefit in their definition of clinical utility, although there the working group also said to consider efficacy sometimes. The examples included health outcomes, [ Speaker/Audio Faint or Unclear ], improved adherence. Like I said, the clinical utility is not the same concept as the health utility. It's more of a decision. I will skip this.
One point I had wanted to make in my slides -- the different slide set -- was that there are different factors involved in decision making. The evidence whether we get it from efficacy or effectiveness trials and the benefits and harms are only one part of it. Another part is the added value. If it is something new does it provide new benefits and harms compared to something old? Costs, cost effectiveness could be part of the discussion. If you are thinking about individual decision at point of care, patient and provider preferences -- these are several other issues that are coming into play. It's just simply just one-on-one looking at the outcome.
I have discussed effectiveness. I will move on to comparative effectiveness now. The issue about comparative effectiveness. What are we comparing? One is a list of clinical interventions, it could be different tests, it's not just labs or imaging, it could be screening protocols or check lists. I'm using the term fairly broadly here. You can go on. There are many different types of interventions, sometimes you are comparing one versus the other or sometimes you are in the same class. Some folks are defining [ Indiscernible ] to include healthcare programs, delivery systems, one can make it broader. The only challenge is the more broad you make the definition and the study design the harder it is to tease out the factors that are leading to improved outcomes. The other part about comparative effectiveness is what are the methods? How do we get at the information? There are some issues about the study design, I'm sure you will hear about that later from another speaker, we have a fairly robust tool kit if you can say that, for studying outcomes. We need to do some tweaks. Having more head-to-head trials. We have established these are superior methodology already. [ Speaker/Audio Faint or Unclear ], modeling, meta-analysis, of course we need to work on analytic techniques that minimize bias and con founding.
One point I wanted to get across is there is some confusion that any evidence-based decision making equals randomized control trial, one is not the other. The e-gap working group has the principals of looking at the magnitude of net benefit. How much do the benefits outweigh the harms? And the concernty of that.The task force has been recommendations on [ Indiscernible ] and [ Indiscernible ] screening, there's no randomized scroll trials on these. There's an EPC report recently, it's an AHRQ program, which looked at different treatments for obesity and they based their conclusions on surgery is very affectively for more bidly obese people based on a study in Sweden. Surgical methods led to reductions in weight in excess of 44 pounds. There was no randomized control data. The magnitude of benefit was so much that it's difficult to explain that with confounding and bias. Those things are not seen too often in our experience.
I will briefly go over what AHRQ has been doing in this area. There is comparative effect was research at AHRQ. We've had a program started since 2005. Congress had authorized that AHRQ should do this research. The goal of this program is to provide the patients, the clinicians and policymakers with reliable evidence-based healthcare information. The effective health program looks at these items for the Medicare, Medicare and the SCHIP programs with a focus on what is known now and building on the previous experience of the gaps in the evidence and where AHRQ can fill the gaps. The focus is on clinical effectiveness.
The framework of how the progra is organized is there is an [ Indiscernible ] through here. There's a stakeholder input in all different phases of the conception framework and the first step is doing a horizon scanning, trying to figure out the evidence needs that need to be methane filled. -- met and filled. Then the decision is made at AHRQ on what is the next step? Do we need to fund a study to create new evidence? Once that research is done the next step is disseminating that information into practice. There are also research creating and career development activities. A couple of years ago we reduced a study about different treatments to prevent bone fractures in people with osteoporosis. These are executive summaries of what our EPC program creates, which we call CERs. These tend to be fairly technical. We go the next step of trying to create some clinically useful products. There's a clinician guide and a consumer guide that tries to make this information available in the concise actionable form where information is communicated.
[ Captioner Transition ]
All of the added value of these tests to our ongoing interventions. And we have heard in the previous sessions about how with the increasing life span with an aging population with the increase of obesity and new technologies, that the health care system -- the health care is becoming more expensive. Genetics is part of this. I have mentioned before the side projects on producing your outcomes and those kind of things, clinical support; there is some that you are doing, but we need to do a whole lot more. I will end there.
Thank you.
That's great.
[ Applause ]
You are going to be here for the today, correct?
Yes.
We will be asking questions of you as we go along. Thank you. These are of the few things that are going on right now in the White House. This will provide some of the solutions to the health care costs. The work is getting cranked up, and one of the people who has played an enormous role for many years is Dr. Harold Sox. That group is about of the error funds. He has earned his medical degree from Harvard, and has continued in other various places. We are getting to the last month of the tenure.
We were hoping that you would be able to talk to us about the comparative effectiveness agenda, and how genomics may fit in to all of this. We did send a letter to the House on behalf of the committee; again, noticing the importance of the agenda. It's always wonderful to see you here Harold.
Thank you Steve. So I'm -- I want to say first that everything I am going to say today is in the public domain. The reason for emphasizing that is due to the medicine reports. They are embargoed until they are released. So I don't want anybody to interrupt anything I say as reflecting the content of the report. Everything is in the public domain, and I will try to be as careful as possible. CER, comparative effectiveness research. It's really thrilling to doctors. They are focusing on making better decisions. I really can't think of a program of research that has more of a focus on something that is so important to the physicians as well as the researchers who work in this field.
Steve has already said something about the AARA, and the role of CER in it, but the only thing I would add is that the funding time line is that the money has to be obligated by the end of next calendar year, although I gather it can be spent considerably longer than that. We are not really limited to short-term studies. On the other hand, I would like to have the short-term studies get done and get finished. I would like to build a report for this type of research.
Now, the definitions, I think, are really important. They tell you what is in. That is what can be if you pleaded with the CER funds. So our committee has spent a fair amount of time trying to inflate the definitions that are out there into something that the short and sweet and it covers everything. Our definition is two sentences. It's generation and synthesis. That is the research as well as using the research that is out there already. The evidence that compares, comparative effectiveness that treats and monitors as well as promotes the delivery of care. There is a broad field of topics to be included in this umbrella.
The purpose of the CER is to help the researchers, physicians, and policy makers make better and more informed decision.
Let's briefly talk about what is unique with the CER. It is unique because it involves all five of the characteristics that are here. I have circled the first three, because I think that is most important to keep in our heads. The first is the direct head to head comparisons of the alternatives, treatments or tests, whatever, any of what might be the standard of care. The study of the population should be the representatives of the clinical practice. Third, it should be patient-centered. In that it should help the patients and the physicians make a choice of the specifics characteristics of that physician. It's gathered by the physician and then it is offered by the characteristics. It's including the delivery of the health care, the translation and the services of the practices and the broad range of the beneficiaries. I want to talk about the patient-centered concept. Let's suppose that we have a randomized trial saying that treatment A is better than treatment B. 60% of the patients respond to treatment A, but only 50% to treatment B. Since 50% of the patients responded to treatment B, it's clear that it is by no means in the near substance. If all you knew about the patient was that they were like the patients in this trial, then you should prefer A, typo --
[ Laughter ]
You were paying attention.
[ Laughter ]
Is it possible that some of the patients actually should have chosen B despite the fact that most of the patients got better care in A. Can we steer them in the direction where they are most likely to respond to. That is an intriguing research question that I believe is an important one in the agenda. That is my personal view. I am going to try to give an example of the principles of the CER, comparative effectiveness research, to the genetic testing for diabetes and susceptibility, and I made these slides last night, and in through a rage of madness, I didn't include the medicine. This is an April 21st issue for those of you who want to follow this. I want to pick up the mess that I have left on the analytics side so I know I am safe when going out on a limb.
Here is the information. They have identified a number of low sides that are associated with the type 2 diabetes and the number of SNIPs associate d with the low side. The purpose of this study was to examine the side effects of the low side and the conditional diabetes and their risk factors. In other words, it is comparing the risk factors and predicting who was going to get the diabetes with the combination of the cost conventional risk factors. What genetic information is added at the margin? Clearly, that is a CER question.
So the study which was done by a group that was mostly based by the women's hospital at the Harvard school of public health predicted that the onset of diabetes taken by women taken by the women's study cohort, and then men was taken by the follow up study. These were a I agreed to give money for -- give blood for the tests. During which time, the participants were contacted by the study every couple of years to see if they were reporting the onset of diabetes. The exposure in this case controlled study would be the genetic low sides and the SNIPs and the conventional risk factors. So the goal here then is to calculate the odds ratio for the exposure. In other words, this is the frequency of the SNIPs in cases versus control and by a wonderful mathematical equipment in the odds of having diabetes around giving the ex -- and giving the exposure versus no exposure. You can learn that yourself with the mathematics you have learned as a freshman in high school.
So the risk factors are examined and including BMI, physical activity, and energy intake, and they have done dietary assessments in these processes periodically. They have done a genetic risk score. The more SNIPs you have, the more the risk score. The goal then was to have a multi-variant model to predict diabetes risk. Here are the main results. They have divided the participants in to Quinn tiles -- quintiles pertaining to their risk scores. There is a risk score for the patients with diabetes. There is a nice dose and a response curve. So the higher the genetic risk SNIPs score, the higher the odds ratio. This was importantly adjusted for a number of the risk factors for the diabetes. So it implies that the presence of these SNIPs make an independent contribution in predicting the diabetes incidence over and above the risk factor. So far, so good. Now, we go and look at the ability within the information to discriminate on the persons who will develop diabetes and those who won't. To do that, we have calculated the area under the ROC curve, and that is not shown in the next slide --
[ Laughter ]
Believe it or not, I couldn't retrieve the figure from my own computer because I didn't have the sign-in to repeat this stuff.
[ Laughter ]
Yeah, it's crazy.
Four weeks to go, I may still do it.
[ Laughter ]
Those who are going to develop diabetes will have a higher score than one who is not destined to develop diabetes. The risk fact is .478. Those who are destined to develop diabetes with a higher score is almost 80%. If you add in the genetic risk score, it is .79. It doesn't make any clinical contribution to discriminate against those who are likely to develop diabetes and those who won't. It is likely what will be a part of the program for the behavioral change as well as the [ indiscernible ] Why does it add discriminatory power? That means that the genetic factors are influencing the diabetes risk through the conventional risk factors, and in that they don't add any information. The prediction is so good with the risk factors that the genetic information can't add much. And the third project, which may be the best -- possibility, which may be the best one of all, is the poor curch which is part of the dis -- poor curve which is part of the discrimination. There is a risk theory which is called reclassification which is enabling the capabilities of the jurisdiction and prognostic tool and it will move someone from a high risk to a low risk. These are the better measures of the diagnostic tests. We are going to see more of these reclassification Indies. indice -- indexes.
The NRA mandated a study by the school of medicine which was 19 weeks after the President signed the Bill into law. It was to include the recommendation of national priorities for the CER. That was for the conditions and the research directions to be addressed with the CER money that you have heard about earlier. In addition, they have mandated that we consider the input of the stakeholders. We are building on the experience in Arc. We have held an open meeting, we heard from 56 presenters for 6 hours. And we had an opportunity to ask questions of them, and it was a highly satisfactory meeting and it held with both the audience, the ones who were on the commit etee as well as the ones who were not, and it went quite well. It is really rewarding when you come through with a nice and good warm feeling.
It was open to anybody, but it was mostly with the health professionals and organizations, and it was also from health professionals who have made suggestions. We asked them to give a speech, and we had 1000 unique respondents and over 2000 recommendations.
Here is some of the criteria which is outlined because this is where we ask the nominators to identify as one of the reasons for them making their nomination.
In addition, we have paid a lot of attention to get a balance portfolio of the topics so we didn't leave any important areas completely high and dry. And for that, we have developed several criterias for trying to balance our portfolio, and we are paying a lot of attention with that during our discussions. The next part of this is the report standards which is in the review process in the national research council and the national academies, and we are hoping we will be able to deliver our report on time in a couple of weeks.
Now, I am going to turn to a question in which a lot of people are wondering and that is: In health reform legislation, will this be here, and if it is, what form will it take? And to do that, I turn to the important white paper that was issued to the finance company several weeks ago. The language here is the language of the report. So, first, it says that a number of respected panels have called upon Congress to create a national entity to conduct the research including the one from the institute of medicine in which I participated.
[ Speaker/Audio Faint & Unclear ]
Pardon?
[ Speaker/Audio Faint & Unclear ]
Oh, it is? Good.
It goes on to say that it is identifying the most pressing gaps in human knowledge. So from that language, you can imagine that something new is going to happen. It needs to be private, non profit, and it will include both the private and the public sectors. It will include an entity for the potential influence on the development of the national priorities. This is what the senate finance committee was thinking about. And in an address on the [ indiscernible ], Senator [ indiscernible ] reaffirmed his thoughts on this. It should not only produce inquiry, it should produce research. It should be part of the contract to have the inner agencies available in your office to have it set up to issue the question for the proposals and to evaluate them and then to generate the reports based on them. It is also having the flexibility of dealing directly with the private researchers as well as through the government agencies. Very importantly, this institute should be open to public interest and transparent in order to maintain the integrity of the research. Just as this body is open to the public and is functioning entirely out in the open.
Most importantly, this should be part of the rigorous oversites of the finances and the trust. It needs an adequate and stable source of funding. And since the research is going to benefit all of the Americans, it would seem reasonable for the finance committee to levy a small assessment on the insurers as a way of insuring a steady flow of dollars in the annual appropriations process. That is what the finance committee has in mind.
Finally, just a word about the public attitudes towards the CER, Scott Gosley who was a deputy of the NEA, wrote a negative article in the Wall Street Journal which emphasized the harm of doing better research.
[ Laughter ]
He was echoed by Limbaugh.
This is the part to reed. This is the statement that the respondents were supposed to react to. You can see, basically, that a total of 73% favored or favored very strongly this statement. Only 17% were against it with 10% not being able to decide. Interestingly, they have framed the question two different ways and they have assigned them randomly to the respondents. In one of the versions of it, it had costs to it and in the other it didn't have costs. Maybe this is reflecting the fact that people didn't read it carefully, but it was the same whether or not the cost was included in the framing question. So I will end by resitting the -- restating that the promise of CER is to help patients, organizations and doctors, physicians make better statements.
One or two questions for Harold. This is terrific. And then I hope you can stay. We hope to have more discussion later.
Jim?
I just have a quick question. What arguments do people make against this? I am trying to think of some, but I can't.
I can't either.
[ Laughter ]
Make a call in to Limbaugh.
Yeah, that's right.
Congratulations. As you mentioned on Tuesday, Peter Orzig believes that the comparative effectiveness that is done right will be bending the key role sustaining the costs. Of the thousand people who responded on the survey and the 2000 ideas do the genetics rise high in the domain of what people want to look at, or was it more likely based on the public hearings with the common and costly cardiovascular disease.
I can't answer that.
Just another point. The cost, people are using the issue of costs, and not looking at the cost, yet creating the concern on the very politically right and the political left, actually, they are concerned that this will fly in the face of the personalized medicine and it will lead to the rationalizing of the care. You are as knowledgeable as anyone in this space, do you think that is a concern? Not what the public thinks, but do you think it will actually cause that harm?
Well, now that I am speaking personally, and the short answer is: We clearly need to know about the value that we get for the resources that we are expending on the patient of care. I work for the American college of finishes, and I have issued a physician paper, which we published, and it came out strongly for the cost effectiveness, and that has come out. Everybody knows that the word cost and cost effectiveness is really toxic in this town, so we will have to see what happens.
I had a quick question on the reliability issues. Have you heard of any concerns, expressions, the product A which is better for this individual statement, I guess, there is a -- [ Speaker/Audio Not Clear ] that might expose him or her to that reliability? Is it more limited to the particular sub-group or the particular patient, and is that factored into the comparative effectiveness protocol?
Well, I am actually embargoed from saying anything about the process that we went through in our discussion. I really can't say whether that issue came up or not. That's part of giving the diagnostics services. It's surprising how little research you see on that subject. You know, we don't see much of that in our journal.
Go ahead and we will take a break.
I have a question for you. You brought up the important issue of the entity, and the fact that it is not part of the public entity because of the fear of the political influence. If you put it on the private sector, it is making it a private component, but it is founded by the insurance company, would that create another type of potential influence?
[ Speaker/Audio unclear due to strong accent ]
What are you thinking of?
[ Speaker/Audio unclear due to strong accent ]
What leverage would they have? If the money that is funding the enterprise is coming from a tax that is -- that exists because it is a law.
But if they -- if they have -- if there are people on the report that has live events, then, you know --
Uh-huh. Well, the finance committee, as I remembered didn't say anything about -- I think they said something about the private and the public sector representation on the governing board. Presumably, there will be an open declaration of the financial relationships, and because of the meetings that will be occurring, just like this one out in the open with anybody to comment, and you can see people are pushing their particular financial advantage, it's likely that that will be leading to the role of making a decision.
[ Speaker/Audio Faint & Unclear ]!
I don't remember --
Part of it was federal.
[ Overlapping/Multiple Speakers ]
[ Speaker/Audio Faint & Unclear ]
Yeah, I think --
[ Overlapping/Multiple Speakers ]
The funding was part of the health plan two years ago which suggested this type of funding and it leads to the substantial financing. It goes out to the additional leads in the senate. It is one of the many funding sources. I think one of the themes of this is because everyone benefits to the pose that it is historically, you know, a government agency, and it may be more on the beneficiaries than the others.
Thank you so much. This is a terrific presentation. All the best as you move on through the next few days. We will be having a panel at the end, and we will be asking more questions with all of the speakers who can stay with us. If you have drafts, please get those to Sarah before noon so we can at least take a look at them.
You know, if you think of anymore discussions, get back to her; otherwise, we will go ahead and finalize it.
We will be taking a ten minute break, and we will be reconvene at 10 minutes to the hour. Thanks.
(The Secretary's Advisory Committee on Genetics, Health, and Society is now on a 10 minute break. This session will reconvene at 10:50 Eastern Time. Captioner on stand by).
All right.
Thank you, everyone. I know I cut your break a little short. I know we will be losing people towards the end of the day. We will get back in the swing. We have a lot to talk about. As we get into comparative effectiveness research, I'd like to introduce Michael Lauer. He has focused in the diagnostic testing and comparative effectiveness. We have asked Michael to talk about the perspective of NIH, it has played an increasing role here in the comparative effectiveness world, he can't speak specifically to the priorities in relation to the era moneys. Welcome Michael. We look forward to what you have to say.
Thank you so much for the invitamin A invitation. The impact of the stimulus Bill on CER, how the NIH activities on the CER Bill are organized and the opportunities and challenges of the stimulus Bill and what we have coming to us. First, the CER, speaking about and the need for the research, and there was a study where they went through all of the guidelines and the recommendations that was released from the American Heart Association, and the American Heart of [ indiscernible ] The energy of recommendations that are based on -- the number of recommendations that are based on solid evidence, those numbers are going down. Most of those are based on soft evidence. You look at the recommendations and you look at the ones that are currently active. You look at those and see what level of evidence they are on. You have level A, B, and C evidence. You have the opinion. You have the consensus, and the quote, unquote experted opinion. What was found is that 11% of the current recommendations of the cardiovascular are based on the evidence. 50% of those are based on level C. 50% is based on expert opinion only. Now, the NIH has a long standing history of the comparative effectiveness research. In fact, in this week's new Journal of Medicine, we have a new tried. It has new studies on diabetes and it has insulin therapies. There was no differences. It was just as good with the medical therapy as with the revascularization. This is a major comparative effectiveness study that has come out. The April 21 issue was study by NIH. We compare the drugs for schizophrenia. We have the upper right hand corner which is the screening and the usual care. This was a bill trial. They compared the screening tests with results of the deaths and cancer. We have the diabetes prevention project which compares a life style versus drugs. Life style has done a better job on the onset of diabetes. This is [ indiscernible ] for the defib raters. These are a small set of the comparative effectiveness studies which were funded now over many and many decades. This is screening versus usual care, and this for the prostate cancer. This involves 77,000 men. They were scheduled to get screening and rectal exams. There was absolutely no difference in the rate of death. Actually, the deaths of prostrate cancer was higher than those randomized in the screening. This is a huge comparative effectiveness study done by NIH.
Here is a smaller study. One type of the surgeries involves the bypass which has been done for a long time, and the other study is removing a portion of the ventricular wall and then putting it back together. This was gaining in popularity. In these two approaches, it turned out that there were no differences in the outcome. So the bypass operation will do.
So here is an example of the trial that we are doing right now and it directly hits on the genetics. This is the clarification of the anticoagulation. I want to go around and spray acronyms. Cardiovascular terminology is good for this. We have a randomized trial, looking at the patients, and they are being monitored for three months. The genetic test results are used to determine the dosing and the other will be based on the clinical algorithm. This is the differentiation of the [ indiscernible ], and then the other is the vitamin K and the reduction gene. It turns out that these two genes are fairly common, and they have strong associates between the [ indiscernible ] in response. We have a large infrastructure for doing the comparative effectiveness research. It has been around and developed for many decades. This is the clinical trial, operative network, agencies, and this is a network that is funded through the national cancer institute and through the NLHBI, and the data is extracted from the electronic records throughout these programs. You have the national library of medicine, research, CTSAs, the clinical transitional science awards, and these are relatively new over the last few years, and the idea of this is to bring in community collaborations of the research. There is a cancer surveillance data set. We have a lot of people with a lot of expertise in this research.
Now, in this new interest and the new legislation, we have had to struggle with the many definitions and how to allude to those. There is a lot of those. This come in at December of '07. This is the impact of different options that are available for treating a medical condition for a patient, and the study may compare the treatments for the comparative drugs and the treatments for them. I am showing you can exams of the studies -- examplesover stud -- examples of studies by that. This is put together with a new stimulus bill to oversee the comparative effectiveness efforts. The first time I saw on the e-mail that we were going to have to contact the FCC, and I thought, what does the FCC have to do this. I felt too dumb to ask. This is to prevent, diagnose and monitor treatments. There is a conduction of the research and there is a synthesis of the research. There is monitoring. This is to inform the patients, providers and the decision makers to find out what is the best decision for individual patients. It's the right treatment for the right patient under the right circumstances and settings.
There is a theme across these. There is is a valid comparison. We are comparing something against something else. The second thing is: The research is focusing on effectiveness. We are dealing with the real world, real patients, real circumstances, and real practices. We are dealing with real options. They are not options on their INDs, IUDs, or that it is highly optional and then nobody uses it. And then we are focusing on the real outcome. So real outcomes would include the length of life, quality of life, the prevention of major clinical events, and costs.
The stimulus bill has presented the government with a unique opportunity to focus their attention to comparative effectiveness research to $1.1 billion. The secretary is getting $400 million. Much of the emphasis for this bill comes from the congressional office that Peter put together. He loves to focus on the plan there on the right. I don't know how many of you have read [ indiscernible ]'s fabulous essay in the currently issue New Yorker. And he mentioned [ indiscernible ], Texas, which I have not heard before, and it is medically the most expensive town in America. The point of it is that there are huge variations of medical care across the country, and they do not appear to be related to outcome. Elliot Fisher have related this to the paper in 2003. And there is a variety of analyses after this that show the same thing.
The NIH in response to the stimulus bill has coordinated a committee. It is chaired by my supervisor and Dr. Richard Hoes. I am on that committee. We are in charge of a number of responsibilities everyone including on how we should -- including on how we should spend the funds, how to collaborate with sister agencies, how to put together the portfolio and analyses to see what we are doing, the type, and how we can communicate our spendings and our findings, how we can explain the existing and new programs, and then consider the long-term charges for N HR. We are seeing this as an opportunity to jump start a new pace of the CER, and it should go way beyond the two-year span of the stimulus bill. We plan to obligate the $2 million nor the support of a variety of activities.
What this means is: Over the past number of years there are a group of initiative grants that come in, they got good scores, but we were unable to fund them. We are now able to fund these grants. I was in a meeting yesterday of the coordinate committee and we went through the number of grants that we will be now funding. The second is the grants and the contracts and providing them with additional money. And this is a small part of the spending plan. Challenges and opportunity grants how many of you have sent in a challenge grant or you know somebody who sent one in?
[ Laughter ]
Okay.
How many of you have missed meetings because of that?
[ Laughter ]
Okay. The challenge grants are two year $1 million opportunities in a variety of areas, and one of the specific areas was CER. We have received $150,000 in the challenged grants. We are in the process of reviewing them and it's going to be a busy summer, the second big area is the grant opportunity grants, and those are two year grants that are more than $2 million, and we have initiated that in the comparative effectiveness research. I know in NHL BI, we have received about 50 -- that's an incomplete count.
Many of the trials are funded by contract. We will be exploring in the next two years areas where we can award those trials. Now, there are a number of challenges that the stimulus bill has presented. Scientists, even highly driven scientists they are not use to the two-year timetables. The rapid timetable has become interesting to us and the scientific community. One of the worries that the community has is what is referred to as the cliff. And that is what is going to happen in two years when this bollus of spending is going to end. There is a political contract in which all of this is happening. You have heard this this morning. There is a question of the economic impact, and that is the economic impact of the stimulus funding. And we hope by providing this to the researchers, small businesses, we will be creating or retaining jobs. There is a question of the economic impact of the comparative effectiveness research. Some feel this is going to be the answers to all of our health care woes. It will be must more modest. This is the interagency contact. This will allow the agencies to cooperate more. There are a number of research projects that are funded by the NRH, and NRHQ, and we have every seem MA -- emphysema surgery. What will be the long term effect? We don't know. The level of accountability is at unprecedently at high levels. We are reminded of this constantly. We are not allowed to have communications with the registered lobbyists unless it is in real writing. There's a worry that they will be interacting with the applicants or NIHs reps and we have been told to be careful. Grant proposals, this year, we will be getting 115,000. All of the people who are writing grants, we are told they should be expected to do a review. We will be able to do this review in an expedited and fair and comparative way.
Thank you for allowing me to be here.
Thank you.
Great presentation. Do we have a couple of questions?
I would like to mention on the registered lobbyist groups, and the White House has expanded that to lobbyist and non-lobbyists. I wanted to let you know that in case it hasn't gotten down through your department.
Questions or comments?
So what extent do you see the genomics playing a role in this? I think it is going to be fairly huge. As you know much of the genomics have been in the area of geneology. We are trying to put that in public available databases. This is used for studies of mechanisms of disease and epidemiology of the diseases. We are trying to incorporate the genomics with the clinical trying t we have the biological specimens. We can do the geno-typing which is more realistic. I can't talk about the specific proposals --
Right, I 578 not asking that.
I can't talk about the specific proposals, but there a lot of them. There's a list of the projects where we are considering the funding and there are a lot of those. The other area is the investigators who are interested in doing the genomic-based trials. We have seen proposals from the investigators where they want to test an interaction to see whether or not a treatment is more than likely to work with a group that is within a certain genotype and a non-genotype. The cost of the genotyping, which is going down, we will see more and more of these trials.
Thank you Michael. Stick around -- oh, know, you have to go to Cleveland. Thank you for your time.
The next speaker is going to focus on the challenges going forward. This is dealing with the method method logical issues.
It's a real pleasure to you have you here Steven Goodman.
Thank you very much. I never was introduced as a guru of anything, I don't know if I can live up to that. I have to develop a conflict of interest here. I have worked with [ indiscernible ] on a project recently, and he knows that I have completely [ indiscernible ] the terms of clinical utility, and clinical mobility, so I don't know if that will vanish me from the room. I am not a big fan of those. Predicting is also hard. That is another Yogi-Bear quote.
[ Speaker/Audio Faint & Unclear ]
What is that?
[ Laughter ]
So, I'm going to be focusing on a small piece of this, not specifically on the CER, but the genomics realm. I want to follow up with how it has been promised and the technical points and the life of computers throughout our talks. I wanted to show this slide. This is showing the individual classification -- let's see if I can get my mouse here now -- okay, now what you see here is the populations is part of the biomarker, the probability of people who have the biomarker and the value of it. This is the non-diseased and the diseased. And the odds ratio is 1.5. Here it is 3.0. That is pretty large for most of the prediction -- for most risk factors. You can see that in the domains. You will see where you cut the populations, your -- it will be bad. They are right on top of each other. The reason we get the discrepancy of the large and the poor affects, it has to do on the individual classification. We are interested in -- until now, in the epidemic populations, and we can make them precise, and we can see a difference, but it doesn't mean we can discriminate really, really well. So the biomarkers, the genes, all of those things, we can't always see those things, we need to see 25 up to 70, and that's something we don't see. We need the power of genomics. And often times they have little power when it comes to the conflict and the prediction of the equation. You can see the poor odds there with the diagonal means. That was for Hal.
I couldn't resist.
Okay.
These are the things that are cancerous. We have the razors, broken arms, but only in women, breathing raindeer, being short, being tall, and if you have escaped all of the -- oh, there is hot dogs, there is having a refrigerator, so we are all at risk.
[ Laughter ]
I can show you the same thing in the genomics realm, but it wouldn't last. That's interesting. It's a big problem. We are generating the reames and reames and reames of relationships and we don't know what they mean. Here are the problems and the conundrum. The background noise and it filters out the signal of what is important. As a result, the pace of the discovery is faster than the pace of the association. Finding the association, that's not really a discovery, but we treat it as such. And then we put it on the table as an evaluation. And then when we look at the evaluation throughout a lifetime, that is obviously really really slow. We have to be careful on how we ex -- experiment with our resources. I didn't want you to wait for all of is solutions, they are all here.
[ Laughter ]
Of course, these are not solutions, there are many, many more approaches. The new clinical trial models, and I will focus on the designs and they will be part of the rapid trials, and we have the enzyme trials. We have the trials such as these where I have been told that FDA has a requirement that when you are doing a cancer trial that one of the agents is an established cancer agency. It may have no effect, but they are working synergistically. We need the clinical files and data from the long-term files. This is is a huge, huge loss of opportunity. The only way we can get the rapid results is a way where we have the instruments of the [ indiscernible ] on the trial data from the 80s. There are very, very, very few resources like that. Every clinical trial that ends without the specimens are a clinical waste of that specimen. We have the power to test many of the things that we are developing if we would start investing in them. That information gets lost. We might have the tissues, but we don't have the long-term clinical followup. We don't have enough of it.
We need to improve the methods of the biological clinical trials. I will put in some of standards as well.
Let's talk about the adaptive designs. Those are the trials that change based on the perspective rules. They are not anything that goes trials. They are a rigorous trials. This is everything that is about the trials as you go on. You change the sample size, the accrual rate, the doses, stop early for success or terminate early for success. You can change the end points from the beginning and the end of the points if you is see that they are correlated. All of the rules that we have been taught about the specification and the design, these are just artifact ss and these designs allow us to do this. The methodology is all there. You need to do a lot to get into the practice. This is being championed by particular folks. Here are the two trials that are currently in the planning and execution phase. There are hundreds of these. Hundreds and hundreds of these. This is I-Spy 2, and that is a design for chemotherapy. The problems that are being addressed for this design is that the clinical trials take a long time for the evaluation of those trials. The biomarks are the predictions of who is going to respond to the drugs and how they are going to respond to it. It is a faster and a smaller amount of trials and they do an amazing amount in just one package of this trial. The design of this trial is that women are -- women who are positive, are randomized with the [ indiscernible ] plus or minus the new drug. They go on to the traditional therapy. Those who are not positive, they go through the same thing, but they don't have the inception of that. This is not doing justice. The second is to test, validate and evaluate the biomarkers. I will show you those. These are high standards of therapies and they graduate from the trial of the biomarker therapies. It look is a lot like it is very, very highly promising and that is leading the trial throughout the settings. They are improving the efficacy. And the new drugs are able to enter as you are going through the trial and graduating and/or when you are dropped. This is a learning clinical trial system. The setting is neo-adavant, and the neurologic is the response.
There are three. Here are the estrogen receptors. And then we have the qualifying biomarkers, they have great promises, but they are not approved. These are some preliminary data as they come and go through the trial. This is the list and criteria for the drugs. This is a certain panel of the drugs, but new drugs come out. This is compatible with the standard of taxing, therapy, and it has to have efficacy, targets, key pathways that are associated with the biomarkers, and lastly, is the drug available?
This is for lung cancer termination. This is a design paper that has just appeared in the clinical trials last year. This, again, is the trial where we have multiple biomarker groups, this is AHFR, KRAS, and -- basically, if you have -- if you have -- oh, this thing -- if you have the AHFR, you have the biomarkers and you are in a positive group. If not, you are negative on all. This is the prediction. This is what it looks like. They are randomized through these four categories. And so that means there is 20 possible groups. There is a number of 20 groups that will be tested. The randomization trials are changing as the biomarkers become accessible. They can graduate, they can drop, they can stop, and we have more information that is added depending on what the results are. We have the designs, the continuation of the process. And the patients are treated with better therapies. They can be shorter trials, but not always. And all of the information can be formalized. We are not used to formalin corporating the evidence in the interpretation of the trial. The physical paradigm it's now 80 years old. How many of those are unchanged in 80 years? We should be embarrassed. We have the itemized segmentation, and that is the dropping of the arm, one phase to the other. It is part of the concurrent informative and it is a definite one. When it is permitted -- what is it? The boat has to -- it's each tub with a boat at the bottom? You can't borrow the information. You have to synthesize those from the multiple sources. If they are not relevant or in conflict, you don't have sufficiency. They are curtailed and you cannot go from one phase to the other, and then you are stuck with waiting until the end.
[ CAPTIONERS TRANSITIONING ]
Outcome information in near realtime. If you don't have this then you can't make decisions that change the trial. This is happening in realtime. So we're accountable for data management, high quality data management in a time scale that we're not always used to. What is holding us back? Flexible user-friendly software. Design data management. Few investigators have experience in these trials temperature does require more up-front planning time.You get the payback on the back end, but not on the front end. Unfamiliarity by government. This is changing.
Again, some of the solutions -- talked about new clinical trial models, support for development of deposittories. I will talk about the reproducible research model so you know what that is. This was written about in an article by colleagues of mine, I have given Roger his picture here. It's his life's work in this, not mine. That's Roger who works in this. It's something that we've not seen, you may not be used to it. The data, the methods, the documentation, the distribution are all part of one document. It looks like a paper that you would read, but you can live reproduce all of the analysis, you can change one point or all of the data. It's a new way and a new standard of how research is presented. It's really -- first it came out of very, very technical proposals in the computer programming literature. It's now starting to see broader and broader application. The current data sharing model is either you share or you don't. Authors put stuff on the web or they don't. We do have some central database in genomics. But it doesn't really solve this problem. Readers have to get the data, download it, and figure it out -- no small thing. The data sharing model involves issues of intellectual property. You -- there are ways you to contain how the data can be used, I didn't put that slide up here. It's more complex than giving people data or not. It's a partnership between the person that has the data and the person that might use it, they're all shades of gray. This is the pathway where we have our measured data down here, and our analytic data result, computational results, and hundred of figures of tables and results and we merge them with text and we get an article at the end of the day. The reproducible research model allows the reader to go back here, all of these things are fused within a single document. It allows for a lot more transparency. We're trying to move this into the clinical research arena. We've made some baby steps. I bring it to your attention as a direction in which I think we will move over the next five, ten, 20 years. What a research article will look like in the new age I predict will be very, very different.
Reproducible research can increase accuracy, enhance the value of peer review. For the people in room it makes questionable results and methods easier to correct and detect. These are all things of interest here in the genomic realm where things -- where there's a lot of [ Indiscernible ] and stuff being generated. Here's the same solutions and, um, I think I have touched on almost all of them. I don't have a set of possibilities there. But I only had 15 minutes to talk about it, that's another few days. I think I will stop there and take any questions, thanks. [ Applause ]
That's great food for thought. Why don't we take a couple of questions for Steve. Hopefully you can stay for some of the discussion, too. Jim?
That's really fascinating. Given it's multiple arms does it limit power to the extent -- I imagine you have to look at conditions for which you have a large number of people, right. I think about that, of course, in genetics there was a study that showed there was one randomized clinical trial in the entire field. Part of that is not excusable.
Yeah.
[ Overlapping Speakers ]
Okay. Um, so -- power. There we go. The whole point -- I didn't go into tremendous detail. We don't worry about power as much. We don't have are these treatments statically different? What is the probability this treatment is the best? That's a different question than saying I can discern this from the bottom one or the next. When that probability gets high enough it goes out. The other thing is the information used for that contrast is far more complex than a simple binary contrast. If you have 20 in this group and 20 in this group you are sharing information from that therapy being used in all of the other groups and the hierarchy within that group. Your affective sample size is larger than 20. This is what is called borrowing strength. It's the same thing we do when we look at patterns. When the dose goes up the response goes up. That's exactly what you would expect because of X and therefore I believe it because of X. If you didn't know anything about the dose -- if you just labeled the dose categories at A, B, C, D, you couldn't make that inference. You have created information by knowing that things are ordered. And so -- these are modeled. The two ways to answer the question -- the effective sample size is larger. And the questions you ask are different and require less information to answer. You also have a coherent way of expressing degrees of certainty. You may choose to act in a phase 2 study when you have 80% sure. So you might say when it's 80% sure I will graduate this to a phase 3 trial. It's the phase 3 trial that provides for information. These screening trials move you on to the next phase. I think that's the best way to answer that.
All right. Thank you, Steve. Hope you can stay on for more discussion. Let's pass the baton to another one of ours, Marc Williams. In his day job you works for a terrific organization. They've done a lot of work this translating information on effectiveness into quality care. Hopefully it will help us to understand how we go into helping people.
Yogi Berra did say I have never said half the things I've said. I would note when I was asked by Steve to do this talk that another great American came to mind, Mark Twain. Those of you who have interacted with me would be shocked that I was aware of his quotes. I think it's important to say up front that I'm not sure I'm the best person to present this. The person that is worked for 20 plus years on this is Brent James. He's been involved nationally in the recent discussions on comparative effective research. The things going on at intermountain healthcare have not been labeled with the rubric of comparative effectiveness research. I thought I would present what I know having gone through the training program and have shamelessly stolen some of the slides of that program -- without his permission.
We tend to think of this as quality improvement. I thought it would be useful at least in my mind as I was setting this talk up to discuss the differences. And to reduce comparative effective research to half of a table on a slide is probably ridiculous. But clearly we've heard that the definitions are evolving. Hopefully they'll be a bit easier to settle on a definition of a genetic test. Methodologies are diverse. We heard about a couple that I have not represented on the slide here. Whereas quality improvement is management of processes. It also uses a variety of methods. I hope we'll demonstrate that it can show improvement in care.
I want to define what a process is. It's a series of linked steps designed to cause some sort of outcomes to occur, transform inputs into outputs [ Speaker/Audio Faint or Unclear ] and add value. A lot of this comes from industry, specifically the post-world war II, the Toyota model, work by democratting Demming and others. To do process management you have to do to start with the knowledge of the processes that you are dealing with, understand the processes aggregate to create systems, and that the processes interact. There's clearly variation in the operations of the processes. It does require a system for ongoing learning. Would we want to try and do is to build a system to manage processes and then ultimately if that's a rationale that works you get what results as quality improvement theory.
When defining outcomes in medicine we can aggregate these into three buckets. Some of these are patient outcomes, functional status measures, et cetera. It's important to recognize a flaw in the research that is published, many of the patient outcome studies are physicians' interpretations of the outcomes. A not so subtle but important difference. There are also service outcomes relating to satisfaction for patients and families, it includes access. I'm sorry Sheila asked earlier about liability. It's interesting that medical liability operates more in the service realm. The other thing that has been raising a lot of dandzer is the whole issue of cost. However, cost outcomes are an outcome of the clinical process. There's lots of costs that can be counted. These are linked with physical outcomes, you cannot say we will only look at medical outcomes and not cost outcomes, you can't take them apart. If you look at medical outcomes you will necessarily be looking at cost outcomes even if you don't actually report them. What I thought I would do is give you examples of things that we've done. I will have to really distill all of the hard work that gone into these different projects and hopefully get across key points about how things work. And then leave it at that.
This one of the first major projects that was rolled out relating to clinical care. These are patients that came in for cardiac surgery, they were intellect baited and had to be extew baited. As with any study you need to know the lay of the land. There was a baseline of data collection for 18 months. The meantime to extew base was 25 hours, you can see there's a huge confidence interval around this and huge variation in the process around this mean line. The intensivist works on this were breaking down the process. They recognized 240 independent variables at work that could lead to information we presented to the physician to present to the physician. If you have 240 variables it's hard to construct a randomized control trial and study how the impact of one would do this. The solution was decided on was to use a computerized-based protocol. The physician was presented with information that was thought to be most relevant to the immediate decision, they could choose to accept or reject the direction. On a weekly basis the research group got together to talk about the decisions that were being followed and not, the protocols were adjusted. This was done over a period of time in a iterative process. In a month after turning this on the meantime to extew base was reduced to slightly over 10 hours with dramatic reduction in variability. NationalAdditional adjustments were made. This resulted in extew base times of under 10 hours with the range existing between 7 and 12 hours. Basically proof of principal that you can take complex clinical processes and distill them down and result in significant patient outcomes. Here's some other tangible outcomes that we can look at in terms of length of stay. This is an example of some procedures. This is blood gases, each patient would experience 12 draws. This was reduced to two draws. The total cost of the hospitalization was reduced by $3000 in 1994-dollars, which I think would translate to $7 million now. [ Laughter ] I may be slightly off on that.
Here's another example. This was recognition of the evidence for patients with acute MI they should go home on a beta blocker. We were doing this successfully about 54% of the time. And the process was broken down and a change was made. The change involved the discharge process, the discharge nurse, and the final order set. We went from this 57% to 98%. This also shows something typical which is called holding the gain. Can you see how we drifted down after initiation of the protocol. This is typical because processes and systems have inertia. We tend to return to what we were doing. Tweaks had to be done at points 2 and 3. And since that time we've been able to manage the process such that we're operating at 97 to 98%. We did this to all cardiac discharge medications. I wanted to show you an example of something we commonly fall into. Here's our baseline measurements with the different values. And here are the national standards here. You can see that we were performing at or above national benchmarks with the exception of antiplatelet therapy. In many situations we would say good job, we're best in class. We compare ourselves to others. We've taken to calling this the cream of the crap approach. Because we shouldn't be comparing ourselves to others that are also doing a lousy job. We should compare ourselves to the theoretical best practice. You can see that in all of these were achieved in one month we were at or above 90% in all of these measures. This is great. This is clearly a surrogate outcome. We're assuming that better compliance will result in that. We looked at mortality one year before and after the protocol. Mortality dropped from 22 to 18%, which resulted in 331 people being alive.You can look at similar data related to readmissions. These are true health outcomes, true things that are meaningful to physicians, to patients, to administrators. I should say that one of the transformational activities is that at hospital board meetings the treasurer's report does not come first. Something relating to actual patient outcomes is always presented first. So I think that really kind of puts -- we hear frequently no money no mission, but the reality is we're not paying attention to the mission we shouldn't get any money.
Here are the cost outcomes. I should say these are not trivial to obtain. Systems are not designed to track where we're experiencing cost savings.We had to develop a radically different way to accomplish this. The fast track extew base protocol resulted in savings to date of $5.5 million. We've experienced with these top 11 interventions $20 million of improved cost structure. We've got an additional 30 successful clinical projects. We've yet to have a clinical improvement project that's not saved money.
Will this work with genomics? We've heard about this trial, it's referenced in readings in your packet. This is a study on Coumadin. We used a short-term follow-up of one month using sur gait outcomes. We did final differences. The initial dose was closer to the stable maintenance dose. This is not a big surprise. If you use this information you can better predict the final dose. We had fewer and smaller dose adjustments. Fewer INR measurementals, which did result in cost savings. We did find that wild type patients required larger doses, not a big surprise, given that the starting due is averaged out. We did not final differences in time and range for the group as a whole. Pharmacogenomic guidance was better for wild type patients. Those that had multiple variants -- [ Speaker/Audio Faint or Unclear ]. True differences in health outcomes of interest, although the time and range is a reasonable surrogate measure. We also captured in parallel, and to my knowledge this is the first it's been done in a prospective trial, is an economic analysis. We were able to do cost accounting. I don't have time to present that information. But it was presented at [ Indiscernible ] and will be published.
Why did not we not find the difference? We used clinical process management in our clinic. We have superior time and range compared to benchmarks. We set up the field to harder detect differences in the first place. There's interesting points to consider -- should a system invest in a robust clinic using best practices rather than genotyping? Would genotyping more appropriate in a rural setting?Would it make more sense to use the genotypes in that setting to get the right result quicker? Could I INR monitoring be optimised? Gurvaneet provided some information on this earlier which I find to be very compelling.I think sometimes we see this being dismissed at cookbook medicine. I like to go out to eat. I like to think the chef is using the same recipe every time I go in there. In some ways it's not an apt metaphor to begin with, but I would contend that the protocol driven work is not equal to cookbook medicine. This involves a multidisciplinary team. We do evidence-based reviews to identify best practices. We then actually put those -- the proposed guidelines out to the full range of practitioners that would be exposed to the guideline to get their comments and suggestions. We implement it into a clinical flow. Guidelines we refer to them as shared baselines. Clinicians are free to vary based on their own individual judgment. The difference is we capture the outcomes from the decisions to learn. When we refer to a learning healthcare system this is one of the key components to that, to have the systems in place to capture results to learn as you go along. We have to measure, we learn, we eliminate professional variation, which is my preference versus your preference while retaining responsiveness to patient variability. That's okay. What we've said -- the first rule is that whatever guideline we come up with it is wrong. We put that clearly on -- this guideline is wrong. But the intent is that we will learn from it and get it right over time. It's a rapid learning, rapid cycle. No protocol fits every patient. And no protocol perfectly any patient. We would be more concerned about a physician where we looked at their practice and we found they were absolutely following protocol 100% of the time. That would be a red flag to us. That implies that physician has turned their brain off. A concept from industry that we think this relates to is mass customization. If you go to order your laptop you can pick and choose what you want to do, but the manufacturing processes are standardized. But you can get a laptop that is built specifically for you using processes that are standardized with very little variability. The shared baseline allows us to focus on small subsets of factors. These are the 10 to 15% of patients that really need the thought and intensity because there's something that is truly different about them. It concentrates our most important resource, bright physicians and other providers. I don't know how many of you manage anticolaggation clinics, but it's the bane of most internists' lives. Our physicians that manage our clinic have extremely high satisfaction because they're asked to work on the patients where there's some really challenging clinical problem with managing their anticoagulation. Which is what we all went into medicine to do. Our satisfaction is quite high in our physicians practicing in this environment.
It retains the art of medicine. We're saying we think is the baseline you should start from, but you need to use your best judgment. It improves productivity. Our physicians are more productive. Which they can translate into more family time or more income. We want to do all of the right things all of the time. We want to do it every time with grace and elegance under the patient's knowledge and control. The question that I was left with is this really comparative effectiveness research? It's clearly comparative. I hopefully have demonstrated that we're measuring effectiveness. The problem is with the research piece. I know that in talking with colleagues that at least outside people that are looking at this are somewhat reluctant to say this is research and whether this would fall into some of these newer research methodologists we need to have more exposure to I don't know. The important thing is there's clearly knowledge here that should be disseminated to improve care. I think these will work for personalized medicine. We think they will be necessary to realize benefit. I would recommend to you untab 6 the brief commentary article which addresses this issue much more eloquently than I. Thanks.
Great, thank you, Marc. This is a good example of how a group can take what we do know and actually then make sure they get to patients and improve processes so they get -- the technologies get to the right patients at the right time and improve questions.
A couple of questions for Marc? Why don't I invite all of our speakers to join us up here at the table and what we have now is some time to talk about where we want to go. This is one of our priority topics that we identified. It's clearly an area where there's lots going on. Would we should be discussing is what do we want to to do from here? What are our opportunities? And where can we play a constructive role in moving this field forward and getting better understanding of the value of Jen stick and genomic testing? I will open it up for -- to our panel and to all of you.
I was just wondering whether anybody -- and Marc addressed this to some extent -- wants to pitch in on where we go once we've shown with comparative effectiveness research that something is better. We're all too familiar in medicine with the old adage that doctors are not trainable, right. We know what to do in many cases yet it's not done very often. What do you think are the best ways of making sure those things are then adopted?
Well, I'll talk the first shot at that. It's something that our system has really specialized in. I think doctors are trainable, there's a subtle distinction there. The reality is that there are several things that have to come together to allow rapid translation into practice. One is the recognition that a problem exists. Second, the demonstration that there is a better way. Third, to understand really the biggest issue which is the work flow and education piece. The education piece we know from physician postgraduate education that the tradition approaches to education have a very low level of effectiveness. What you need to do is present the relevant information to the physician immediately at the time that they have to make a decision, which is why -- you hear me harping on the idea of just this time point of care education. I have to make a decision, I need to know what the best decision is. I a lot of the care guidelines and processes that we have running operate in our environment under an info button. If a physician orders a test there's a button that will present if there's a relevant guideline the summary will pop up to them immediately. In realtime within seconds they can get that piece of information they need to make the right decision. Also with electronic ordering you can request that certain additional information be presented. You can do that without suffering problems of alert, fatigue relating to the idea that every time you try and do anything you are alerlted to something, we've seen that the drug/drug interaction field. The second piece is really understanding how physicians do their work and integrating that at the proper time. If you can match the right information at the time that the physician needs to do that decision, which I think obligates the use for the most part of EHRs, it can be done by paper but it's much harder to disseminate. If you can hilt those two then you can get rapid compliance very easily. The third thing to recognize is it's not always the docs that are the key person in the process. For that discharge medication process it was the discharge nurse that was the key individualism we removed the doc from the process there and were able to achieve the high level of compliance with improvements in morbidity and mortality.
I have a couple of questions for Steve. I enjoyed your talk. I would be interested in your comments about how your approach fits to analyze what is happening in Salt Lake City. Can it be analyzed in terms of group sizes and mathematics and certainty of the answer? You mentioned some value associated with tissue banks -- I'm interested in further exents about that. -- further comments about that.
I also wanted to answer the last question. The science of what makes doctors do what they do is very complicated. They always say if you want to understand the man look at the child or the woman. Let's look to see how they're educated back to the preclinical and the undergraduate, virtually all of the education is focused on basic biomedicals that none of us have to remember. Physicians are not equipped to be lifelong learners. Our fellows and faculty do not understand the literature they read. They understand the biology of it. They do not understand the statistics. They don't have the fine sense of the weight of the evidence provided by the designs and the results.In some way this is a profoundly different way of appealing -- it's a different source of authority, of knowledge in medicine.They're taught when they get out it's not important anymore. Do they have to read papers and do anything by spout the conclusions? Basically -- no. Physicians don't have access -- this is not a language that they're familiar with. They've to be taught on the back en. I think we have to look. I know it's being done. There was a report last week about pre-medcal requirements and such. We're trying to change curriculum constantly.It's too late late in the process. I don't want to say that. We do train clinical fellows, but it takes years. It can't be done in a short course. You want to add something to that before I get to --
[ Speaker/Audio Faint or Unclear ]
On the second question -- I don't want to -- even though I waved the magic wanldz I don't want it to appear like magic. By far and away the most important things are asking the right questions and setting up the right experiment. That said -- it is possible there are ways of incorporating approaches to make them more flexible, more powerful. You have to look at the guts of any particular experiment. I think talking about the kinds of questions, the information that can be shared from external and internal sources -- it's the information sharing issue that is key, that can be brought to bear on that process, maybe it could be made a continuous learning process, where the experiment never ended but new protocols are brought in. In the same way we have QI you could have cyclical experimental process. There are examples of this that have been done. You know -- I would always say that looking at any design through a more powerful and common sense methodology might improve it. How much it could improve it is very, very hard to say. I do know in the area that I highlighted that's an area where there's particularly high yield. With respect to the tissue banks -- it takes funding. I forget to say when I listed solutions that each one of these the NIH has the power to ameliorate. When we have a five-year grant for a trial where all funding ends for follow-up and support maybe we should think of a certain percentage that is maintained for every one. You have to have a centralized resource for the tissues, the linkage to the long-term outcomes, but you need support for patient contact, for all of these things. If the funding ends then the information ends. This is being done in many domains right now sort of piecemeal. It has to be taken on a major national initiative to not squander the resources we've put millions into building.
There was a really important point that Steve made. That is the idea of the continuous learning. I think that's really critically important. There's another protocol that we've developed on glucose management.
[ Overlapping Speakers ]
Not only have -- [ Speaker/Audio Faint or Unclear ] have built on a web-based server or laptops and have disseminated that to investigators across the world. We found that the protocol works in all of the different settings whether you are in Salt Lake City, Boston, et cetera. We've found that the same algorithm works in all cases. That type of knowledge can then be rapiddedly incorporated and aggregated. The key point there is that the target level of glucose, we can get to that level and reduce the variabilitity will not answer the best target to treat to. There's been evidence showing a much tighter control of glucose may not be the best thing to do, we maybe need to relax that. This research may not answer that specific question.
I've been a life long advocate of computer-based decision support until I got to [ Indiscernible ] and started to have a sense of what evidence base looks like. It doesn't look really good. When I heard Marc's talk I was totally dazzled. I am wondering -- to answer where we go from here -- how do we learn from the experience that you've had in a way that can be transmitted to other people in a way they would find convincing for their setting about how basically you get doctors to feel invested in decision support and want to pay aintelligence to it doctor attention to -- pay attention to it.
Brent has a training program where he brings people in for four weeks where you get the theory and you are required to bring a project to the course. The team works with you to help to have a success. There's that training aspect to understand the theory behind this and to also understand the theory of how to deploy it. What that course has led to is development within other institutions of satellite courses.There's been a couple of excellent articles out of the CF Foundation that have shown dramatic improvements. One of the interesting things is that it creates an environment to share success. What you find is no one is the worst at everything, no one is the best at everything. There's variability. Some places that are worst or best in class are the opposite in other areas. You can get a rapid learning environment. You also learn about what worked for deploying it and what didn't. That's the training perspective that's been successful. The second issue relates to the barrier of publication. Frank Davidoff has published a couple of articles relating to the work he's done looking at methodologies and organization of papers around quality improvement that are beginning to start to define the landscape around how should we be presenting this information so that others can begin to learn from successful experiences around this type of improvement activity.
It occurred to me --
Your microphone --
With computers up the opportunity to randomize within an institution different methods for getting attention. For example, maybe you need to get Steve out there to collaborate with you on studies that would generate knowledge that would find a ready home.
I would agree with that. There are ways to do it. There were examples where children hospital's was offering a range of tests for inpatients that were treated on medications. They had genotyped the patients and then they actually looked at the medications that were used and said this was a -- they assigned whether it was a good or poor match based on the type of medication and dose and found significant differences in terms of length of stay, restraints and holds. They created a system which which the physician could say this could be benefitted by a pharmacogenomic test, do you want to do that test yes/no. You've got a real world trial where you measure your events based on did we follow the instruction or not.
I think what you are describe be is why [ Indiscernible ] systems are so important. We often talk about research-based practice, which get this data and try to apply it and opposed to practice-based research. Gwen was next.
Okay. I wanted to go back a few steps to Steve's presentation. One of the things that is critical to research is people that participate in it. This-- is it is a design that appeals so much to advocates and those people that will go out there and to help the trials because it is adaptive. It's just to -- just to reinforce the fact that research needs the people. This is a very -- the other thing that I think works is the collaboration across the different stakeholders. I would just make sure that we include that.
I would be interested in your comments about how CER could be structured so that patients felt as if they were part of the game and that participation was an opportunity instead of something to be avoided.
I think the most -- you know, one of the most important things to patients and why the trials work well is what you were talking about in terms of asking questions -- asking the right questions. The right questions have to be questioned that matter patients and patient outcomes, quality of life, matched with values. I think that's a really critical thing. That's why the adaptive trials appeal to people. You don't go in with something that is fixed. I think it's pretty horrifying to think that doctors don't necessarily -- aren't good lifetime learners. I think the other aspect of the trial that is a great precedent for other trials is all of the stakeholders have been involved from the beginning. If you want patients to buy-in to it you have to bring the patients in from the beginning. I spy 1 had a lot of MRIs and biopsies. Patients were brought in to communicate to the parents, they had a high retension level. I think there are different ways of bringing people in the beginning. Everybody wants to know that the drugs that they're given are effective. They also want to know they're an improvement and there's a learning process, there's progress. I think those are two ways to bring patients together. I think there are obvious many more.
Let me get a couple of other people.
I have something very important --
20 seconds.
The other place I see it relates to a dilemma that has appeared around adverse events and efficacy. If you take the UGT1A1 e-gap there appears to be evidence foreincreased efficacy in the patients that have the polly morphism. I would think -- if I were going to study that I would be very interested in engaging the patients. What is more prorn to you? Avoid of these events? Or irradcation of the tumor? That is another place to engage.
What are the important outcomes? What really matters?
Andrea?
I have a different issue.
Okay.
I think what I want to do is get different issues on the table here. One of the options that we have going forward -- having identified these issues -- figure out where we want to go next. One of the things we hear a lot is if you personalize things it will be hard to do it in the comparative effectiveness world. There's issues of disparates. How does that play out in genomics?
Just a statement. As I continue to read about research and looking at the different ideas that are proposed and where you might be selecting different patients on genomic technologies we need to be cognitive that different technologies work differently. One example is breast cancer patients, if you do testing for [ Speaker/Audio Faint or Unclear ] versus fish you might have different results. I haven't heard anything about the role or research needed on comparative effectiveness on some of these genomic technologies to focus on [ Speaker/Audio Faint or Unclear ] the patient population. With that, also, as we continue to look at the studies where you select patient populations, or a group of individuals to go into a [ Speaker/Audio Faint or Unclear ] that actually these extensivelies should be -- actually these tests should be done under the highest quality. I haven't heard anything about CLIA certified laboratories. These could be very important issues, that we're assured of the testing that is done under the best quality. The other issue I I was struck by is different organizations -- the amount of money that is put on the infrastructure to look at fundings and research. The idea of having coordination on what different clinical trials is being used. Maybe having a clearing house of what is being funded, and what are the results to come back and say this is already done. Maybe something similar to the clinical trial.org website where the information can be accessed. It's a topic that I have not heard discussed that I think is important. With the issue of tissue banking the quality of the specimen that is put in is of huge importance. If the tissue is not properly stored or obtained the data will be skewed. These are issues that need to be dealt with before we dive into the comparative effective research to make sure that the data can be translated into the practice.
I want to answer just two things. First, what is interesting -- I didn't go into all of the details of the trial, but they'r looking at how that measure of how [ Indiscernible ] was measured. They plan to shift from the [ Indiscernible ] model to the other technologies. If they prove to be more predictive. That's embedded within it. They're doing that with several other biomarkers as well. That's part of the validation and improvement. With regard to tissue bank I couldn't agree more. Everything I mentioned will require serious thought about how to create databases that will be usable 20 years later.
Thanks, Steve. [ Laughter ]
Thank you.
Mention a few things. One, since we're talk being clearing houses and there's already this challenge about information and quality improvement activities and AHRQ has [ Indiscernible ] exchange clearing house for that purpose is so we can share innovations and other people can learn from it. The second activity is one we had funded more on the learning healthcare and practice-based research. There were two different modeled that we funded. One of them is looking at how different primary care practices who want to benchmark how they're doing and compare each other and learn from each other can exchange that information and it can also be used for outcomes research. The third part is the clinical support tools that I mentioned before. There will be involvement of the patient in terms of getting family history and shared decision making with the provider. I think we will be learning something from that project.
I wanted to talk about one aspect of your question, trying to achieve transparency as much as possible so the public really understands what is happening. I'm in favor of that, except for one part, that is the research results themselves. Steve, pay attention, I'm going to ask you a question, right now I'm a strong advocate of journals and the processes they go through to make sure that work is done according to good practices and the language is transparent and is not biased or slanted. And therefore I wouldn't want to see research results published until they had gone through a process like that. Steve, is there a time in which with the appropriate design of research perhaps particularly adapt to trials we could skip the journal part, in other words things would be done in such a way that the role for journals would be reduced to writing occasional -- editing reviews of subs like that? Or do you thing there will always be a call for journals? Steve by the way is the editor.
[ Overlapping Speakers ]
I think we will always need impartial after bit fors of the science.-- after after bitters -- arbiters of science. I think it will have to be retained. Researchers themselves because of training and conflicts of interest are not always the best judges of their own work. I would just leave it at that.
I don't think I was talking about putting all of the results -- but what is done -- sometimes also it's important to realize that some things are not published. Negative findings are not publishable, but they're valuable.
Right. This is always being done in clinical trials.gov. There's several international efforts devoted to developing standards for reporting results of research. It's starting at the RCT stage, those are the most structured ways we have of doing and reporting experiments. To what extent this will be extended it all research is a really complex technical challenge. Even with RCTs this is very, very difficult to know what you put out there, what do you put out there vetted or not vetted. A lot of groups are struggling with this. It's a very much a subject of international ration -- collaboration.
Knowing that the research exists can help a lot.
Right, that's what clinical trial.gov does.
You don't have to have the results to know what the body of evidence might look like.
I think also the negative findings that don't make it to literature are very important for investigators to know. I don't have an answer.
That's what clinical trial registration does.
The registration. But there's no results --
That's the beginning of being able to go back to the company or investigator. You know the denominator. Yes, the results may or may not be there. Can you go in theory --
Some should be on clinical trials.gov.
Sheila?
Thank you, all. This has been a great discussion. I want to bring it back to your slide sets. You included a page on solutions and future steps. I thought that might be helpful for this group to talk about that for a moment. If each of you could suggest one thing that the department could do in this area to forward these approaches. Whether it's eliminating barriers at FDA or consolidating or linking up the innovation clearing house that Gurvaneet talked about. What would those things be?
You go first.
What is my top priority? I think the fundamental issue is an infrastructure that can get at what is happening in the healthcare and learn from it. That would include inform mattics and better clinical data collection, maintaining the privacy of the patient information.
I don't know that I actually have anything to add over what I said. It's two pieces. One, to create a data sources from past experimentation that allow us to test as quickly as possible.We already don't have adequate past data. We have to look forward and start creating our past in realtime. And then start using -- in terms of HHS I think what I mentioned before is thinking about how to formally support the increasing data we gather with RCTs being the natural first place to start. That offers the biggest bang for the least buck. Second, going forward focusing on the resources which include development of inform mattics, the tissue storage, everything that is involved in doing -- in using methodologies that get us answers more quickly and efficiently. Right now everything is built almost from scratch. We need to increase the resources available for the development of the software, the training, the inform mattics, backbone, all of these things. Going back and going forward -- that would be what I would say.
I would like --
[ Overlapping Speakers ]
If I had the Secretary's ear I would urge her to make a really serious effort at coordinating CER across the different agencies and HHS, as well the VA and the Department of Defense so that as much as possible outcome measures are standardized using the instruments that are widely available and validated. So we end up with research that can be compared with each other as much as possible, even though the funding agency may be a different one. In addition, as much as possible, promoting collaboration between the agencies and funding research on high priority questions and conditions. Serious effort of coordination.
One footnote, this is something is a priority already, enabling -- doing everything to get this into community research networks. Most patients are not seen in academic centers. This is being done piecemeal.
This has been a great discussion. We're now at the point where we have to figure out what we will do from here. I have heard a lot of good issues. We had earlier discussions that said we need the evidence before we can move some of these tests forward into practice. These are critical issues. I have heard issues around study designs and how to build the right infrastructure. How do move move into a learning healthcare system. There's unique issues that relate to what we're talking about are rapidly moving fields. There's a general sense there's some dichotomy between personalized healthcare and the information that comes out of comparative studies. I think there are a bunch of issues here. Are there some of these that we are well positioned to take on and work through? The proposal I would like to put on the table for you to consider, since I doubt we can [ Speaker/Audio Faint or Unclear ] is we form a small group to sort through the issues and bring back to us next time a distilled and considered list of things that we could do and recommendations about whether to go forward with this work and ideas on the scope of work.
So, if I could add two things to the list that may also help to focus this. As I look at we have to clearly have to look at genetics and health and society. At the present of time we don't know what the IOM report will look like and what their prioritization is going to be. That will be forthcoming. Second, we will presumably have the round of funding announcements from the first round of the ARRA in September. I don't know whether it's possible, Michael could probably answer it if he were here, if we could get a list of the general pots of funding to see what we might be the genomics round, that would also give us an idea if there's priority areas that somehow escaped being funded. That could also help to form late where we go.
I didn't mean to make this a fixed list either. I think a group could tease out whether there's an agenda for us.
One comment about the word [ Indiscernible ] wasn't mentioned here. But the experience there is interesting. CA big is cancer bioinformatics grid. It was a huge effort, which I think everybody is fond of deriving. Where the progress is not in the tools themselves but in the standards, in getting people to talk to each other. If you can think on your agenda of what standards there could be in the domain of genetic testing that would enable sharing of information, established quality standards -- I wouldn't even know where to start -- that's where that effort would be. Ultimately many people are building their own tools, but to those standards. It's sort of like the iPhone model. They unleashed this huge -- it's a huge marketplace now. I don't know that anybody can dictate the tools. If you have a set of standards you will move things forward.
[ Overlapping Speakers ]
That is one of the things that federal government can do. If you will give out grants, in this area you can dictate the standards on whatever it may be.
Right.
If folks are okay with that I would like to see volunteers that could help to pull the threads together and help us shape and bring back something. I would be deleted to have a [ Indiscernible ] voice.
Andrea, lab perspective. I think some federal partners, too.
I would think at the minimum Gurvaneet and someone from NIH.
Can we start with that core group and certainly others that want to be --
[ Overlapping Speakers ]
If there are others just let us know. Marc, are you willing to -- I know you have given a huge amount -- are you willing to help lead this? That would be great. All right. So -- let me, again, thank our terrific panelists. [ Applause ] A great group of folks. [ Applause ] We appreciate the insight and leadership you provide. We'll take a break for lunch. We'll aim to be back here by 1:30 promptly. I know we will start losing folks. And we have some reports to get in. Thanks, everyone, see you back here at 1:30 Eastern Time Zone.
Session on lunch break until 1:30 Eastern Time Zone.
All right everyone. We are in the home stretch, I hope we have several updates on federal activities related to our work. In the post of those presentations we have from our colleagues at CMS where many of the issues that surround reimbursement and coverage have launched an interest to us. And this committee made a number of recommendations. And it has been really gratifying to see the response that CMS -- or how responsive CMS has been to those recommendations. There has recently Ben two meetings that have been held that relates to genetics and genomics. And Jeffrey Roach who is a regular here as a liaison has played an instrumental role in all of that. He is a physician with CMS and we look bored to hearing what has been going on -- look forward and to hearing what has been going on.
Thank you very much and I would like to summarize some of the meetings and we have been asking for a variety of clinicians and agencies and government and those who were present patient advocacy groups and industry to health Medicare understand the things that are important when we decide coverage we like to have evidence that we can provide for it and these meetings which were held in the last four months has focused on genetic testing and that was by design. So I like to very briefly talk about some of the things that were done and I appreciate the gentleman that will advance to the next slide. The first of the two meetings was run diagnostics uses of genetic testing and what qualities or characteristics of evidence would be desirable for Medicare to use in determining whether genetic testing as a laboratory diagnostic service improved health outcomes. And that is part of our role and part of the Medicare orientation of this week asked the MedCAC panel members to look that at this definition of diagnostic genetic testing to print made the amendment to make decisions about an illness that was under treatment. And because of the different types of evidence that might be involved last the panelists also to look at diagnostic uses, prognostic uses -- what is the likely outcome or total burden, and finally, tests that health physicians assess the response to therapy. And we tried to give some examples of the uses of diagnostic genetic testing and these were posted in the Federal Register about a month before the meeting. And we try to supplement with some of the more valuable pieces of literature. And our role there was to listen. And we were grateful that the MedCAC members provided us with some very good suggestions. In addition we were lucky enough to have some very good guest speaker and one is Tom Trikolinos will had performed with his colleagues a Technology Assessment on genetic testing as well as Dr. Ralph Kotz at the Centers for Disease Control and prevention. And both of these were very helpful and we got a lot of positive response from both of their presentations be one of the things that the committee heard about was the cgap ACCE criteria and some of the facets of evidence that you can see on the slide and this is what the panel felt was a useful framework and what was the value of genetic testing and diagnostic situations. And we also were impressed with the EGAP's methods and looking at questions which were similar to the ones that Medicare asked. We have to ask, for example, what is the evidence for adults with non psychotic depression with SSRI type anti depressants benefit from Gino type testing and it turns out that EGAP has addressed these issues and make up some ground rules for doing so and we were grateful to know that EGAP is working on these and other important decisions and use of genetic testing and other diagnostic decisions. Next slide, please pick what our usual practice is at CMS is to ask a panel specific questions related to some of the things that we consider when we look at Medicare coverage of diagnostic testing. And it's already covered to some extent under the Medicare program and one of the first questions we wanted to find out what are the desirable characteristics for diagnostic genetic testing different to those of diagnostic testing in general? And MedCAC's response was no. They suggest that we consider the EGAP ACCE criteria as a series of useful questions as we sort of the evidence and finally that the public is well served by robust evidence such as evidence of its harms and benefits such as in the elderly population. The second question that we posed to the MedCAC panel and these were posed about one month in advance published to the Fred Register, how do we determine analytical validity and the MedCAC responded that the free market had a number of specific areas on which evidence could be constructed to determine the validity of these types of tests. In the third question again in the February meeting was whether there were meaningful differences in the types of evidence about the use of diagnostic genetic testing in terms of those three major using, diagnostic, prognostic and pharmacogenomic and MedCAC's consensus was as noted there. And I should mention that the transcript of this meeting is available through the CMS Web sites. Unfortunately the May 2009 meeting which is the second part of our talk is not yet available but once the transcript is finished and reviewed by CMS we will go ahead and post that as well. Oh, sorry -- can we back up? Thank you. And there is one difference in pharmacogenomic because there is a three part leakage, and linkage between the genome, disease, and drug and dosing and genomic testing does look at all three of the serious but again we have recently finished the public comment period and have public comments suggesting that we could stomach should consider before we make the final decision on that in roughly two months. Now the other kinds of evidence that will look at is evidence about changes and outcome. And in this question, question Number four of the February MedCAC looked at three different types does the physician change his or her toys of treatment and second to outcomes that affect in direct health care outcomes such as a change in the lab results are those the prepared to defer that diagnostic genetic testing is effective and what about direct health care outcomes like mortality or adverse events? Again, the MedCAC was asked to vote on this and as you can see they felt that the highest confidence could be placed in studies in which the outcome reflected a direct health care outcomes such as brutality. And with the boating skills going in this question and indirect health care outcome was a fair. And this was rated a little bit lower than the other two. Now the fifth and six questions which are similar in both the February and May 2009 meetings addressed whether ethical issues pertaining to genetic testing should alter, limit or lose the match the look the logic -- methadologic rigor and.
And to be that it might detract from evident since it might tend to lead to additional harms and the population been separate and where the age of the Medicare beneficiary population was a challenge for researchers looking at the use of the diagnostics be in the testing. And the panelists nearest to possible considerations that e shifters should take into account. The first that there is a rarity in the Medicare beneficiary population and the second is that the challenges in that population may be to eliminate confounding factors that might be due for example to polypharmacy, to multiple causes of that affect this population more than other populations subgroups. Thank you. Could we go ahead and skip through this one? At thank you in summary in the February meeting and thanks to Dr. Louis Jock to summarize what the expectations the Medicare at least was to have at this meeting for diagnostics be should be at least as high as the expectations that we have four other diagnostic technologies. That there is an ethical imperative that requires rigorous evidence when we make such decisions especially because of the consequences for the more than 40 million people that could potentially be affected by these decisions better Medicare beneficiaries. And finally that the clinical context of such decisions is extremely important but we should always be very much aware of and make such decisions in very close concert with professional societies and other groups that recommended leading opinion. And backed up, Of course, by evidence of the effects of these things. In May, it just about five weeks ago we convened another group on screen uses of genetic testing. And this focused on the desirable characteristic of evidence again needed to evaluate screening genetic tests for Medicare coverage. And our question basically was does this improve health outcomes for the Medicare population? By detecting a disease in a person who has no signs or systems of that disease, for example shown in this slide. Next slide, please. In current law under Medicare part B under Section 1862 there are a number of exemptions under General about reasonable and necessary treatment which allows for screening of particular preventive service benefits including some of these screening test shown here not only for cancer but relatively common chronic diseases like diabetes. Can we skip the next four slides please?
We were lucky at this point and people may notice a few familiar names to have them to the speakers of one was Greg Feero and Steve who was one known to many of does he was kind enough to, and talk to us about some of the screening genetic applications that EGAP has considered and in particular Steve was kind enough to go through a very careful discussion of the EGAP method as provided -- as it looked at screening techniques, not just diagnostic techniques. And I think Steve made a very important point which was picked up by many panel members at the words which is in a screening situation, using genetic tests has to be looked at not only for the potential benefit for those who are affected but the potential harm to those who actually did not carry a particular genetic marker. But because of testing uncertainty or mistakes could be exposed to harms of additional testing. And again, Steve suggested the importance of a balanced approach between benefit and harm the outcomes. Next slide, please. And during the discussion the panel was also informed that some of our partner agencies like ARQ did a number of studies on both the screening testing and the effect of this as a less cost effectiveness of DNA testing, CT planography so that the idea of doing technology reviews and the cost effectiveness of technology is not a new one. And the first two questions were similar, are there differences that governed screening genetic tests versus those that we require screening tests in general and whether the desirable characteristics of evidence that they are analytically ballot that we are measuring one expects to remeasured. And the third question was a little bit different. What we wanted to do was look at the two major paradigms' which Medicare has by law luck at -- by law has looked at, can improve patient outcomes by detecting and disease early and can improve patient outcomes by treating the disease early before signs and symptoms are apparent. And the following question reflects the fact that genetic testing is in some ways replacing earlier screening paradigms' pick for example, if you recall blood testing. And we were interested to look at coverage decision effects of comparative data that we would need to make sure that there was evidence that the alternative strategies for screening rely less effective than the genetic test strategies. In addition we did ask the panel to vote, next slide, please, on the different types of outcomes here. And one of the outcomes that the panel decided not to vote on was that a genetic test used for screening purposes might provoke additional confirmatory diagnostic procedures. The panel did not think that was a reasonable outcome to look at at all. However, the panel did clearly indicate that they would have a high confidence that it was effective if it improved survival. And a moderate degree of confidence that a screening genetic test would improve the other patient focused health outcomes especially functional status or would decrease the incidence of adverse events. The fifth and sixth questions were focused on some of the new authority that HHS may have at looking at cost effectiveness. As you know in the Medicare improvements Act of 2008 or MIPA 2008 in section 101 it indicates that the secretary may look at the relationship between the benefits of certain new preventive services and the expenditures involved in those services. And the panel was asked to rank for the specific examples of screening genetic tests what type of the outcomes would be most favorable or most desirable in terms of genetic testing coverage. In the second of these two questions, question Number six we asked the panel which would be desirable methodological characteristics which would health provide evidence that they were preventing or detecting early either ... or disability. Next slide, please. The MedCAC were clearly comfortable in this is on a different scale than the prior two tables, it goes from one to three here number one a less desirable measure or three a more desirable measure and it looks like there's not much difference between quality or decreases in incidence of illness or net gains and other focused patient health care outcomes. Next slide, please. Finally the last two questions as I mentioned were similar to the ones posts in February. Next slide, please. In summary, the MedCAC in May suggested again that we should have high expectations for the evidence used to suggest that screen uses of genetic testing were purpose for Medicare coverage. And we thought in view of the large number of people who might be their risk from is sufficiently investigated -- excuse me, screening genetic tests that rigorous evidence was entirely justified. And especially that there was a very important role in balancing, sorry, considering elements of both of harm and benefits and looking at either quality adjusted life years or decrease the incidence of disease. And the panel really was not interested in looking at outcomes that suggested for example, the lifetime cost of an illness would be decreased due to screening speech. Next slide, please. Again I want to thank both Steve and genetics who were kind enough to go to CMS for the purposes of these meetings and I would be happy to answer any questions briefly as time presents.
Thank you, Jeff. I think we're holding these meetings because these are exactly the kinds of things, not only will be grateful but it was very productive.
Mark? And languishing in the discussion period was clearly [ Indiscernible ] by me not being up that front. I do not understand that either. So in the comments about the discussion of the single gene, I was curious if there was any specific discussion about to population of Medicare that they're responsible for one is the adult disabled population and a fair number of those related to more traditional genetic disorder some of which andante end Stage renal Disease population and the genetic disorders that are relevant.
Mark, thank you that is an excellent comment and I agree with you in those two populations especially and more generally as they understand the narrow degenerated diseases that Medicare has the need to look at the specific applications. And when that comes about and the shift focus is from the court and the fishery population, those -- the court beneficiary population. I would not call them criteria at the moment but some of the suggestions and indication on where the value would be and what would actually improve outcomes for the beneficiaries. So thank you, you are quite right.
Thank you, Jeff. We always appreciate it and thank you Board your information and all of these discussions -- thank you for your information and all of these discussions.
Greg, I see you back there. Since we just introduced you yesterday I assume that we all have an efficient memory of who you are and where you are going but we would like to welcome you back. And, in fact, you actually had a nice introduction from Jeff and I think you'll be reflecting again on what is going on with the family history tools and the upcoming state of the science conference. So take it away.
What is that?
Sorry, I did not catch that.
So I was thinking to myself I had the luxury this time of coming to you talking about mom and apple pie subjects and nobody says that a family history -- Well, maybe there are a few. I was asked to give an update on the pedal family history activities -- federal family history activities and I apologize to any of the partners that have hit history that we were unable to capture. I want to make sure that I have comments for some of their activities but I suspect that there are others and I know, in fact, that the VA is actively engaged in family history activities as well. So this is not the official NHGRI you on this subject and I put the next slide up to say that most people agree that this is probably true and we ought to be focusing some ongoing attention on family history as a tool in health care moving board if we focus on advanced screenings of the American public agrees that this is true and I don't know if this has been presented before but there was a recent study and Oregan and showed about 99% people said that family history is important to their health and this improved from the early data from the CDC were about one-third said that and this said two-thirds of folks collected information. And the vast majority recognize that having a relative with heart disease and diabetes increases their own risk of developing the disease. And I think family history falls nicely into a, you know, relatively well accepted position for use. If you want to consider if a genetic test. And we are thinking that we have seen this before, though one were to have this move over to hear and we would like to get this closer to hear. And family history will be very important for risk assessment purposes. And I'm like a number of genetic tests, they have come up with guidelines that involve family history. And this is the one that is most positive and I made the argument as CMS there are a variety of the USPSC guidelines and if you look at colo rectal cancer you can use these unless there is a family history of colo rectal cancer, in which case you have to use a different guidelines. So there are the positive elements of the USPSC guidelines and then the negative elements in order to apply the guidelines appropriately and health to drive the potential use of family history in the health-care arena. Some other things have happened in the recent past that make a family history a more powerful tool in many folks have been concerned about family history information and their main concern about how that might be used in some of these have been diminished. And this is something that this group may not know so much about. But this past year the Office for Civil Rights put out some guidance regarding HIPAA and family history and I would urge you to take a look at this URL and it suggests that family history can be treated as other health information in the medical record in terms of sharing, and you can in fact, if the patient gives you the relative name, diseases, etc, etc, transmit that information and use it in the medical health record environment freely as long it was obtained from the patients themselves. And I think we have a possible window of hope in the reimbursement a rematch with the MIPA -- with the MIPA passage alluded to earlier and we have an uphill climb regarded to the Medicare population and the use of family history but at least there is some light at the end of the tunnel there. Seoul on to federal activities just as an update. And many of you are aware that the CTC over the last couple years have a major trial of eight family history tool which was a web based -- of a family history told that not only collected family history information but provided the patience with some risk assessment feedback from that family history information around six common complex conditions. And the methodology for coming up with this tool was published recently in the prevention of chronic disease. So one of the first papers and I believe there is seventh in the pipeline and there may be five because of these two being published and one of the first papers that came out looked essentially at the burden of disease risk in the disciplines and the trial. And there is a pretty remarkable data. 82% of the participants had a strong or moderate familial risk when and that is not that shocking. But some of those folks have high risk. What I think is more interesting and has not yet come out that a sub group was click debt in the northwestern health care system when they looked at the uptown and tools as to what was in the paper charts and about 23% of the paper charts had enough information around family history to assess the risk for those diseases and that goes to Mark's point about the need for enhanced tools for this kind of work in the tool, the preliminary results says that there may be risk perception among users but there are also a lot of paradox zero defects that were noted -- paradoxial affects and they were folks that were attuned to their health and were highly Flint, -- affluent, well educated and you'll be reading about that more in the future. There have been a number in the last year or so about translation of genomics research put out by the CDC, NCI and if you look through the grant listed in there was at least one or two in there that involve family history and point of care tool development, for example. And if you look at NCI's cancer preventive service division website you will see that their priorities for 2009 include the following statement which really bolsters the likelihood, I think that folks will be thinking about integrating family history into population based studies for disease risk as we move forward. And in the area of evidence the synthesis, HRQ has been very active and they have had two major reports published on the use of family history and the cancer arena and then the last and most recently published in April of 2009 tried to address the issue of clinical utility of cancer family history and this is where family history is on somewhat blocked ground. We assume that there's a lot of face value and literature, but I would argue that there is not a ton of literature using stethoscopes and medicine as well. But, in fact, this is just some data around family history and I include a lot of did in the slide. This is what the conclusions were around clinical utility around canter family history collection and primary care. There are very few evaluations of cancer risk prediction models and that those risk prediction models do not suggest a huge amount of individual accuracy. And we heard a little bit about that around genetic risk markers. And that the experimental evidence based and the primary cancer prevention is very limited. And this is not a primary care study, not in the special the clinic where there is a lot of literature or a fair amount of literature. And there is evidence on preventive behaviors, of course, the CDC tools, the trial was just completed at the time this report was put together so they did not have any of that data and there is insufficient evidence of whether it directly causes adverse outcomes could which is a good thing, I guess. So where are we going with this evidence since this is a round family history? In just a little while we will be having a major conference that is open to the public at the NIH where we are attempting to gather the entire realm of literature around the use of family history as a screening tool in the primary care setting into one place. And then in the process of doing this state of the Science Conference identifying with the gaps are and where research needs to be done to fill those gaps. And I invite you want to consider registering and attending, it's free and is in Bethesda and it should be quite interesting. There will be 21 speakers I believe, three of which will be from the EPC. And it will update those cancer reviews that you just heard about as part of the process and we have asked them to look beyond cancer to cardiovascular disease, diabetes and things that were not covered in the earlier evidence based reviews. And there will be a large number of experts speakers on family history. Running the gamut from this epidemiological aspect and how well it predicts risks to social cultural aspects that family history and how can it be used in community settings to engage folks in discussions about the CS prevention -- disease prevention and there is the URL on the slide. And what is the pragmatic approach? We immediately jump to the risk of family history as a risk assessment tool in health care. And, in fact, a family history does more than that it allows people to an idea and differential diagnosis some no matter what the evidence based review show I don't think family history will be turned off in the minds of health-care providers. So given that it does sort of have lots of rules in addition to risk assessment there has been a lot of effort focused on an aging communities around the use of family history. And some wonderful work done with the genetic alliance in the last year creating tools for helping communities and individuals gathered family history information and share that with the health care providers. And NHGRI has had some very interesting demonstration projects with communities. This is example in the south central foundation of the family history demonstration project which was quite wonderful. And if you have a chance and go to the NHGRI website I think the video was up about an caging the community -- engaging the community. And the Jeffrey Roach has done a fair amount of work with the urban appellation community and very interesting work. A little bit earlier than the south central foundation work. And NHGRI spent some time and this is largely work and I don't know if Vince is still back there, but it came from the education and community involvement branch at NHGRI. And they have done some work around the National Council of [ Indiscernible ] in looking at family history in that population. Again, quite interesting work. So the grand daddy project that we were tasked to talk most about which is what has been going on with the surgeon General's family history to appeared in 2,004 be teamed up to introduce the family history initiative to increase public and provide your awareness of the families of history and health care. At that time there was a first generation family history tool created and it was then both web based, downloadable and in paper format. And it did a very nice job of collecting family history of affirmation and focusing on those six disorders that the CDC focused on and reporting that information both chart and pedigree form. It was, however is stand alone tool. So one or two of the major deficits with that tool, the first was that once the patient completed the tool at home or the consumer completed the tool at home there was this gap in getting that information from the user to the health-care system were its potentially provide benefits. An individual would have to print the history out and carried it into the clinician and in the age of electronic health records they did not have anywhere to put that so you can imagine where a lot of those family histories might have ended up. And the other aspect of the tool that it provided no immediate gratification for use in terms of providing consumers with some glimpse of what their family history action meant to their health. So the first issue I think was the one that needed to be tackled first. In the last two years folks in the personalized health care initiative under the former secretary and the surgeon general, NHGRI and federal and nonfederal partners decided it was time to create a new version of this Web based surgeon General's tool that had the capability of connectivity to electronic health record and personal health records systems. And you can see the list on the slide of the folks who were involved in that. And the principles is that it would be standard based to the best extent possible at the point in time that the tool was being created so terminologies, for example, were done in SnowMed and anything that was numeric. And we used the recently passed HL7 and the output of the tool is XL based and apparently is compatible with a lot of health IT systems for bringing in data .And we recognize quite rapidly that there were a number of gaps in the existing standards that did not allow you to deal with family history. And one of those was dealing with the fact that there was no clear corer minimum data sets that folks had identified for a family history and we spend a fair amount of time on this data set which has now been published and adopted by HITSB as aid interoperability standard. In January 2009 the new tool was launched and interoperable with a variety of different HIT platforms with the minimum amount of tweaking on either end. And it allows the consumers to the potential to share their family histories electronically in a way that does not necessitate this paper step in getting the information into the health-care scene. And since the launch of the tool which is available not only as a usable tool but also for download. There has been a lot of interest in vendors and northwestern health care system has been looking at this tool and the PHR and EHR and we have engaged in discussion about Microsoft helped gold and making their information compatible -- Microsoft health vault and DockSite has engaged in conversation with us a lot has happened with the tool. As I mentioned the tool is now openly available and the source code is openly available for download. It can be downloaded and customized and the surgeon General's monitors the so it can be completely imbedded to come into a health system architecture and used freely. The only criteria is that the interoperability is observed. So it has to be compatible with the old version of the tool. So the source code is available through NCI's website and Ken Vito has been heading up this project so HRQ also has some interesting projects around the Family History tool and I am sure that Gerveneet can fill you moron this and there is a project looking at a point of care -- can filled you in more on this and there is a project looking at the risk of breast cancer by virtue of family history collection and PURSA has a project that focuses on improving tools and education around family history in the child health environment and I hope that all of these will come together and be compatible over time so that folks can share information across these platforms. And again, there are bullet point that you can read over. So I think many of us are thinking about the next stop for my family health portrait. And that is to begin the development of some very basic open sores interoperable risk -- open source interoperable risk modules. And we have started discussions around colorectal cancer and any discussion about it in the people who are baseline risk is a good thing if they come to their health care provider and come and talk to them about it because our screening rates in general are subpar. And we can begin to tease out the people who have elevated risks and should be in an accelerated screening program. This is in the drawing stages and I cannot say this will come to pass because there are a lot of potential barriers to creating this type of resource in a federal environment. So, conclusions, family history is a potentially powerful tool and I think you know that. And I think that you know that family history will not be supplanted by genetic testing in the near future and it will always be useful to contextualize all forms. Even when we have sequencing Information Family History will capture things in the shared environment that will not be bullied the supplanted by genomic Information and the evidence based will be -- there will be lots of gaps in the state of the science conference but we are on the trajectory for we can think about how we can fill those gaps effectively in a rational way. And there are many ongoing federal activities that are working on expanding that evidence base and at the same time enhancing adoption on the assumption that there will be clear utility for various portions, if not the overall picture of the family health care.
Thanks, Greg. This has been a long haul and it's good to see all of these products. Any questions or comments for Greg? It looks like you answered them all. Good luck in Maine. Think of us down here in the heat.
The last subject today is a follow up to the discussion that we had yesterday with David and how genomic is incorporated with health information technology and we want to welcome them to individuals and I am not exactly sure how you will format this, Rebecca who was from the date the Exchange standards consortium and Jessica will talk about about what is really happening in getting genetic information into the electronic standards world. So thank you.
Thank you we are pleased to be here today and I will give the first part and Jessica will give the part specific to genomics we wanted to talk about health care and clinical research and the ability of HIT to support clinical research indicates that we are doing right now with the core clinical research set of data elements and how can we combine that with clinical genomic data. So this is to remind us all, if we have forgotten, and I doubt that and the fact that health care informs clinical research and helps in for medical decisions and that we spend a lot of money on medical research right now and the requirements for research and health care and clinical quality overlap substantially. So we need to make sure that the standards that we are producing also are harmonized. And [ Indiscernible ] is involved with a clinical research standards development and we have been working with them since 2001 under a formal charter agreement to make sure that the standards are harmonized and it was mentioned earlier about one of the clapper to projects that we worked on was to create a model that we -- collaborative projects and the bridge model which is to represent the context of clinical research in the health level seven realm so that was started to bring piece closer together in the standards world. And it's based upon that model that all of this and the vendors that create those are obligated to follow that and make it conform to bridge the. This is a reminder to show was what the clinical research data looks like right now which is the fact that we have basically clinical research going on. A lot of times there is an end point of publication and then we have regulated clinical trials that have data that go to the Food and Drug and initiation or other reviewers like that data Steve the Montreal Board -- data safety monitoring board and we have health care data and they're hard to put together because they exist and paper medical records a lot of times. And research all lot of times is in notebooks unfortunately. And in clinical trials we have 50 to 60% of trials on paper and when it is collected electronically is collected by systems with different requirements. So they not only have no books and case report forms but they have an average of three different applications to collect data for their studies. And whether its electronic or papered they then have to transcribe that. So that affects quality and time and the majority of investigators who do a study said that is enough and I don't want to do another research study so we are losing a lot of potential research data because people do not want to do that trials because they are so cumbersome so that is something we are trying to address. And the objective is to share this information at least in certain intersections. And that requires that we have standards, not only standards for transporting the data but content standards so we have to semantic interoperability and that you'll be able to understand that data when the next system picks that up. This is a model that we have been working under for the last few years and was developed by Glenn and he has worked with HL7 and he was the CIO for awhile at Ohio State and he has installed a number of medical record systems and we ask him to look at the academic research. So they go over to the Duke Medical Center which then pulls -- which has not pulled the paper to her in years and bills of these paper forms. So we did a pilot there and tried to bring the forms into an electronic health records system so that the investigators could pull a case report form into their environment, complete the form for research and complete their clinical care worker at the same time so it was much more integrated into their workflow. So the idea right now is that you have a number of people working in different systems and entering data for public health, all print reports, a case report forms, CT reporting, quality measures and different forms of paper in different ways to reflect it. And what we are trying to do is replace that environment with the EHRs. And assuming that we have the right chord data set and standards we can start collecting that data within the EHR and these other systems and the transcription disappears. So this is actually being done in a number of places prevent its being done in a steady in Georgia for clinical research and being used to report swine flu breakouts to CMS and at Harvard to report adverse event to the FDA and the reporting time has gone down from 34 minutes to 30 seconds which means it's actually happening now when it was not before in most cases. So bad as the model that we have been working under partly -- so that is the model that we have been working under partly to make sure that you can use that data for multiple purposes and to eliminate some of the transcription and duplicate machinery so that you can use standards to do the interoperability. So taking that model is a step further, we try to get on to the program for several years and say, don't forget about clinical research. And that took place for about three years while we went through 13 use cases and finally about last July they said it is a good idea and we should look at clinical research. So we're kind about money so if you all can raise the funds from anyone, stakeholders interested in clinical research and we will take this into the program. So we raise funds from over 40 different contributors. So no one organization is driving this, let's put it that way. It has been very cooperative and we took it through the process to get the Hughes case written and this was delivered last April and as of this week is going through the process now to identify standards to support this. And the case that was selected by a group that [ Indiscernible ] convened last November is a case of taking a core data set and exchanging it from a EHR system to a research system. So the group decided to start there because that could provide a foundation upon which you can then build and take clinical genomics and add it on top of that and add eligibility criteria, Safety reporting. So the idea was to create an infrastructure to which health-care advances for the core research and we are leveraging the existing standards. Yesterday, in fact, they finished the requirements stage and a set of standards and that we'll go again to the process and we're hoping that it finishes up by around September, if we are lucky we have defined research. Broadly and we used basically the NIH definition. It includes epidemiology outcomes, research, and other kinds of research. And we have done the definitions of these different types of steps also broadly. So on the research side, at any site doing research. It could be a health care location, pharmaceutical company that is the sponsor, and that is the site. And the sponsor would be a company or CRO or vendor. In the research site could share that research data with Weber the sponsor might be and then that data could be used for multiple purposes whether its safety reporting, IRBs or a scientific publication or clinicaltrials.gov
[ Captioners Transitioning ] .
It's important for both specimen.
To build on the core data that Becky just told you about, we wanted to talk about the data standards with the clinical genomics, and we started with the federal government. We are starting to expand it throughout the federal government, and we are reaching out and we are interested in getting input from the federal agencies to help to get this right. The plan is to move forward with the public meeting and to get the public input on both the inside and the outside with the input with what we will need in the fall. We need a standardized terminology to move the genomic data around, contain it with the E HR, and contain not just the genetic tests and genomic experience, but to report every step of the process. In fact, every step of the process is important to understanding the outcome and the reports that are in the end. These are the working models that are along the way of putting the results in from the beginning to the end and what it means once you have it in front of you. There are standards that are being worked on for these things -- let me just back up for a second. There are plenty of processes here. This is for the handle of genomic information, the data, the analysis of the data, the gleaming violation of the analysis. There are standards for some of these things. There are -- there are -- there are on going workloads with the HR-7, and we have the genetic standardizations, family history data. And we have the expression data and we are going to move forward with the standard reporting with the genetic testing. This type of information clearly has both health care and clinical research. For the health care and tailoring that with the screening in the genetic profiling and using the genetic research for the stratification of the patients, drug tableting and the recovery. So these have to be developed in some of the aspects, the aspects that are in the model which I have shown before. But these are the aspects that will allow us to move forward with it. When we are talking about the standards, they are talked about in two different ways. We don't want to say this is how you are going do the experience, and that is the result that you will get. We are talking about the standards in a vocabulary and a language so you can interpret the data at the end. We have talked about the regulatory mandates and the lack of. We have went through the need of standards and the standards that are needed to facilitate the exchange. We have the standardized research and the health care, and you can integrate that back into the health care. The idea that we can obtain multiple standards is not particularly useful, so it makes sense to get those standards in the forward health care and place it into one and another. I want to emphasize the harmonization of the health care is critical. This is to use this across the different stakeholders, the different health care providers and settings, and if it has to do with the clinical supports, they must all integrate with each other so you know what the data is and what you can do it as we move forward. We need to have ideas on how to move forward, link the biomarkers with the characteristics and the outcomes and then to provide the clinicians with the date of care, so it is accessible for the comparative research and the evidence needed to move forward with all of the processes we have been talking about for the last two days.
So the case for the clinical research is available on the ANSI website. This is contact information for Becky and I, and, of course, we have the cast of thousands that helped to contribute to get the youth case to HIPSI. We have had a lot of people to contribute to get that work moving forward.
I will close with that.
Do we have a question or two?
Dr. Williams. I have two questions. The first one: It's relatively straightforward. After this process, is there an intent to move this across the certification admission for the Health IT. They put clinical research on roadmap. As of July, there will be a work group for EHRs. They will be using the specifications out of [ indiscernible ], and also the clinical research and clinical profile that we are validating out of HR7. Those are helping to reform the criteria process.
Excellent.
The second question I have here is from a presentation yesterday from David Bloomsimal, is there a direct engagement and representation from someone -- from you or someone like you on their policies or their standards committees.
I'm not sure how the standards and the policy committees were formed, but there are people on there that work with the health level and the HR-7 disks, it's not the research folks, but there are ones on that are involved with health level 7, and the [ indiscernible ] disk. I know one of those with on the NCI and one that understands the research and the policies as we had a meeting with John Glauscer on Tuesday, and we are hoping that everyone recommends that it stays on the agenda. We have worked very hard to get it on there. We have filled in all of the gabs. We talked about AHIC, and EHIC where you wanted in mode yesterday, so we have created our own mechanism. It has been extremely supportive, so I am hoping once we get it produced in the tiger team period, that we have going on now, that it will be an opportunity to declare the standards that are going on at the end of the year. Any recommendations that we are able to get from you will be much appreciated.
Thank you for persevering, this is excellent work.
With the interoperability and the researching part, some of these contain different forms of consents. Does who the information go to, follow the data piece all along the way?
That's a good question. I don't know that I can -- I will tell you what we are doing. There is a set of contextual submissions that go in to the HR when it is set to go in the data program and trial. That should have attached to it who gets to see what data and where it goes. It's a whole privacy and security piece that goes along with the core set data and that is basically just a set of elements and the code list that get transformed around in the three layers.
Thank you very much. These are important topics. We appreciate you coming. We will be keeping you in our agenda.
Thank you.
Thank you.
Thanks for all of your work.
[ Applause ]
Now, we come to our second public comment period, and as you all know, this is a time for us to hear from all of the public comments.
My name system Jeff Boyd. I work with early state of medical technologies. With many of my clients, I am not a lobbyists or work for a trade or a special interest groups. I am here to ensure that the companies that I work with are competing and they are working on to improve the quality of care that is affordable. I would like to talk to you about today from a perspective from someone who works in these trenches. I am here today to speak about an issue to understand how diagnostic tests are improved by Medicare.
In February 2006, there was a coverage report on the genetic tests and services. In this report, there was a recommendation made to form the tasks and the groups to set a group of principles that are made for the genetic testing services. This group had been asked to assess the type of quality and quantity of the specific evidence of the test and to establish the test in the clinical validity and the utility. I would like to focus on clinical utility. It's definition is in this report and earlier reports. This refers to the usefulness of the test and the value of the information to the person that is being tested into the clinician. Some of the publicly available plans at that time have the definition for the clinical utility as the test availability to influence the disease management of the covered member. In the earlier reports, by this group, clinical utility was defined as follows. This is taking into account the impact and the usefulness of the test results to the individual, the family, and the society. In the absence of the clear benefit of the burden, illness and the deaths, these are benefits of diagnostic delays, reproductive health planning and it should all constitute the support of the clinical utility. Since the 2006 recommendations have not been followed through, at least I have been told that, many of the payers have been filling this void for coverage. In my ideas of the diagnostic testing for the payers, this has been defined now as clinical outcomes. Establishing clinical outcomes of a genetic test provides the specific innovations for health care information and to enroll in these health care plans. Being able to establish a direct effect of a clinical task result of the health outcomes is extremely challenging and it is sometimes feasible. The tests is often confounded by the variables of use of other tests, in sequence or in combination, physician behavior, their decision making, the type of treatments, patient adherence to the regimens and following the diagnostic use. It takes a leap of faith that the results of the diagnostic tests have any effect on the outcomes. Something similar was read in 2005 to this group. These coverage are significant for these companies. First, the costs and the resources can be enormous. They signed two outcomes. The clinical test, the clinical trial cost 25 to $40 million to perform. Secondly, the time to complete the profiles can take a long time, years to complete. Third, based on the enrolled demo graphics. The other private payers may declare that a different population be studied. These are suggesting drug-like trials to match. If these are the outcomes to establish the positive termination, it will reduce the investment in the genetic tests and the marketing and the production of the new tests. These will have an adverse effect on the quality and the costs of the care. I would like to suggest the following. The secretary form the tasks and develop a set of principles and to guide it for a genetic test and resource it immediately. These principles should be communicated to the paying committee as soon as possible. Despite the reports of the health care reform, and the common health care costs, we should not establish the policies that stifle the health care innovation. There are exciting new tests that are more accurate, provide more information, and it will undoubtedly improve clinicians to make decisions. Thus, we are over all cared for and provided in an informed way. There are diagnostic genetic tests that are covered by the payers and there is no evidence that are proven with outcomes. What happens to these tests. I would like to thank the secretary for the time to present. I would like to see these become a care in the community.
Thank you, Jeff.
You should know that these are really important issues for the committee. We discuss these regularly, and understand some of the trade offs here and we appreciate the input. Thank you for coming.
Well, we have come to the end of our regular meeting. I don't have any additional agenda items other than bringing your attention to some of the things we have established over the last two days. Kathy will have those for me soon. I will have my memory tickled. We heard about an update from the task force, their process going forward, and we look forward to them coming back with some recommendations and we will have a chance to review them at the next meeting. We heard from David who took at [ indiscernible ], and we have heard the followups to his discussion, and we have drafted a memo to send back to him on the things we would like to move forward on. And we would appreciate -- can you -- that memo was drafted and we got input from many of you. We have some helpful suggestions and thoughts. And we will be getting that for David hopefully in time for his meeting next Tuesday.
Next. Next.
All right. We have set a bulk of the day on the health care issues and the genetic institutions. There are several guests that were brought to the table for the secretary as it moved forward. You can see the enabling of the corporation and to help the IT. We have the need for the evidence development in the area of genomics. And then we continued an issue of reimbursement and genetic tests. We then had a fascinating discussion after an enormous amount of work from our DT committee, and I think we went back and reviewed the report. We are going to be adding an executive summary that will really move things forward. One of those was the genetic tests, medical tests, and which is which. Where are we? We are assuring that the same level of oversight is the same as the medical care. We are going to be bringing all of that back -- for review at the meeting, and we will be putting in the appendix much of the background information that has been assembled. Today we have had a group of speakers talking to us about where the comparative effectiveness and the issues that are laid out. We have issues on those and we have discussed things about the funding how genomics fit in there. The engagements about the trial, the specifics about the genomics and the personalized population choices, disparities, diversities, and particularly to see how it fits in the patient stratification. We have talked about the need for the infrastructure and how that is put in placest we are going to -- place and we are going to capitalize that with the genomics. We have the biobanking and we have talked about the types of studies that will be developed in a more efficient standard for the clinical practice. So because that is a simple task we have --
[ Speaker/Audio Faint & Unclear ]
[ Laughter ]
We have given that to Mark Williams.
Please pardon the interruption, your conference will be concluded in approximately 10 minutes, if you would like to continue, please press star one.
[ Overlapping/Multiple Speakers ]
We will have to find a focus. These are the ones that are volunteered to be on the task force with Mark. If we have --
[ Laughter ]
We have heard from the various partners. This has been an extraordinarily productive meeting and we are here again on October 8th and 9th, here in the Humphrey building. With all of that, I wish you well. Safe travels, and many thanks for your input.
[ Event Concluded ]