[This Transcript is Unedited]
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Agenda Item: Call to Order, Review Agenda
DR. CARR: Welcome everyone to the day two of the NCVHS full committee meeting. Before we go around the room, there's a couple of housekeeping issues. Our hearing this afternoon goes until 4:00, and we need to make some plans for how we get from here to our means of departure. I think what we would like to do is, if you could, just have everybody write down what time they are leaving and where they are going. If you write it on your notepad where your departure point is, what airport and what time or plane or train, whatever your departure, then we will go around and collect that. And we will try to get enough cabs, if you want to travel by cab, or you could mention if you want to travel by metro.
Bruce, did you look up how long it takes by metro from here to the airport?
DR. COHEN: Jack and I are just going to leave at 3:30 to take the metro to National.
DR. CARR: Okay, just to remind you that it is important that we respect all the participants who are coming here for the hearing this afternoon that goes until 4:00. So where possible, I am hoping that we will have a good showing until the end.
(Administrative comments)
MS. GREENBERG: Those of you who met with us yesterday and were interested in the new workgroup, we are hoping that Todd Park will get here about 12:30, if he can. He is coming from Baltimore, and so that would give us an opportunity to talk with him, so just when you are planning your lunch plans.
DR. CARR: Okay, I will start. I am Justine Carr, of Steward Health Care, chair of the committee, no conflicts.
DR. FRANCIS: Leslie Francis, University of Utah and Visiting at Oxford, and no conflicts.
DR. GREEN: Larry Green, University of Colorado Denver, in this committee, no conflicts.
MS. MILAM: Sally Milam, West Virginia Health Care Authority, member of the committee, no conflicts.
DR. FITZMAURICE: Michael Fitzmaurice, Agency for Healthcare Research and Quality, liaison to the committee, staff to the standards and quality subcommittees. If I had conflicts, they would have to put me in jail. I'm a federal employee.
MR. SOONTHORNSIMA: Ob Soonthornsima of Blue Cross Blue Shield Louisiana, no conflict.
DR. COHEN: Bruce Cohen, Massachusetts Department of Public Health, member of the full committee, no conflicts.
DR. TANG: Paul Tang, Palo Alto Medical Foundation, member of the committee, no conflict.
MR. BURKE: Jack Burke, Harvard Pilgrim Health Care Boston, member of the committee, no conflicts.
DR. HORNBROOK: Mark Hoonbrook, Kaiser Permanente, member of the committee, no conflicts.
DR. WALKER: Jim Walker, Geisinger, member of the committee, no conflicts.
DR. SCANLON: Bill Scanlon, National Health Policy Forum, member of the committee, no conflicts.
DR. MAYS: Vickie Mays, University of California, no conflicts.
DR. WARREN: Judy Warren, University of Kansas School of Nursing, no conflicts.
DR. SUAREZ: Walter Suarez with Kaiser Permanente, no conflict.
MS. GREENBERG: Marjorie Greenberg, National Center for Health Statistics, CDC and executive secretary to the committee.
MS. SQUIRES: Marietta Squires, staff to the committee.
Agenda Item: Standards Letters - ACTION
DR. CARR: One other housekeeping issue. We have set up SharePoint, and the goal of SharePoint, going forward, is now when we have documents for the subcommittee to review, and people want to edit, it will be on SharePoint and that will assist us in version control. If you have not signed on yet, just follow the directions in the email, and make sure that you are. And then, as we have letters or things for us to share through the subcommittees or the full committee, we will find it there.
Walter, I'll turn this over to you. Wait, I have one other announcement actually. We mentioned yesterday that a number of us, six people's terms are up in June, and some of us, Judy and myself, have reached the maximum. And because Judy serves as co-chair of standards, we want to ensure the continuity of the work. So Judy has graciously agreed to step into the emeritus position, and Ob has graciously agreed to step into the co-chair position, so thank you, Ob, and thank you, Judy. Now, Walter?
DR. SUAREZ: Well, what we want to do is cover the three letters that we discussed yesterday. The good news is basically we don't have too many edits and we appreciate the comments from everyone that we received. We are going to go through each of the three very quickly, and highlight the changes that were made from the version that was distributed to the full committee.
And then, we want to also spend some time in a fourth letter that was drafted, that focuses on ICD-10. As we discussed yesterday, it is going to be very important for the national committee to make a statement about the recent announcement in the delay in the adoption and implementation of ICD-10. We wanted to do that and take the opportunity of having the full committee here, and prepare a very short letter. This will be a first letter really, of what would become a second, larger, more detailed letter later on, with respect to ICD-10. But we wanted to sort of make a statement at this point about ICD-10.
The first letter that I think we are going to review is the claim attachments letter, and I think there are only just a few edits done to that letter, mostly edits related to consistency in the way that structure of the sentences were written. There were no substantial changes made, so I don't know if you can open that.
Let's go to the ACA 10109 letter. The Affordable Care Act, section 10109 letter is the one that dealt with these four areas that we cover in the hearing. And this letter, there were two changes, one on page 3, I believe, so if you could go down. This is the section 10109.
Let's go to the first change. There's some small editorial changes, so this one is, I think, on page 3. On page 3 of the letter, on the second paragraph that starts with use of the terms enrollment, at the end of that paragraph, there is a sentence that references litigation history. And we are changing that word to malpractice claim history, mostly because not all go into litigation. So really, we didn't figure litigation history was proper. We are changing that to malpractice claim, that is one change.
And then, the second change in that letter is on page 5, under section 4, consistency in claim coding edits, the bulleted list of issues. The first issue that does not belong there, it is a copy from actually section 2 before so. We are deleting that first bullet that talks about reviewing the e-billing initiative in Texas and California. I believe those were the only two changes of this letter. Is that correct?
DR. CARR: Do we have a motion?
DR. SUAREZ: Do we have any other changes or was that it?
DR. WARREN: No, that is it.
DR. SUAREZ: That's it, okay.
DR. WARREN: Just those two.
DR. CARR: Do we have a motion to approve?
DR. SUAREZ: I move approval.
DR. WARREN: Second.
DR. CARR: Any further discussion? All in favor?
(Chorus of ayes)
DR. CARR: Opposed?
(No response)
DR. CARR: Abstaining?
(No response)
DR. CARR: Pass.
DR. SUAREZ: Great. The second letter that we will be looking at is the one that we call the DSMO letter, which is a letter addressing some of the updates on maintenance process of standards and operating rules. So here, I believe there were no changes in this letter at all.
DR. WARREN: No. I am just scrolling through to make sure though. Yes, there was one. It was brought to our attention that we had left out the word “operating rules” in this particular list. So there are transactions, operating rules and code sets.
DR. SUAREZ: So this is the only change, and we are passing it around, the revised letter with the red lines already. That is the only change in this letter. I guess I will move approval of the letter.
DR. CARR: Do I have a second?
PARTICIPANT: Second.
DR. CARR: Any discussion? All in favor.
(Chorus of ayes)
DR. CARR: Any opposed?
(No response)
DR. CARR: Any abstaining?
(No response)
DR. CARR: Unanimously passed.
DR. SUAREZ: Thank you. The third letter is the letter on claim attachments. And again, this one we had a little more changes that we made, all of them really where primarily editorial and consistency in terms of the phrasing and the style of the writing. So you will see several, in this particular one that we are highlighting here in this screen is basically creating a more sentence-like set of texts in the bullets, rather than leaving the bullets too loose. We tightened up some of that in this particular paragraph.
I think the next ones are the same thing, primarily correcting some of the phrasing and the wording and the paragraphs, but no substantive change in terms of the contents. These are all just kind of editorial changes.
I think beyond that, this one at the bottom of page 3, there was a good question about when we standard, and then we say request and response. In reality the claim attachments process, as I think I mentioned yesterday, there are sort of two ways of thinking about the attachment. One was the unsolicited way in which the attachment is sent along with the claim.
And then, there is the solicited way, which is a request is submitted by the payor. That request, there is actually a standard to submit the request. We are just highlighting here, requesting a claim attachment, and this will be the standard that would be considered. And then, the second part is the response, which is a response to a request to submit an attachment, or the submission of an attachment without a request.
DR. WARREN: So I am wondering if what we need to do with the word standard is put the standard process is as follows, just to get the same format as the above? Or if anybody has a different --
DR. SUAREZ: This particular part refers to the actual technical electronic standard, which is the current electronic standard that is being --
DR. WARREN: I am just trying to get the grammar, because the word standard still doesn't tell you what you are --
DR. SUAREZ: Good point. We need some wording in there. We can either say current standard being considered include --. I would probably say current standards. So current standard being considered include, so I would take the s at the end of includes. That is just a clarification change, I think. And I think that is pretty much, in terms of edits.
DR. FITZMAURICE: Walter, just going back up to where we were before, something about responding to a requested attachment for submitting in an unsolicited manner. Is that saying, you asked me for something, but I am going to pretend that you didn't, and I am going to send you something anyway?
DR. SUAREZ: No, the two ways the attachments are sent are I send it without having to be asked to send the attachment, so I send it in an unsolicited manner.
DR. WARREN: Does that help?
DR. FITZMAURICE: Yes, yes, yes.
DR. WARREN: There is one other one on here that I had a question for Sally on, and that is down here where she recommended we delete the word integrity. And when Walter and I looked at this, we were thinking of data integrity, which is as important as the others.
MS. MILAM: My reason for that is integrity is a component of security. I thought it was a duplication.
DR. WARREN: No, data integrity itself is you have got the right data in the right format, not necessarily that it is secure.
MS. MILAM: I guess the right data, in terms of integrity, though, is a domain within the security itself.
DR. WARREN: No, it is a domain within data entry.
MS. MILAM: So it's not corrupted data, there aren't missing elements?
DR. WARREN: The numbers aren't reversed, it's the correct concept in the correct slot.
MS. MILAM: I think we are saying the same thing.
DR. WARREN: Except I don't see it as a security issue. You can have data with no integrity still be secure.
MS. MILAM: Well, I think security is made up of confidentiality, integrity and availability domains. But however you choose to leave your language, it is up to you.
DR. CARR: I think it reflects the different disciplines that people come from and how they use it. Is there any objection to using data integrity? It's a term that we have used in the past. Let's leave it as data integrity.
DR. SUAREZ: So were we deleting integrity? No, we are not?
DR. CARR: I think what we are hearing is different terminology used in different disciplines. But I think because we have used the term data integrity in the context that you are describing in many previous documents, I think it would be consistent to leave it in, noting that actually it encompasses security. But I don't think it changes or undermines the meaning. You are seeing it as a redundancy, but I think just leave it in.
DR. WARREN: I think that was the last change in the letter.
MS. MILAM: I see that the minimum necessary was added, but it wasn't underlined. But I am pleased to see that it was added. It was in your paragraph under general concerns, third bullet. You need to go up a little bit further. I don't have that hard copy in front of me. There, in that third bullet, you added minimum necessary.
DR. SUAREZ: So that is basically this letter. I guess I will move approval.
DR. CARR: I hear a second?
PARTICIPANT: Second.
DR. CARR: Any discussion? All in favor, any objections or abstentions, passed unanimously.
DR. SUAREZ: We are going to talk about the ICD-10 letter, so I am going to turn it.
DR. CARR: I think we actually had some rich discussion yesterday afternoon, building on, as Marjorie points out, years and years of discussion. I think that we are respectful of the Secretary's decisions and supportive, and I think we want to reflect that, and offer support or observations that might be helpful at this juncture.
This is a draft of a minimum necessary letter that documents our awareness, some thoughts and keeping it at a very minimum necessary. I guess it wasn't posted, and again, this is just the work of a small group. So the outcome of this can be that we accept as written that we revise or that we decide that it's not the right time to submit a letter. All of those are on the table, but this is the straw man to try to capture some of the discussion that went on yesterday. I think we do have a fair amount of time to be able to deliberate over this.
I am going to read it, so that everyone is aware. Dear Secretary Sebelius, the National Committee on Vital and Health Statistics is a statutory advisory committee with responsibility for providing recommendations on health information policy and standards to the Secretary of the Department of HHS.
Under the Health Insurance Portability Act of 1996, NCVHS needs to advise the secretary on the adoption of standards and code sets for HIPAA transactions, including on the transition between ICD-9 and ICD-10.
That is our customary first paragraph, with the exception of the final phrase, including on the transition between ICD-9 and ICD-10. Yes, Mark?
DR. HORNBROOK: Is it important to put in the CM, because the 9 and 10 are codes of death?
DR. WARREN: Do we want CM and also PCS?
MS. GREENBERG: Well, I think it is important to put in the CM, and then after ICD-10, I think the way they have been called collectively is the ICD-10 code sets. I have been particularly asked by World Health Organization to be careful in this country of not referring to ICD-10-CM or ICD-10-PCS as ICD-10, because ICD-10 is currently implemented for mortality data, and also in many, many countries for morbidity data. It causes a lot of confusion. So throughout the letter, if we can just make that change, I would appreciate it.
DR. WARREN: But I have the wording the way you want it, right?
MS. GREENBERG: Yes, in that sentence, ICD-9 CM.
DR. CARR: And is the term, including on the transition, between, are those the right words? Including the, take out the on, including the transition from ICD-9-CM to ICD-10 code sets. Okay, any other comments on paragraph 1?
These are unprecedented times in health care. The pace of change is extraordinary, and the opportunity to improve the health and health care of our nation accelerates with each passing month. Ironically, our success in the pace of advancement has also become our challenge. As clinicians embrace electronic health records, they are learning not only how to document care delivery, but also how to use population data and how to redesign care to meet the needs of their patients.
With meaningful use of electronic health records comes a further requirement to express clinical concepts in SNOMED CT, a structured terminology that is also new to clinicians. Information technology infrastructure demands have also accelerated with this rapid pace of change, including the recent implementations of ASC X12 5010, NCPDP D.0 and 3.0. These transactions standards will bring us closer to the goal of administrative simplification. ICD-10 also supports administrative simplification as a granularity of the structure of Ford's Electronic Communication of Clinical Information, obviating the needs in many cases, for additional inquiry and or claims attachments. Stop there.
MS. GREENBERG: So the ICD-10 code sets.
DR. SUAREZ: A couple of quick comments. Where it says, they are learning not only how to document care delivery, I would just say they are learning not only new ways on how to document care delivery, because it would be too strong to say they are learning new ways – they are learning how to document. But new ways on how to document care delivery consistently, but also how to use population data, so that is one change.
There is a missing of before the ASC X12, implementation of ASC X12 version.
DR. WARREN: Do I have this sentence right, the way you wanted it, Walter?
DR. SUAREZ: I am sorry, they are learning not only new ways to document care delivery consistently, but also exactly. Yes, I think that.
DR. W. SCANLON: I think that moderates it some, but I am taking a physician perspective here, and I want to take an umbrage at the original sentence, on learning how to document care. And my solution was to insert the word electronically, how to document electronically care delivery.
And I actually question the other, the second two parts, whether this is really widespread among the physician community, that they are also how to use population data, and to meet the needs, and redesign.
DR. CARR: So let me give an example. If you are to get your HEDIS scores perfect, you need to know who in your panel has diabetes, hypertension, heart disease. If you have a paper system, it is not easy. If you have an electronic health record, you can pull a report of show me everyone who has diabetes, so that is that population. Population can be at the provider level, as well as at the national level.
DR. W. SCANLON: I think of those things as aspirational goals, if you started off, if you want to get your HEDIS scores perfect. I can't believe that we are yet, as we are talking about the adoption of electronic health records, they are not being exploited for their full potential on a widespread basis. This kind of goes further than I think we have evidence for.
DR. CARR: Let's hear from the docs, and can we get Raj on the phone?
DR. SUAREZ: I think one way to change a little bit what you are pointing to, is that part that says but also how to use population data. In my mind, if really also how to use more granular data for population health management, and to redesign care, because it is ultimately really we're learning how to use more granular data to do population health management.
DR. CARR: But let me take it back a level to Bill's question, because I think we need to break this down one step at a time. What Bill said is that he is looking for the level of certainty that HEDIS measures are a significant driver of physicians, to begin to look at population health.
DR. WALKER: I would say that Bill is right at one level. I think one thing is the verb, learning, is the right verb. That does not say we are doing it, we are learning it. I would also say that there are tens of millions of Americans, maybe 40 or 50 million, who are being managed at a population level. We can tell you, and Kaiser can tell you, when each of 22,000 diabetics had their last hemoglobin A1c. And we manage that sucker, so it is happening. I think learning maybe expresses that we are still in the learning innings.
DR. CARR: I think you are right. I think you are the 99th percentile.
DR. WALKER: But you have to remember, there are probably 40 or 50 million Americans that are at the 16th percentile.
DR. CARR: I think there are mature systems that not only have electronic health records, they have connectivity, they have informatics expertise to know how to push data at a time. I think that is the aspiration, to be sure. I think there are physicians who are just now, as we heard from ONC, getting their EHR, and they will, in time then, be learning how to aggregate for a population, in order to manage.
So I heard Bill also questioning whether we can accept there is a mandate that practitioners see the importance of managing populations. I use the term, the HEDIS measures, so I think you were questioning that.
MR. SOONTHORNSIMA: Maybe Bill's point, it would separate a panel of patients from population, so that we don't confuse the two, if that makes sense. We are talking with individual physicians here, and they are going to be much more concerned at the practice level, the panel of patients, versus the whole community.
DR. CARR: Let's think of that, and let's hear Jim.
DR. WALKER: I think we would be better off to define population. When we use that word in all of these discussions, we are usually completely unclear. Are we talking the country, are we talking a state, are we talking 21 million veterans, are we talking 2000 patients per doctor? Those are all populations. And the structure, the intellectual task of managing those populations is all similar. Obviously, there are different demands. So I think we would be better off to say a population can be the panel the physician stayed at IDN.
DR. CARR: So you are saying add a sentence that says a population can be any of the following, can be at the local, at the office, at the state, at the national level?
DR. WALKER: And this will come up again and then we have got a standard way of talking about this that makes sense.
MR. SOONTHORNSIMA: Is it just patient populations?
DR. WALKER: I would use an asterisk, I would just say population can be a physician's panel.
DR. CARR: Yes, so just a sentence. I want to hear from Paul.
DR. TANG: Is there a reason we are limiting it only to population management, versus the management of individuals? I mean, ICD-10, so I'm just asking a question, why?
DR. CARR: Yes, individual and population management, I think that is right.
DR. SUAREZ: Part of what the next statement, after population management, is to try to go to that, is really signed care to meet needs of the patients. So really, sort of managing population, and the other part was trying to get to a managerial and individual care.
DR. CARR: They are learning not only ways to document care delivery consistently, but also how to use more granular data to manage individuals and populations. It should be manage the health of individuals and populations, and then parenthesis, populations equals this. Larry?
DR. GREEN: I don't understand why this matters to this letter. It seems to me that the letter wants to get to the point that we want the delay to be brief. And it's the recent action that provokes the letter.
DR. CARR: We are going to get to that conversation. But I was looking for the physicians in the room to respond to Bill's concern that it is aspirational, that the management of a population is on the horizon or in the purview of physician practice today.
DR. GREEN: I tend to agree with Bill, that it overstates just a little bit where we are. I am more inclined, in a background paragraph, instead of arguing about where we are with adoption and stuff, what I believe is the key issue is the United States is using a classification system that is obsolete.
It is lacking, so we lack the ability to express important clinical concepts that matter to people, and that we are continuing to deprive ourselves of the opportunities to use modern medical knowledge with a classification system that very succinctly and briefly, and quite simply on a claims form, could be being used, but it's not being used. And from a clinical point of view, it's the absence of important concepts in what we are required to report that is really what justifies getting.
DR. CARR: It sounds like we need more work on this to prioritize what we say, and to say it in a succinct way. Maybe we need to talk about the finish line of where this letter is going, and then work back from there. Is that good? So knowing that we have to do more work on paragraph 2, I'm going to --
DR. WALKER: Justine, can I just raise one issue? It's it two and three both. But I think the letter begs the question. We are saying for administrative simplification, second paragraph, third paragraph, what AMA and John Halamka and lots of other people are saying is, one person's administrative simplification is another person's administrative nightmare. And so, the question is whose administration, and that is the whole argument here, who bears the administrative burden, and who reaps the administrative benefits. And so, I think at some point, we need to address that and say on some basis, we believe that this burden is justified by this simplification.
DR. WARREN: Jim just caused me to think in a little bit different way with his comment. The administrative simplification is for the patient, because what we are trying to do is get the information that we need in order to improve the health of the people of this country. Not to improve government functioning, not to create a burden for the physician, but to improve our health, our individual health. And maybe that is what we need to make clear in the letter. This is all about patients, it is not about regulation or anything else.
DR. CARR: So let's hold those thoughts, except for Marjorie, because I want to make sure we are headed in the right direction. But if you want to make a comment now --
MS. GREENBERG: One comment on the population health, and this was just a clarification since I wasn't at the meeting when this was drafted. I thought that in mentioning populations in the context of meaningful use, you were referring to not only obviously the more population approach, and I do think population has more behind it than panels. I certainly understand what Ob is saying.
But also the fact that meaningful use does require some structured communication with population health data systems, like immunization, et cetera. Right now, this is just dependent on if a physician sends a postcard or something. So there is that engagement with the population health agenda, as well.
DR. CARR: So I think that the clarifying sentence that we received, I think from Jim, to say population health may represent a panel, a state, a country, all of the above. I think that is helpful. I want to read the next.
MS. GREENBERG: But I did want to say one thing about the other thing. I understand what Jim is saying, but this letter specifically ties administrative simplification to obviating the need in many cases for additional information, claims attachments, et cetera, and that should be for the individual physician.
DR. CARR: Okay, let's hold the comments now, just read the next paragraph to see if the finish line is where we think we need to be. So the NCVHS has a long history of support for transition to ICD-10 code sets --
MS. GREENBERG: That's okay the way it is.
DR. CARR: -- because of the potential to efficiently summarize the critical clinical information, thereby facilitating administrative functions, as well as understanding of population health. We recognize the challenge before us. We urge you to limit the delay no more than one year. We also urge you to leverage emerging technology, such as Mlm's just released iMagic program, which allows clinicians to easily translate clinical concepts into SNOMED and ICD-10 code sets.
MS. GREENBERGL: Well, that is actually ICD-10 CM. I don't think the Mlm product deals with 10-PSC.
DR. CARR: And I will just read the last two lines, so we can then circle back. As always, NCVHS stands ready to assist in any way we can. We are already scheduled to hold a hearing on ICD-10 code sets this spring or early summer. We would be happy to address specific issues related to facilitation of the ICD-10 implementation.
So again, let's go at a very high level. We've done a couple of things, number one, identified that we feel that, given our long history, it is important that this meeting to say something about ICD-10. And secondly, we have tried to articulate this, acknowledging the issues that have led to this delay. And thirdly, offered up our assistance in helping address those issues. So let's just go around the room, I think, one by one. Judy, did you want to say anything? Paul?
DR. TANG: I don't think, and it's probably deliberate and I just want to make sure that is true, it doesn't address the sort of incorporation of SNOMED into the discussion and being a vehicle for conversion.
DR. CARR: Do you have a friendly amendment, as Lorraine would say?
DR. TANG: I can read the thoughts. So we agree with the importance of converting to ICD-10-CM, so that we sort of put that on the table, that it is important to billing in epidemiology. And here's the part where we sort of create the opportunity. So at a time when the US is converting to the EHR at an accelerated pace, it's important to establish a standardized clinical terminology. And we acknowledge that the Department's issuance of the -- for meaningful use stage 2 recommends SNOMED as that clinical terminology.
So what the recommendation might be is that, at the time the country is converted from ICD-9-CM to ICD-10-CM, that it leverage the work of the NLM in mapping SNOMED ICD-10-CM. And recommend a strategy, a voluntary one, but it puts on the radar where it is not at all today, that the users of EHRs use the recommended clinical terminology to code diagnoses, and use the NLM-supplied mapping to translate that or convert that into ICD-10-CM.
DR. HORNBROOK: Which is royalty-free, publicly supported.
DR. CARR: If you want to give Judy a copy of what you have, we can have that for consideration. Let's just go around the room, because I want to get the feeling of the entire committee on is it right to have a letter, is this the right direction, and any other comments?
DR. COHEN: I think it is right to have a letter, and as strong a letter as possible. Now, the question, going back to the issue that Judy and Jim raised, is the goal of ICD-10-CM to improve individual health? And if that is the case, we should say the committee is supporting a small as delay as possible, because we feel not only the focus should be to improve patient health, as well as facilitating administrative functions. So if we truly believe that that's the goal of rapid implementation of ICD-10-CM, the focus should be on the individual health and the population health.
DR. CARR: Jim, I'm going to just go around the room, because I think we have to have all voices heard, and out of that will emerge the kind of collective wisdom.
MR. SOONTHORNSIMA: I believe there are two running themes. One is a sentence that tries to describe SNOMED, but I believe that sentence really, what we are trying to do is help harmonize the clinical context systems, whatever it is, in this case SNOMED, with the classification system, ICD-10. That is one goal.
The second goal is really to facilitate and expedite the implementation of ICD-10 with limited delay. And I think that is what we are trying to say in this letter. What we need to clarify is we also urge you to leverage the emerging technologies. I think what we need to say, what is it that we want that system to do. Isn't it to harmonize? That is the point I was trying to make. Is it to harmonize the classification system with the clinical context, and limit the delay. The only comment I have, which may be open for question later on, is why a year and how did we pick that one.
DR. FITZMAURICE: A couple of things, one that I might consider even eliminating mention of SNOMED. Our focus is on the decision in front of the secretary right now. And then, secondly, the sense that we urge you to limit the delay. I would say, if you choose to delay, which means we have some questions about whether it should be delayed or not, but if you choose to delay, no more than a year.
But also allow ICD-10 to go into effect, because people can use ICD-10, but delay the mandatory use of it for a year, if that's their choice. That would recognize the tremendous investment that has already been made in ICD-10, and that people could use it and get something back for that investment.
MS. MILAM: I agree that the letter is important. I think it could benefit from some additional framing, in terms of impact and risk benefit analysis.
DR. GREEN: I would like to see us have a letter. I agree with particularly what Mike just said about how to make the point. I like that if condition, or if you decide to delay. I really don't think we need most of what's in paragraph 3. I think it should be greatly simplified.
And one other thing is, I think the letter just needs a sentence or two that takes care of June Walker was saying. We need to indicate an awareness and appreciation and sensitivity to the fact that this solves problems for some people, and makes problems for others. But the position that I would like to see the committee take is that aware of that, do it.
DR. FRANCIS: I am not sure that it fully captures the sense that what is behind the delay is that people feel like they are having to meet lots of demands at once. And on the positive side, I would suggest anything we can figure out concretely, and maybe the iMagic is and we can frame it that way, to suggest ways of helping coordinate all the things that people are having to do. So if you are going to delay, don't just delay. Figure out how to make use of the delay in a constructive way that actually helps people put it together.
MS. GREENBERG: I think all the comments have been good. I actually, although it may overstate, it may be more aspirational than actual, I thought that some of paragraph 2 actually was rather eloquent actually almost. That'd be too strong a word, but in capturing the very issue that Leslie just mentioned, about all the different demands that are on people.
I think my bottom line is that, and this is your decision obviously, it does seem appropriate given your responsibilities at this point to make some kind of a statement, but I really do think that, if you want to do that, you need to do it now. And it could take a few months, writing the perfect letter, but I would say that it probably have no value.
DR. SUAREZ: I agree we need a letter. I think at this point, the main thing the letter can address is the time, how long this will be. I agree that framing it as the delay should not be more than a year would be important. But I think there are a couple of other things that are important to mention, that haven't been clearly stated perhaps, or at least I haven't heard it.
Number one, I think that is maybe what the second paragraph is saying, is we continue to believe that we must, as a country, convert to ICD-10. That is a statement that we have present, just to ensure that the idea that maybe we shouldn't even go to ICD-10, so number one.
Number two, in one sentence or 15 words, we say we urge you to limit the delay to no more than a year. We don't give reasons for that. We want to say a couple of short sentences about because, and the big because is any delay will delay the ability to benefit from the transition, and will increase the cost of doing health care business in this country. And we can elaborate more on that, but I think we need a statement about the reason why the delay should not be more than a year.
The second thing is, Mike, your point, at some point there was some discussion about well, maybe there should be a way to allow people to ICD-10 and also ICD-9. The worst thing that can happen in this country is if we have a prolonged dual system. That would be more expensive than anything we might have ever thought. Normally, with other standards like 5010, yes, we could handle 4010 and 5010. In fact, that was the idea. We had a year to allow to do that.
But with ICD-10, my suggestion is that we need to emphasize that the delay should be no more than a year, and that there should be a hard conversation. A hard conversion meaning minimizing, and again, given the reason to limit the need to maintain dual systems that support all a new code set.
DR. CARR: I am just doing a time check, because we are technically supposed to begin a talk on the subcommittee report. We will go a few minutes over, but if you have a bullet.
DR. SUAREZ: One last bullet is, in addition to we support the delay for no more than one year, that there should be a deliberate mechanism that ensures that, during the remaining time towards the transition, there is concrete steps taken by people to appropriately and efficiently and effectively achieve the transition. So there is not just we delay, it's we delay and people have to do the following.
DR. MAYS: I definitely think we should have a letter. I would like to see us try and keep paragraph 2 in. I think people have said kind of what the problems are. The other fix, because I didn't understand the more than one year. But I also think we recognize the challenge before us, that if we could kind of say a few more words there. I think that paragraph just needs a little more development.
DR. W. SCANLON: I have actually, yesterday and today, been more in a learning mode than anything else, listening to sort of everything that has been said, and trying to decide sort of which of the statements are hypotheses and which of them are facts. And I very much like Jim's framework, which is the issue of sort of the cost and the benefits, and recognizing that there is a distribution that is across different types of people.
I find the administration simplification argument more intuitively plausible than some of the others, that I find a stronger rationale for moving forward. Having said that, I have no sense of what the real costs of delay are, and I have no sense of sort of why a year is the right sort of timeframe.
DR. WALKER: Sir William Osler was teaching a bright young trainee, who was faced with a big patient problem, and started to rush into action. And Osler said famously what we try to teach all trainees. Don't just do something, stand there. We don't know the benefit and the cost, but what we do know is that the cost has been exaggerated by a factor of at least two orders of magnitude. The costs of making the conversion are at least 100 times greater, and this is for a very capable organization. This is John Halamka. For very capable organizations, it's at least 100 times the published estimate from CMS.
I think the first thing we ought to do is call on the director of CMS to publish a cost-benefit analysis within six months. And it would obviously be only as good as the evidence is, and the evidence is undoubtedly not very good. But I think without that, it's like Bill said, we don't know what anybody's cost is. And the benefits, we haven't thought carefully about it.
Number two, clinical communication, the standards conceptual just transmitted to ONC, which largely accepted it. A whole set of standards for communication, immunizations would be CVX, and we actually have standard vocabulary for clinical communication, none of which depend on ICD-10, and for which ICD-10 would be inadequate.
We have got to acknowledge administrative simplification and burden, and that is one reason the secretary needs to have the director of CMS make some estimate of what those are. I am not aware of any evidence, or very much feeling, that ICD-10 will improve patient care. I think there is wide belief and some reason to believe that the use of SNOMED will, but that is a stretch. But we aren't saying it in the letter, so it probably doesn't matter.
I agree with not mentioning SNOMED. For one thing, we got it wrong. The image is about translating from SNOMED to ICD-10. There is an NLM map from ICD-9 to ICD-10, which would be relevant to sort of call out as one of the things that could be more heavily publicized, so that people could make the transition easier. As far as I can tell, and I think in NLM's sense, not very many people know about that map.
MS. GREENBERG: Is that the different than the general equivalence maps? That is what the official map is.
DR. WALKER: It is by image.
DR. HORNBROOK: To be a little contrary, I think we are missing the boat here. The fact that both I9 and I10 are kind of artifactual classification systems, I10 is a lot more rubrics in it, so it gets much more detailed for clinical realism. I9, if you get and start drilling down in it, you realize that there are a lot of categories that have almost no clinical meaning, other than being different than some other category, which also has very little clinical meaning.
So the iMagic transition means that if you are inside an EMR, you're already working in SNOMED. Physicians should be working in SNOMED to describe their clinical, and we should be using that data, rather than I10. So right now, you have the ability to move physicians into SNOMED very quickly, and then the administrative business of putting SNOMED into I10 is handled electronically. Nobody has to learn I10 who is a practicing physician.
And of course, physicians right now have quote learned I9, have their favorite code buckets inside their specialty area, and that is the mental set that they are resisting change, I think. I think we have an opportunity here to make this letter much more pointed and important.
DR. GREEN: The letter should go quickly, obviously. But for me, the reason is to avoid the disruption of heavy resources that are currently in place in the industry, not just on the provider side, but on the payor side, that are vested in achieving whatever the final outcome is, whether it is a SNOMED intermediary or not. If we are getting to ICD-10 eventually, these resources have a way of being sapped away to other uses. There is a sum cost right now of people not working on this as diligently as they should. So that is one of the becauses for Walter.
DR. WARREN: I would just like to say, I had a chat with Lorraine Doo yesterday. And just as a caution for us on our speed, CMS is already working on the NPRM. And if we don't have our input in there like within the next day or two, if our comments are not considered, then these options may not be of the NPRM, and they will be off the table. So we do have a timeframe here that we need to expedite this pretty rapidly.
DR. CARR: So I think one thing that I heard that I believe that we have consensus on is that if there is a delay, the time should be used constructively to address the issues. Do we agree on that? That is one.
Second, do we agree that we want to mention, as was stated in the beginning of that paragraph, the recognition of the consequences of our own success, in many ways, our capacity to accelerate change is now the challenge that we are dealing with, because so many things are converging at the same time.
DR. WALKER: Someone else sort of said it. I think we would be better to say there is substantial cost being incurred by many entities, all of which have significant other demands on them. I think that is enough to say.
DR. CARR: Well, the only thing I would say is that, there is a lot of passion and emotion here. I think it is important to say that because we have been able to be nimble and make changes and move quickly with high-tech ACA, I want to put that forward, that that is the good thing. But the unintended consequence is that everything has come to at the same time.
Then, I think hearing different points of view is the what gets better with ICD-10 and for whom.
DR. SUAREZ: Did we agree on the one year delay?
DR. CARR: No, we have said two things that we agree on. And I think we agree that in this room, there are varying perspectives on what gets better and for whom. And perhaps what is true is that the what gets better, do we have consensus? If we say what gets better, with this classification, we would have more granular description, right?
DR. WALKER: Chris Chute has done a study that demonstrates that that is way overstated. There is some marginal benefit, in terms of clinical resolution, but it is far less than people believe. And they reproduced a study that was done three or four or five years ago, and came to the same conclusion.
DR. CARR: So we can say it is more granular, but how much, we don't want to put a modifier on that. Obviously, if we have it, it aligns with what the rest of the world is doing. And is it true that, if we have this granularity, the need for claims attachments could go away. Walter, you reflected that if we don't.
DR. SUAREZ: It won't go away, but it will be reduced. I expect that will be hopefully the outcome, because I mean we are going to have more granular data. And going back to what Judy said, which is we need to do this in the next day, and what Larry said, which is what is relevant in this letter, what is the important relevant point? And the important relevant point, we can argue and we can bring back.
DR. CARR: What I am trying to do is a strategy, let's just say what we agree on.
DR. WALKER: But I want to address the claims attachment. Saying the procedure that you did or the thing that you did more precisely does not mean that you have answered the question, what was the justification for doing it. I think the idea of the claims attachments will decrease needs to be seen.
DR. CARR: It's not substantiated. So let's step back from that. Is there any other statement that we heard that every person on the committee agrees with?
DR. FRANCIS: I wonder whether people agreed with the comment about trying to use any delay constructively.
DR. CARR: We said that, that was our first point.
DR. FRANCIS: Well, I wasn't sure that you had said that.
DR. CARR: That was the first that we all agree on. If there is a delay, use the time constructively. What was the second point?
DR. WALKER: I think we might be able to agree on the dimensions of the cost benefit analysis. There are some costs that have been mentioned, there would be administrative costs for provider organizations, different costs for different sized organizations. There is the payors who will have costs.
My guess is that CMS's costs might be greater than private insurers, but I don't know that. But I am guessing that their information ecology is enough more complex, that that might be the case. Anyway, we might at least identify the elements of costs and benefit that we believe are relevant to consider.
DR. CARR: I think in response to that, what we have heard is that there are costs for those who have not started, there are costs to do it. For those who have got it done, there are costs to maintain. So there is cost going to be incurred, regardless of what the next step is. And the question is, by whom?
DR. WALKER: How great? Maybe they are orders of magnitude different, maybe they aren't. I don't think we know.
DR. SUAREZ: The question I still have is, what is the relevance of that to the fact that the delay would happen? Are you making that argument because we think that the delay should be longer, or are we saying that we shouldn't even go there because --
DR. WALKER: It is specious to recommend a length of delay if you have no agreement at all on what the costs and benefits are. That is all.
MS. GREENBERG: Well, first of all, the department's press release stated that ICD-10 codes are important to many positive improvements in our health care system, et cetera, et cetera. Now, I think the committee has to think whether you just disagree with that. Certainly, there are members of the committee who clearly do disagree with that. I think you are reopening this fundamental question, which even the press release seems to have settled from the compartment's point of view and the rulemaking. I think that is something that you need to think about.
Also, I believe that whatever you think about ICD-10-CM, and you can find studies on all sides of this, there does seem to be a recognition in this committee that we need to move to more modern code sets and terminologies, a greater linkage between clinical concepts, SNOMED CT and the ICD. The ICD is not going to go away, unless the US completely turns its back on the rest of the world. The ICD, in different versions, is being used effectively around the world. And those countries are getting better health care outcomes than the US in many cases. I think we have to pause, if we don't think about.
And ICD-10-CM is definitely a pathway to greater convergence between robust clinical terminologies and modern classifications. ICD-9-CM is not. I think before you trash the entire ICD system, I think you need to put this in the context of what you are saying.
DR. CARR: I think we are converging on things we can agree on. Paul and then Bruce?
DR. TANG: The time emergency, I think, is moot for us in the sense of the NPRM is going to ask for comments on the delay. We will have the time to give a more measured response to that. So we don't have to hurry up and say hey, don't forget to ask about the delay. That is the whole purpose of the NPRM, so I think that is actually moot.
We either say something about SNOMED, or we even say not to forget about ICD-10, but forget about the issue in terms of converting from everybody's use of ICD-9 problem list(?)to everybody's use of ICD-10 and problem list, and just forget that stuff.
Departments are already on record for saying let's go to ICD-9-CM to SNOMED for diagnoses. Let's just accept that. They already are working diligently on doing the mapping. In a sense, it becomes almost the proposition is we do better, it's almost a non-issue for the frontline clinicians if we do it this way. So we either make that bold recommendation so that you can include it in the NPRM, or we don't. We don't have to worry about saying don't forget to ask about why the delay.
DR. CARR: So your point is the timeliness and it impacts on what goes into the NPRM, and clearly the delay issue will be in there already. Bruce?
DR. COHEN: I agree with Marjorie. I don't think we have to address the importance of converting to ICD-CM. I can't speak for the clinicians, but from a population health perspective, it is being used to measure more free-standing morbidity all over the world right now, and it will continue to be. I think that is not an issue. We just accept that going to ICD-CM is important.
Also, I think talking about SNOMED is a real distraction for this letter. That is another issue, again we are talking about the clinical aspects of it. And the bottom line is, do we want this delay to be as short as possible? I'm hearing actually a couple of different things about that now. One, that some of us fundamentally just accept that it should be as short as possible, because the longer we delay the greater the cost will be for implementation. And others feel that perhaps that is not the case. I would like to get a consensus from folks.
DR. CARR: I think perhaps the length of the delay is less important than the things that need to be addressed within that delay. We want an efficient, timely adjudication of the financial burden that is being held by two groups. That needs to be understood and managed. I do think I agree with Paul that SNOMED, these data come from clinicians. Clinicians are the ones that are being asked to retool how they document. And the burden on the clinicians to learn this in the community practices is in play here.
I think to Paul's point, pointing out that we could take that off the table if we could make tools of presentation layer, as Jim described, that is a piece of it. Paul and then Walter.
DR. TANG: So just to restate something in a different way, which may actually provide the way to say this, which is, if we instead focus on SNOMED instead of a conversion of diagnoses from 9 to 10, we will be aligning and harmonizing with other federal rules, which is meaningful use. That would be a way of stating this.
DR. SUAREZ: So just in the interest of time here, too, I would suggest the following. Ultimately, what we are trying to do is recommend to the secretary certain things to consider, to include in NPRM. At the end, that is what we are saying. Anything else, we can talk about all sorts of other things, and go back to cost benefit analysis and documentation, that was actually included in the 2005 publication of the regulations that called for ICD-10. Actually, it was 2007, I believe it was.
There are all sorts of background that I think could create more noise. What I think we can recommend is the secretary is to consider including the following five things in the NPRM. Number one, the delay, and that it should not be more than a year, or the shortest as possible, preferably no more than a year. Number two, that the NPRM should emphasize the importance of the role of the SNOMED in the EHR and the translation of the SNOMED according to the ICD-10 for billing purposes and administrative purposes, and the need to establish requirements on the EHR to be capable to do that. So include something like that in the NPRM itself.
Number three, I would argue that the NPRM should include specific steps to achieve the meeting of the new deadline, and that should be established in the NPRM. Number four, I think that NPRM should also state basically how the federal government itself will intend to meet the deadline and expect that, for example, Medicare would not accept transactions that come in the standard that are using the old code set. And that gives a sense to the industry that this is going to be a deliberate way of having everybody move to the new change.
And the last thing I think you need to include is that the transition should be a hard conversation transition, that there should not be a dual system. We all know that we are going to have to go to a dual system, but that the length of the dual system will be directly related to the cost that this transition will incur.
I think what we can suggest is recommend the type of things that should be included in the NRPM, and then just move along. We are going to have to have the chance to comment on the NPRM, we are going to have hearings that will bring up new issues about this whole thing. But I think we should concentrate on the four or five things that we should have.
DR. CARR: I think you are right, I agree. I think we should have a letter. I think if we articulate these are the concerns that need to be addressed during that delay as quickly as possible, we don't even need to express consensus on which is more burdensome, the expense to the industry or the expense to the doctors. We simply say the expense to industry and clinicians needs to be well understood. And we need to create a roadmap that will achieve success. We need to identify the roadmap that will achieve success. We need to harmonize around the clinical terminology direction of SNOMED with a seamless backend to take the work out, but to use that mapping. Do I hear any objections to putting those three things? Walter had some other things, but those things that I just mentioned.
DR. WALKER: So we are recommending a cost benefit analysis, based on the new information?
DR. CARR: I think we are not going to go as far as that.
DR. WALKER: Then I want to point out to us that the whole reason we are talking about this is because AMA deposits a different cost benefit analysis than others do.
DR. CARR: Understood.
DR. WALKER: So this is all about estimated cost and benefit, and for us not to mention it is silly.
DR. CARR: I don't think we want to be as granular as do this, do that, do the other thing. But address, adjudicate, understand the concerns on multiple fronts of the costs, the cost of continuing in two systems, the cost of converting to the new system. I don't think we need to get any more specific than that, but just to say that.
DR. TANG: On your last one, about terminology, was there an ask in the way you phrased it?
DR. CARR: What would you suggest?
DR. TANG: If the theme is let's take advantage of this, if there is a delay, let's take advantage of it to do something constructive. I would actually put in language that says here is our recommendation for your consideration of what would be an alternative, but we view a constructive approach.
DR. CARR: Again, I am trying to keep it as objective as possible. But SNOMED is the way meaningful use is going, we're asking that we harmonize with what we have already said.
DR. TANG: That's the ask then.
DR. CARR: So are we in agreement with that?
DR. TANG: Yes.
DR. CARR: That we have already committed to SNOMED, we harmonize with that and facilitate with whatever back end mapping.
DR. SUAREZ: This is a fundamental component of this, yes.
DR. CARR: Walter had two other things, we are going to talk about that, and then we are going to stop and go onto the committee reports, and come back. Over lunch, we will try to put this together. But you also were specific in asking that it be addressed to meaningful use. Again, I think to do that, I thought you were saying that --
DR. SUAREZ: I was referring to what Paul had --
DR. CARR: You also said that we avoid having dual systems.
DR. SUAREZ: That there be a hard conversion, and we need to use those words.
DR. WALKER: That is back at cost benefit analysis. You have got to understand that for the provider, you could easily have a system, where the provider is allowed to provide either nine or ten, and it is the insurance company's problem. So there again, it's whose cost, how much, and it is being assumed.
DR. CARR: I think we agreed on three important things, and if we say those three important things in a timely fashion, with a letter going out today or tomorrow, we will have added value, brought something new to the table, informed the NPRM, knowing that when the NPRM comes out, there will be ample opportunity for us to have a more in-depth discussion. Any objections to that approach?
DR. SUAREZ: So just to clarify, the next step we are going to take this letter, draft it and have executive committee -
DR. CARR: No, I am going to see if we can do it over lunch. I would like to have it looked at before we get out of here today, a draft. So we are now going to move into the report outs of each of the committees, and we are going to have to be doing some parallel processing here. So Judy, if you can kind of call out some of those things. And I am going to ask that we keep the kind of opening sentences in section 2, paragraph 2, about this is an unprecedented time.
Paul, would you like to report out on the Quality Subcommittee?
Agenda Item: Subcommittee Report outs, Strategic Plans & Next Steps
DR. TANG: I could go to conclusion recommendations or I could stay at some of the observations. It's up to you.
DR. CARR: Why don't you take eight minutes?
DR. TANG: Christine Bechtel from National Partnership, started out with the story of her trying to find her own doc, which was very illustrative. I will summarize her journey in this way. There is a lot of information out there, varying values. But even the most motivated, knowledgeable, persistent consumer can't find information useful for choosing physicians in hospitals. That is sort of the bottom line of her experience.
The cause of that, complexity of information makes it impossible to understand health-related metrics, whether it is to choose a plan or to choose a doc. And the way it is told, the legalese, the academic way it's told makes it, once you even find it, impenetrable.
One of the enlightening things that came from consumer union was in their surveys, basically coverage concerns and non-profit costs quality. The implication is important to us because they are not even going to get to the measures that we are talking about. So that, we have to consider, that an important ask of panelists were that measures needed to be designed with the patients, for the patients and tested by the patients, just a design principle.
Measures that were important to consumers are things that not a general like how are they rating, but things that they could apply to them individually, their specific conditions. These all place requirements essentially on the measures that matter to consumers. A big impediment to these measures that consumers could use if they were meaningful to them, are the lack of standards and the cost of prosperity tools. We had someone from the Physical Therapy Association, the vast, all of them, except one, had a license cost to it. So the topic of, well, gosh, if this was paid for by public funds, why all of a sudden are license fees getting in the way of their appropriate use.
The movement in population health status needs to be dealt with at a community level, strong voice from a group from Rochester, very strong community. We heard it from CVHI, as well. And some notion that the experience of care is better than a patient set rating. We have to, as health care professionals, do a better job at learning how to engage, activate patients, and it may not be with simple scores. And of course, no one pays for outcomes or improvement, so therefore nobody wants to measure it.
So some conclusions in the lumping style, is that consumers and patients don't have access to the relevant information they need to help them select their health care team or insurer, or to make informed choices about their care. So what is out there is siloed, complex and hard to understand. That is the conclusion.
To support health reform, both patients and payors need standardized, understandable, useful measures that matter to me, and usable things that I could actually understand and interpret. The lack of standards in propriety interest in measures that do exist inhibit or prohibit the development of useful comparative information at any economy of scale. Somebody might decide to spend money on this measure, so they can't combine them.
Recommendations, first is to take advantage, we do have ACA. There are going to be insurance exchanges, many or most insurance exchanges are going to be federally supported. So therefore, not only does the government have a stake in, it has a say in the health insurance exchange rules. Our proposal then is that the insurance exchanges have standardized comparison benefit tiers, with clear, easy to understand comparison charts. These tiers have a specific standard benefit description, that doesn't mean any plan can't add up to any of these tiers, but at least gives a consumer patient the ability to compare plans at some kind of standard level.
At a minimum, there would be a nutrition summary like, that appears on the can, a way of saying what would be the reimbursed, give some transparency into what the insurance company pays the provider, and the out of pocket costs for someone on this plan for these common transactions. That could be very illustrative, but that is saying it more specifically than, let's say, let's be transparent with cost. Again, that goes back to understanding by the consumer.
A second recommendation is that again, for all of these federally-supported health insurance exchanges, that they also publish, we will just call it next generation measures that matter to consumers, and will describe how those are created, in a standard form, it's easy to read and understand comparison charts that would include things like demographics and location we know are important to them, quality measures of the kind we are going to describe, experience measures, and that these publically reported measures be standardized, free of licensed cost, and include condition-specific measures.
Recommendation 3 is that we take advantage of what already exists that, as I said, were siloed. So on the same webpage for these insurance exchanges, that there be consolidated federal and federally-mandated reports, such as whether they are already meaningful use qualified, the PQRS scores, HCAP, CGCAP. In other words, the things that people were having to report anyway, but consumers can't actually even get their hands on. That beyond this single side with software, and here is the ask, to help them visualize consumers, visualize data in meaningful ways. So ideally, you could plug in some of the parameters important to you, and you would end up with, well, what does that plan look like for you? It's a little bit like the Medicare Part D thing.
So these things, we thought one, take advantage of something already in progress and mandate, i.e. insurance exchanges, and take advantage of data already there, and report it. But make them much more understandable, much more tailored to the individual.
So the second set of major recommendations really our conclusion was we do not currently have measures that matter, just like we don't have measures that matter to clinicians. We have to develop consumer measures. There is additional research and development needed to understand the factors that consumers use to make health plan and provider choices, and how to support those decisions with appropriate information. We need training materials or software to be developed, that would support the consumers' assessment process about health-related matters. And these measures should be developed with consumer input and tested with consumers. So that is sort of our what can be done by 2014 and what can be done with future research agenda.
DR. CARR: So again, I think it was a great model to have time to deliberate the day after the hearing. That was great, and it shows what you synthesize. I think what you are doing also ties in nicely with what Todd Park is trying to do. I think it is almost a perfect use case for what they might be thinking of. And so, you'll be putting together a report or a letter?
DR. TANG: We will put together a letter with these elements.
DR. CARR: And do you have any immediate plans for another hearing at this time?
DR. TANG: We do not. Let me make sure other people on the subcommittee have anything to add to what I summarized.
DR. COHEN: Great summary. The question is, it was a rich discussion, I don't know that we can convey it all in a letter. I would like us to think a little more about whether there can be, I don't want to spend a lot of time doing a full-blown report. But maybe there is something between a report and a letter, to capture the richness and subset plans for the future.
DR. TANG: So the process we thought we'd do to accommodate that which is let's get the letter out, because that is one of the things we have. And then, if we find such rich and voluminous things we have left out, we either create an appendix or an additional report. How does that sound?
DR. CARR: Very good. All right, Populations?
DR. GREEN: We did three things. We planned our workshop five days from now, refined the questions, the background, identified where we still had gaps, and got it to a point where it can still be posted and ready to go. The second thing we did was have a discussion about dissemination of our working reports. I think the crux of that discussion is there is a performance gap for NCVHS, that after NCVHS does good stuff, almost no one seems to know about it. And we don't have a systematic way of defining what Justine often refers to, he's a customer for this report.
And at least this subcommittee of the full committee believes that we should get much better at knowing who needs to get reports that we do and the work that we do, and that we should adopt a multi-faceted dissemination system. We miss Linda Klaus. She provided us with a template, and the committee agreed to receive the template by email. And over the next few weeks, we plan on circulating this template to identify potential audiences for NCVHS work, population work in particular, and how that might go. And we will continue that discussion.
The third thing we did is we had a robust discussion about what we might want to do next. There are eight possibilities, and we are going to try to summarize those and get them circulating with the committee again, so that we can look at prioritizing some next steps. They are pretty much unified around the communities and learning health system.
The committee feels it is totally capable of addressing more than one thing, and so we are excited. Vickie has done yeoman's work here in getting this workshop together for next week, around the SES stuff. So the committee, I believe, feels comfortable, feeling like we can run on parallel tracks with more than one thing at the same time.
DR. CARR: I don't know if you and Walter have had a chance to speak, because there is some work on population health standards, or public health standards that, --
DR. SUAREZ: We haven't talked about it, but I mention it in my report.
DR. CARR: We want to make sure that that gets in the mix of the discussion. Anything else to add? Great job. I want to go to Privacy.
DR. FRANCIS: Just very briefly, we are planning a hearing of the 17th of April. With having learned from Quality, the hearing will be on the 17t,h and then there will be subcommittee discussion on the 18th. The topic is next steps for community data use. Our audience is local communities who want to use data.
Our problem, I will just go back to saying, trust, and our focuses are going to be what do we know about possible modes of governance, that would be beyond data use agreements. What do we know and could recommend about dealing with the problem of small area, and potential problematic inferences. What are good ways of communicating to the public what uses are being made of data. And finally, what is known about, there has been some pretty significant research and there also are groups with some important views about.
So what do we know about people think about what would surprise them unfairly, with respect to data use. That is on the table for the 17th. People, feel free to enhance the accuracy of my summary, but that is a rough quickie.
MS. GREENBERG: I just want to say I am so pleased that the quality subcommittee really set the standard for leaving time and actually setting aside like a half day for processing what you hear in the hearings. I think that is so important. It is something that we have tried to encourage in the past, on the staff level, but we recognize that you all have day jobs, et cetera.
But I think in the long-term, it is a very efficient way to use your time, because you are already here, and we all know how difficult it is to schedule teleconferences and all of that. And also, how you can kind of forget what happens when the days go by. So I really strongly support that and we are glad to work with you, to accommodate that for future hearings by all of the subcommittees.
DR. SUAREZ: Okay. Actually, we have prepared slides and a lot of animation and all that, but in the interest of time, I am just going to talk. So very quickly, the subcommittee on standards, we are looking at the follow activities over the next year basically. We just completed, and thank you everyone for your engagement and participation in the letters about claim attachments, section 10109, and the standards and operating maintenance process.
So the next step is going to be very quickly complete the process for identifying and recommending and coordinating authoring entity of the operating rules for the remaining transactions. And then, bringing that recommendation very quickly back to the full committee, and we expect that to happen in the next two months actually. We are going to be moving very aggressively on that, because of the timing of the development of those operating rules for the remaining five transactions.
We are going to be developing, as part of the letter that we just approved, a strategy for the section 10109 next steps. As you recall, the letter called for committee to develop a strategy by June of this year, so we are going to develop that strategy and what needs to be put in place, in order to address all those five areas on section 10109.
And then, as we mentioned, we are going to hold a hearing in June, around June, we don't have the dates yet. And this will be a relatively large hearing in the sense that, the intent originally was to cover before the announcement of ICD-9 delay. Normally, we have ever year a review of where things are with the implementation of the standards every year.
So this year, we are going to have how are things going with 5010, how are things with going with the planning of ICD-10, how are things going with the planning of the operating rules implementation. But this particular hearing is going to have to have a dedicated component on where are things with the standards, in terms of 5010, what are some of the issues around that, and the preparation for the operating rules.
And then, I think we are going to have a separate complete hearing on ICD-10, that addresses all these questions and brings together the NPRM hopefully by then, if there is an NPRM out. We can include that, and then prepare a more detailed separate letter with recommendations regarding ICD-10 transition. So that will be sort of a major activity in our June timeframe.
And then, we are going to be working on the development of the 11th HIPAA report to Congress, which we hope to be able to finish by the fall of this year. And then, in the fall, we are going to be looking at working jointly with the population health subcommittee on a new topic, new in the sense of a topic that is separate from HIPAA. And that is the topic of public health data standards, the status of the development and implementation of public health data standards. And when I mean data standards, I refer to generally the standards are used to communicate data and messages between public health and the rest of the industry, and between the providers and payors in public health.
So we are looking at convening a hearing again jointly with population health in the fall, to invite public health groups and organizations, and invite certainly a number of other groups, to talk about the status of public health data standards. So that is our agenda, as we have it planned now. We even have an early version of the agenda for 2013, but we will just have it there. Any comments, Judy?
DR. WARREN: No, other than we are also looking at some alternative strategies for developing the HIPAA letter that, as we work with Justine, will probably be contacting the rest of the committee about how we will go about that in a much more efficient way than what we have done in the past.
DR. CARR: Right, the report to Congress, I think that is right And again, I think we ought to begin to think about what is this year's letter short, focused targeted, informing Congress, this is where we are trying to get to, this is where we are today, this is where we see the challenges.
DR. WARREN: One of the organizations that we thought of the letter, instead of the letter being drafted by the standards subcommittee, that we actually get a task force of the full committee, representing each of the subcommittees, to work on that letter, because the letter really has become one of the full committee. Initially, it was just looking at the status of implementing the standards that HIPAA had, and now it is has kind of moved a little bit beyond that because it is so involved in quality and so involved in populations. And it has always been with privacy and standards.
DR. CARR: So I think as we said before, the co-chairs of the subcommittees ought to think about what their message is. Sally, did you have a question?
MS. MILAM: I have a question for Walter. At I think it was our May community health hearing, we heard from NAHDO that one of the challenges around public health data were the differences in definitions utilized to public health, and that would thwart our efforts at linkage. And I'm wondering if the work with the standards group in the fall will take up that sort of issue, as well?
DR. SUAREZ: Absolutely, I think that will be one of the components of our focus. Thank you, that's great.
DR. GREEN: I would like to echo Sally's quote about that is an exciting proposition. I want to stake out a little territory here. I don't think we should go into that hearing or workshop with the assumption that there is such a thing as public health separate from individual health and vice versa.
This is a 100-year old concept that many people think needs to be healed. And in between now and the fall, there will be IOM reports coming out about trying to integrate public health with health care. And that can make the September meeting very timely. But I just want to advise caution about framing it as if we are going to come out with recommendations for one side or the other side. What we are really looking at is integration.
DR. WARREN: That has always been a problem for me, to try and figure out how things are different for the individual and how they are different for the public, because I see it as continuum.
DR. COHEN: I just wanted to add to that comment. When we think of public health, we should think of public health more broadly, not in its disease-specific focus, but that it embodies a quality of life and well-being in the broadest of UHO sense. This really expands the notion of developing public health standards to less traditional concepts that people envision as part of public health.
MS. GREENBERG: I might point out that your statement associated with the 60th anniversary symposium was very eloquent on these very issues, and it never hurts to go back to some of these things.
DR. MAYS: Talk about timeliness, the issue of quality of life and well-being was issued in terms of Healthy People 2020. And they haven't developed anything about that, and that is going to be the next work. The report from IOM that I sat on the leading health indicators that actually outlines recommendations about what should be taken into account, so you might want to do that in terms of also the other report coming out.
DR. CARR: So Walter has got a very full agenda, standards has a full agenda. But as populations thinks about your priorities, I think this is an important one to consider, and it might be able to start sooner and align with the Healthy People 2020, as well, or at least to inform, find out what everybody is doing.
DR. SUAREZ: I just want to say this is so exciting. I think this is really bringing us back to one of our origins, which is public health. I am just extremely excited about the opportunity to work on this particular topic this year, and certainly partnering with public health, the population of health workgroups.
DR. CARR: So a couple of things, Debbie has a couple of announcements. I want to be realistic getting this letter done. Do you have a draft that is ready? I think we agreed on the three concepts that need to be in the letter, and I think what we have to do is have the executive subcommittee sign off on the final thing. So it is those three concepts only, in the way that we heard from everyone in the room. Is there any objection to having the executive subcommittee finalize this letter, either later today hopefully or Saturday?
We went through and we said do we all agree that, if there is a delay, we need to use the time efficiently to understand how to eliminate the obstacles that currently exist. Second, we want to make mention of the fact that there are stakeholders on all sides that are bearing a financial burden. So slowing down fixes one and solves the other, speeding up fixes one and solves the other. We wouldn't say it that way, but simply to say there are stakeholders on all sides with financial challenges that need to be better understood.
And then, thirdly, that we need to harmonize on the fact that SNOMED is the clinical terminology mandated in meaningful use, and that we need to find ways to work with that and use the mapping, et cetera, to make it easy to map to ICD-10.
DR. SUAREZ: Are we going 6to be silent about the time?
DR. CARR: I think what we want to say is, if there is one, we want it to be as short as possible. But during that time, it is important to understand the following things.
DR. SUAREZ: Can we say as sure as possible, and I don't know, hopefully it is the right word, but no longer than a year.
DR. CARR: The NPRM is going to provide ample opportunity to address, I would imagine, that timing.
MS. GREENBERG: But it is also going to make a recommendation on that timing.
DR. SUAREZ: We are trying to make a recommendation about what to put into the NPRM. That is the main purpose of this letter. Otherwise, we can wait. We can make arguments about why it would be valuable.
DR. MAYS: The one thing this letter addresses that will not be in the NPRM, and if we don't send, won't even show up in the NPRM, which means no one can address it, is this whole thing of harmonizing the use of SNOMED to get us to ICD-10. And also, to call attention to the expenses of those people who already implement it, and will have to maintain dual systems.
DR. CARR: So let's have a show of hands, how many people would favor the specific language of limiting the delay to one year, all in favor? Any opposed? Do you have an alternative recommendation, either Jim or Paul?
DR. WALKER: Yes, that it be guided by the analysis of the cost and benefits. To me, it is specious to say it should be a year, when we have no agreement in this committee whatsoever about what the relevant cost and benefits are. What are the costs exactly? If we are going to bear a bunch of them, but I don't know what they are in any even semi-quantified way. So my concern is that we will just be making a recommendation, I don't know based on what, but not on anything like evidence.
DR. TANG: I guess I am a little less worried about the quantitation of the cost so much as what if she adopts this other strategy. Let's take the time to get that strategy right, that could have long-term benefits.
DR. SUAREZ: What is that other strategy, Paul?
DR. TANG: Basically focus on clinical terminology.
MS. GREENBERG: Do you want to wait until everyone in the country has implemented SNOMED CT, the hospitals and the physicians?
DR. TANG: Exactly.
DR. CARR: So this is an important question. It seems like with two objections, the consensus of the committee is --
DR. SCANLON: My issue is the specifics of it, and the notion that as soon as possible is strong language. And it can be buttressed by the fact that you point out that delay is costly. And so, I think that is the position that is totally defensible. If you try to defend a year, and people have evidence, it becomes problematic.
DR. CARR: Okay, as soon as possible, in bold, underscored. I think we then have unanimity, the members of the committee, any objections? Okay, as soon as possible, caps, bold, underscored. I believe with that, this meeting is now adjourned, and we can have lunch. And then, Todd Park, I believe, hopefully will be here by 12:30 and we will have a chance to chat about this data initiative, for those who are interested, followed by the rest of the afternoon session that begins at 1:00.
MS. GREENBERG: Is the plan then, if the executive subcommittee will final assist by when, by Monday?
DR. CARR: Yes, by Monday, unless Monday is too late, but yes, by Monday, as soon as possible.
DR. JACKSON: I just wanted to underscore what Larry reported out for the dissemination plan for populations. Really, it kind of applies to all of the subcommittees. What you will be receiving for the executive subcommittee is the template for dissemination that Linda Klaus has pulled together so nicely. And in your work projects, just start keeping the template in mind, start filling out listservs and programs and organizations and meetings that you see would really use our products.
I had to step out of the room because the tenth report is being prepared in the same manner as this, as the community report, in time for the tenth summit. So you will see that when we go to the meeting at the end of March. All of those things, just kind of keep in play to keep our materials out there to public, the folks who really want and need them.
(Whereupon, a luncheon recess was taken at 12:03 p.m.)
Agenda Item: Opening Remarks by the NCVHS Chair
DR. CARR: Before I call the meeting to order with regard to the letter to the Secretary about ICD-10, so let me just see if we have a quorum. I believe we have one, two, three, four, five, six, seven, eight, nine, ten, eleven members. And are we able to find Bruce or Marjorie?
DR. SUAREZ: Just a matter of process here, since you before lunch, adjourned the meeting.
DR. CARR: I adjourned the meeting – Marjorie corrected me. We will be just a moment while our visitors get here.
The letter up there is the usual introduction. The next paragraph, this is the thing we agreed on, and just taking us to the next paragraph, the same as we said, unprecedented times in health care, pace of change, ironically our success and the pace of advancement has become our challenge.
Nearly 20 years ago, NCVHS introduced the importance of timely conversion to ICD-10, and we are going to attach our timeline code sets. We wish to recommend to the secretary, if you choose to delay the scheduled implementation of ICD-10, you address in the notice of proposed rulemaking the following three issues. One, use the time to identify and address the obstacles to implementation.
Two, evaluate the financial impact on the communities that are ready to implement, and will carry the financial burden of maintaining two systems, as well as the financial burden borne by those who have not been able to yet begin their transition. And three, take this opportunity of conversion, converting the ICD-10 classification system from ICD-9 to 10. Do it in such a way that aligns this rule with the meaningful use rule set, that specifies SNOMED as the standard clinical terminology for quoting diagnoses.
That would mean that clinicians would document their diagnoses in EHR using SNOMED, which would be mapped to ICD-10 using the NLM-developed map on the back. And in this way, each coding standard is then used for the purpose for which it was designed, thereby helping to mitigate the ICD-10-CM user interface challenges. The NLM-developed iMagic tool is a good example of user friendly interface tool for the conversion from clinical language to the structured terminologies.
And this is four, the committee strongly urges that the issue be resolved as soon as possible. Now, this is the point that I want to raise. At the break, there was significant discussion about the impact of not including the one year. And we did not officially take a vote on this, and I realize a couple of our members have left, but we do have a quorum. So what I want to do is put to a vote for the committee, the consideration of adding the within one year, and follow the rules of the committee that a simple majority is sufficient to pass. And so, I will ask then for a show of hands regarding the inclusion of the no later than one year as stated, I guess.
DR. SUAREZ: Couldn't we make a couple of comments about that letter, or did you just want to?
DR. CARR: Very quickly.
DR. SUAREZ: The first one is this number four, the committee strongly urges that it should be resolved. I don't know that really the idea there is that the committee strongly urges that, if there is a need for delay, that such delay be no --
DR. CARR: Concluded as soon as possible?
DR. SUAREZ: Exactly, and no later than one year.
DR. CARR: That the delay be concluded as soon as possible, and no later than one year. So I want the committee members –
DR. WARREN: Where does the delay go in this?
DR. CARR: That the delay be concluded as soon as possible. I want to get to your critical point, Marjorie, so we will go back and let the Executive Subcommittee fix that. I think we understand the intent of that. We want to be respectful of our guests, and I want to just get the issue resolved as to the will of the committee, with regard to adding the phrase within one year. The delay should not be more than one year.
MS. GREENBERG: That the delay should not be more than one year.
DR. CARR: Right, that the delay should not be more than one year.
MS. GREENBERG: This sounds like the issue should be resolved in a year.
DR. CARR: Judy, have it the delay should be concluded within one year. That is the proposal. I would now like a show of hands from the committee members all in favor.
One, two, three, four, five, six, seven, eight, nine, that is a majority. That is a simple majority, and so, the will of the committee then is to include that delay should not be more than one year. Is there any discussion? So we will add that back in and send the final version to the Executive Subcommittee.
DR. COHEN: Justine, just a point of order, you might want to find out the people against and the people abstaining for the record, since it is an official vote.
DR. CARR: People against, Bill is against. People abstaining, I am abstaining, Leslie is abstaining, okay. So the committee is in favor. We will add that back in.
So that concludes the discussion of this letter. The final copy, hopefully we can circulate today to the Executive Subcommittee.
DR. WARREN: Just a friendly amendment, the delay of the ICD-10 code set implementation should be.
DR. SUAREZ: Yes, I think we need to fix the wording. But the idea is that, if there is a need for any delay, that that delay should not be more than one year. I think that is the main principle.
DR. CARR: So thank you, that concludes that. We now go onto our very exciting program of this afternoon. Let's start by going around the room, and then I would like to ask Todd perhaps to give us some introductory comments. I will begin, I am Justine Carr, from Steward Health Care System and chair of NCVHS.
DR. SUAREZ: My name is Walter Suarez. I am with Kaiser Permanente, a member of the committee and co-chair of the standards subcommittee.
DR. MAYS: Vickie Mays, University of California Los Angeles. I am a member of the full committee and a member of the subcommittee on population health and privacy.
DR. SCANLON: Bill Scanlon, National Health Policy Forums, member of the full committee and the standards subcommittee.
DR. HORNBROOK: Mark Hornbrook, Kaiser Permanente, member of the full committee.
MR. BURKE: Jack Burke, Harvard Pilgrim Health Care in Boston, member of the full committee and member of the population health and privacy subcommittee.
DR. TANG: Paul Tang, Palo Alto Medical Foundation, member of the committee, and quality and privacy subcommittees.
DR. COHEN: Bruce Cohen, Massachusetts Department of Public Health, member of the full committee, and member of the population and quality subcommittees.
MR. SOONTHORNSIMA: Ob Soonthornsima, Blue Cross Blue Shield of Louisiana, member of the full committee and the standards committee.
DR. FITZMAURICE: Michael Fitzmaurice, Agency for Healthcare Research and Quality, liaison to the full committee, staff to the subcommittees on quality and standards.
DR. GREEN: Larry Green, University of Colorado, member of the full committee.
DR. FRANCIS: Leslie Francis, University of Utah, member of the full committee and co-chair of privacy.
MS. GREENBERG: Good afternoon. I'm Marjorie Greenberg from the National Center for Health Statistics, CDC, and executive secretary to the committee. And I want to welcome all of you and am very pleased to be hosting the session this afternoon.
DR. WARREN: I'm Judy Warren, University of Kansas School of Nursing, member of the committee and co-chair of standards subcommittee, member of the quality committee.
DR. CARR: So I too wish to welcome all of you. This is very exciting for us. I think a year ago, Todd came and we spoke about many of our areas of alignment, and are very excited about our working together. So Todd, I wonder if I could ask you to give us sort of an overview of what we can expect today.
Agenda Item: How the Construct Fits Within the Department's Data Strategy - Big Picture
MR. PARK: Hello, everyone. It is fantastic to be back, and talking with you about the power of data and innovation to improve American health care. It was wonderful to speak with you all a year ago, and we are back with a lot of exciting stuff to talk about.
As we had mentioned a year ago, the department, HHS, is engaged in a large scale and growing effort to really maximize the ability for data information, to help improve American health care, while rigorously protecting privacy, confidentiality, really unleash the power of data information, to help catalyze transformation in health and health care.
And the specific form that this has taken, the kind of flag around which all of this activity is rallying is the Secretary's health data initiative, which is an effort to really turn HHS into what we are calling the NOAA of health data, in this case, N-O-A-A, the National Oceanic and Atmospheric Administration, which famously in certain circles has for decades not just collected a lot of weather data, but has chosen to publish it in downloadable electronic form.
They have made it available to anyone and everyone for free, which is then directly fed a host of innovations, rapidly growing still in the world outside of government, everything from weather newscasts to weather websites, mobile weather apps, weather research, weather insurance, et cetera.
The government made a similar play in the 1980s when it liberated global positioning system data, which of course now powers everything from Foursquare on your iPhone to super tanker navigation systems in your car and everything in between. So Healthy Initiative is the government's latest effort to run this open data, open innovation play, while obviously taking into account the very, very specific considerations that are extremely important around privacy and confidentiality, with respect to key transits of the data.
The whole idea is to encourage HHS and other sources of data, while respecting privacy and confidently, to actually make data more accessible, machine readable and used by a whole rapidly growing host of innovators across the country, to leverage the data as fuel, mashed up with other information, other capabilities, to build tools, services, programs, features, capabilities that help consumers and patients to control their own health and health care by giving them the information they need at their fingertips, of everything from how to basically pick the right provider for their family, to what the latest and greatest information about diabetes is, to clinical trials that could save their life in the area. Tools, services, programs, capabilities that help doctors and hospitals get ever better, continuously improving care, that help promoters promote health and wellness, that help researchers advance the state of the art in understanding any number of different deals, to help local policymakers, public health officials make better decisions.
And the fundamental insight that we have really acted upon is what I mentioned a year ago, Joy's Law. It is a famous law from Paul Country(?), of Silicone Valley. It is attributed to Bill Joy, who is the co-founder of Sun Microsystems and a legendary figure in Silicon Valley, who once said, no matter who you are, you have to remember that most of the smart people in the world don't work for you, which is of course true.
And if you really want to maximize social return on data, the idea here is to not just have your own smart people work on the data and turn it into tools inside, but to really have everyone who cares about health and health care improvement, be able to respect privacy or data sets. Be able to access and use that data to develop insights, tools and services that can help advance the well-being of the American people. And what we have seen over the last couple of years, that has helped the initiative rolling forward, has been living proof of the truth of Joy's Law.
What has happened as we, A) made brand new data available, B) actually maybe less successfully but equally importantly, taking existing public data that was in, say, books, PDFs and static websites, and turn it into forms useable by third parties, i.e. machine readable downloadable data can actually ingested by other websites. They are doing that, as well. And on top of that, promoting and educating the world about the availability of this data. One interesting insight that we had was about a 95 percent of innovators who could take our data and turn it into useable products and services, who didn't even know we had the data. They didn't even know that it was available to them. So we have been engaged in a whole series of meet-ups and workshops and webinars and whatnot, to get the word out about this data, both brand new data and data that was previously public, but not turned into machine readable forms.
What we have seen is an absolute explosion rising tied in innovation across the country, at a grassroots level, by non-profits, for-profits, students, researchers, universities, entities large and small, who have an unbelievable tide of activity, taken various swaths of data, and leverage it to build new features, products, services, capabilities, et cetera, to help consumers, help doctors, help employers, help journalists, help communities get the information they need, make better decisions, and improve health and health care, which has just been spectacular. And we, of course, actually I think they most notably have seen this in our annual health datapaloozas, the health data initiatives forums that the secretary has hosted. At the last health datapalooza, which was June 9th, 2011, actually at the end of a process, in the American Idol style process, where an independent panel of judges narrowed down a whole field to ones that actually fit in the Natcher Center at NIH. We got the opportunity to see 50 innovators present tools, services, capabilities that they had built, that were live in the marketplace, had sustainable models of operation, that were already collectively serving, just these 50, tens of millions of people. It was just an astounding display of American mojo and ingenuity.
What we actually say now is that if your faith in American is wavering even a smidgen, go to the Institute of Medicine's website, a co-sponsor of the health datapalooza. Look up June 2011 Health Data Forum, watch as many of these 50 videos as you possibly can, because it is the most awe-inspiring display of American mojo that I have ever seen. And certainly put it best that day, we said look, if you look at just these 50 innovations, it was just a small subset of what is actually going on. Just these 50, no one organization, no 10 organizations, could even have dreamed this stuff up, let alone have actually built it and deployed the scale that it is already helping millions and millions of Americans.
We are, in the Secretary's words, doubling down on health data initiatives. So actually after the June health datapalooza, the Secretary issued an executive order in August that asks every agency to publish a data access and use improvement plan every six months. We actually just got our first draft of plans in November, produced by senior health data leads that every university now has, and they are spectacular. They are spectacular to the point where actually, on our healthdata.gov site, which is the catalog we started about a year ago of all of our fully open data, the amount of data on healthdata.gov is roughly going to probably double in the next six months as a result. It is just the beginning.
We are discovering that we have had data that we didn't even know we had. And then we just decided that, now even people within HHS realize. And think about it, across all the agencies, of course it helps. So it's actually helping us to use our own data, on top of actually making it available, of course, for lots of other folks to do useful stuff with it.
On top of that actually, it sounds like a very -- detail, but I think it is a critically important detail, we are engaged in a major upgrade of healthdata.gov, because that is increasingly kind of the storefront, if you will, that we are using to present this data to the world. The outside world does not know how HHS is organized. They can't navigate our 100 million webpages to find the data sets they are looking for. They need one place to go. And in an act of national service, Dave Forrest, who is the CTO of the legendary Motley Fool website, has volunteered, we are paying him but very little, to serve his country, join HHS and lead over the next few months a massive upgrade to the healthdata.gov site. That is going to make it vastly more usable, and he is going to turn it into much more of a site ultimately. He has a vision for it, as an information utility of unparalleled power. We are very grateful to David, who is here today, for leading that effort.
And actually, speaking of datapaloozas, we have announced that our third annual health datapalooza is going to be held June 5th and 6th in the Washington Convention Center here in D.C. We had to pick the convention center because it was the only site that could hold all the awesomeness that his being generated. It is a two-day event this year.
And it is not going to just showcase the winners of the American Idol process. We are going to have actually panels of patients, panels of doctors, panels of community leaders, who actually judge the entries coming in for health datapalooza. But there are also going to be genius bars set up, where owners of data can actually set up shop and explain to any interested person what this data set is and how you might think about using it, what it means, what it doesn't mean, so on and so forth. It should be incredibly cool. I can't think of actually a way to have more fun than to hang out at the health datapalooza. I literally cannot.
And that brings us to our agenda for today. First of all, we are absolutely delighted to be partnering with NCVHS on this great endeavor, to maximize social return on health data. I got the report from earlier today that folks here are very excited about the new NCVHS subcommittee on health data access and use. Thank you so much for pursuing that. It is going to be extremely exciting and an invaluable aid to us and others, as we seek to improve data access and use, and improve social return on data.
And in another action beat, I am going to turn it over to the truly incredibly exciting part of our presentation. Now, Brennan is here to talk with you about a very significant move that CMS is making, a move to establish what we are calling a data and information products line of service or line of business, if you will. So to kind of put it in a nutshell, and I am saying this on behalf of the Secretary, Deputy Secretary, Marilyn Tavenner, Michelle Standard, who thought she was going to be here, but I am channeling Michelle.
We actually believe that over the long term, information and data parts from CMS should be considered to be a line of business, on the same level as Medicare and Medicaid, that is a national treasury, the data that CMS has, that can be turned into a significant catalyst for health care transformation, improvement of the well-being of not just Medicare or Medicaid beneficiaries, but actually of the country as a whole.
And then, the fundamental idea is that, as opposed to thinking of data as a byproduct of what CMS does, the idea in a nutshell is to think of the provision of data innovation products in a responsible way respecting privacy, and well-constructed and thoughtful approach, that the provision of data innovation products is actually at the core of what the Center for Medicare and Medicaid Services should be doing for the United States of America. And to make it a priority, to make something that we are very proactive about, and to work in close partnership with the health businesses broadly to make sure that the idea does help produce maximum social return, in terms of health and health care improvement.
This is a really, really, really big deal, and we are so excited about it that I can barely see straight. And it has gotten an enormous amount of support at CMS and HHS and broadly across the government. So without further ado, I should turn it over to the guy who I just can't describe how much I love you, Niall. I just cannot describe how much I love. I am going to turn it over the man, Niall.
Agenda Item: Opening by HHS Staff, Presentation on the Plan
MR. BRENNAN: Thank you very much for those kind words, Todd. Following Todd is one of the more unique challenges in health policy yet, speaking challenges. I would also add, thanks to Mark for joining me today, and thank you to the committee for letting us present on our vision for where we want to go with this.
I would like to start with just a couple of introductory scene-setting slides. None of these will be particularly earth-shattering discoveries for a committee of data mavens like yourselves, but just to put things in context. So obviously, CMS is the largest single payor for health care services in the United States, with over 1.5 billion claims submitted annually. We directly administer the Medicare program in all of its different facets and work closely with states on the Medicaid side of the house.
In addition to all this data, there will be significant additional data sources on the way in coming years. They have already started flowing to the agency, electronic health record data, Medicare advantage plan encounter data, and obviously beginning in 2014, additional Medicaid and health insurance exchange data. But it is really not just about the claims data. We literally receive billions of other non-claim data points in any given month or year. There are eligibility verification checks, there is quality data, there is visits to the website, there are calls to 1-800-Medicare, and it all represents the very wide range of data that we feel we are only scratching the surface of, both internally and externally.
Also, with the passage of the Affordable Care Act, actually prior to the passage, we had already begun a transition from a passive payor to an active purchaser of health care. We are expected to drive a new innovation in health care. And obviously, the last bullet is very important. We take very seriously our commitment to maintaining and respecting beneficiary privacy in all these efforts.
One of the first things that CMS has to consider any time it thinks about releasing data is the complex and interlocking legal framework that confronts us. And release of CMS data is governed by several different legal constructs, the Social Security Act, the Privacy Act, HIPAA, ACA, SAMHSA and FISMA. And some of them say you should do this, and some of them say you shouldn't do this. And so, it is kind of trying to thread needles that aren't always lined up in a straight line.
As a result, traditionally speaking, we have generally provided beneficiary identifiable data for traditional IRB-approved university research, to support demonstrations that we sponsor at the agency, and for quality improvement organizations. We have not traditionally utilized HIPAA provisions to make disclosures to covered entities. And as Todd so eloquently and passionately described, we believe that the result is that the health care system is not benefiting from optimal use of CMS data.
We have been active in soliciting input from key data stakeholders over the past several months. In fact, we had a fascinating and inspiring data summit, we called it, just before Christmas, where we had a whole parade of both existing and potential data users, and people who really know what is going on when it comes to health data analysis.
And so, this is some of the feedback that we got. States really need timely data for Medicare and Medicaid care coordination, but also for more general research and population health purposes. All payors claims database, other payment reform efforts, and quite frankly, the current process is not really as customer friendly as it could be, regarding getting data out to states, particularly when you view them as who are really a trusted partner with us in administering the Medicaid program.
Providers need data on the beneficiaries they serve, to permit and enhance care coordination and patient-centered care. We have made some important steps here with recent decisions to give ACOs and ACO providers both quarterly performance reports and monthly beneficiary level claims feeds. But we feel that this may only be the tip of the iceberg, and we also need to make sure that we have the necessary IT infrastructure and processes in place, to make sure that we can do that in an efficient and effective manner.
And researchers, the ones that I have talked to say that CMS data costs too much, is too old and that it comes with too many strings attached. And specifically, we are increasingly aware that our current research data process may not be designed to support this recent advent of broad-based research inquiry, big data analytics, et cetera, et cetera, where we tend to look and ask for very specific hypotheses, that may not necessarily be available on the front end. And in doing so, we are sort of again potentially restricting the ecosystem with the backend knowledge that might emerge.
The problem is not just restricted to external users. When you generate as much data as CMS does, there can be internal challenges, too. CMS staff struggle to a surprising degree to get access to CMS data in a timely manner. It can be enrollment data, it can be spending data. And we also need to harness data ourselves in ways that we never have before.
Obviously, this isn't strictly linked to the transition from a pair of claims to a value-based purchaser. But when you think of the Affordable Care Act, when you think of value-based purchasing, when you think of ACOs, quality resource use reports, the list goes on and on and on. You can't do any of that unless you have a very firm handle on your own data, and unless you are getting the most recent data possible, and you can set baselines, identify problems, measure progress, et cetera, et cetera, et cetera.
As I alluded to a little bit earlier, we have actually made very significant progress, even in the last 12 months, in terms of data dissemination at CMS. We are providing data to both MSSP and pioneer ACOs, both quality reports and monthly beneficiary claims data. This is a real game changer, as far as I am concerned, because for the first time in a fee for service environment, it enables patient-centered care. Providers will not just know the interactions that they are having with their patients, they will know the interactions that those patients are having with all of the providers.
We also have the Medicare data sharing for performance measurement program, otherwise attractively known as section 10332 of the Affordable Care Act, which will provide 100 percent extracts of Medicare A, B and D data to qualified entities for performance measurement purposes. So the really exciting part about this particular program is that, in order to receive the Medicare data, obviously there are rules.
One of the key rules is you are not going to get Medicare data unless you have claims data from other sources, that you undertake to combine with the Medicare data, and create our provider performance reports. So this creates a framework and a potential to go from the now, where providers are receiving one report from Humana, one report from Aetna, one report from United and nothing at all from Medicare, to potentially receiving a single report, done in a standard manner, covering all or most of their practice. We are very excited about that particular provision. We are accepting applications, the program went live on January 9th of this year.
Finally, and very, very importantly, we will touch on this a little bit later, too, we are trying to forge ahead in the creation of additional non-beneficiary identifiable data sets. Todd mentioned the health data initiative. CMS is a very enthusiastic participant in the health data initiative. We contributed, for the first time, hospital referral region, Medicare spending and utilization data to the health indicators warehouse, which was a major initiative under the health data initiative. We also have a lot of information on quality measures, Medicare beneficiary, demographics, disease burden, et cetera, et cetera.
You can now go to the health indicators warehouse, and for any given hospital referral region in the United States, have access to a wealth of aggregated information that, while it is not necessarily beneficiary level, it is, I like to call it, conversation starter information. Why is imaging spending in area X 50 percent more than area Y?
So all of these new approaches are really just what we feel are the leading edge of a new wave of CMS data users. In order to ensure that it doesn't engulf us whole, we are going to need to ensure that future data release processes will permit 100 percent extracts of data, across multiple years, on a routine basis, enable analysis across multiple care settings, allow for the routine creation of customized analytic files, and accommodate large increases in the number of data users and the volume of data that they are demanding.
So what is the solution? We are going to get Todd to do it. Todd is going to get me to do it. We are going to employ advanced analytics to create actionable information products. We are going to establish new policies to support more use and reuse of CMS data. We want to expand the pool of CMS data users, while maintaining appropriate beneficiary protections. For example, we are exploring the establishment of data enclaves or portals that would expand secure access to different levels of CMS data for a wide range of users. Some people might go into the enclave and have access to full beneficiary identifiable data. Other folks might go in there just to get their ACO report or their provider performance report. Other folks would get deidentified data.
MR. PARK: And one benefit, of course, being that the physical copy of the data doesn't move outside.
MR. BRENNAN: Exactly, because under current processes, we do a lot of cutting and shipping. And while we have a DUA process to a large extent, we are somewhat reliant on the good graces of data receivers, not to act in an inappropriate manner with the data, because there is not a whole lot of follow-up, auditing or monitoring that goes on with existing data users. So an enclave would be a significant improvement in that regard. I missed the punch line. And so finally, as Todd mentioned earlier, we are committed to establishing a dedicated data and information product line of business at CMS.
How will this transformation affect CMS data users? We believe it will result in data that is more timely, more accessible, more intelligent and more flexible. Will it happen overnight? No. Are we committed to doing it? Absolutely. I think it will be an iterative approach, and I firmly believe that data users will begin seeing meaningful changes in the types of products that they receive, and I think possibly just as importantly, their interactions with the agency very soon.
And if we do that, we believe that we will support CMS in becoming a data-driven value-based purchaser. We will make the health care marketplace more transparent to help beneficiaries make the right decisions. We will help providers move from maximizing the volume of services delivered to maximizing the value delivered. We will support community and state efforts to identify variations in health care delivery and take action that supports health and health care improvement, the conversation starters that I talked about. And we will help researchers of all kinds advance knowledge about how to improve health care, again typing it back to Todd's introductory remarks. We do not have the firepower to fix all of the problems, so we have to leverage the broader ecosystem.
The next couple of slides are very important personally to me, and I think for the whole concept and framework of the information line of business. We have a lot of data at CMS. And we have said, we push it out to varying degrees of success to some external users. But what many, many users really want is information, not data. And so, the missing link to generate information is analytics. We acknowledge that some people want raw data, but our data files and layouts can be intimidating, and obtaining large amounts of raw data can be expensive. So we want to explore ways in which we can provide users with the information they need, without necessarily releasing beneficiary level data.
How do we unlock our data to develop insights and information for internal and external users. And as I said earlier, without analytics based on data, we don't believe that we can establish baselines, identify interventions or evaluate progress relative to our goals. And that is crucial for us over the next couple of years.
This is just some excerpts and quotes from a publication by the Partnership for Public Service called From Data to Decisions. I feel it is just very much conceptually in line with where we are going. As they say, data is only the starting point. It needs to be analyzed, turned into information and made accessible to staff and executives, and be understandable to different audiences. And it stresses that what really matters in this context is not necessarily the latest whiz bang business intelligence tool. It is leadership commitment to making decisions based on analytics and human resources, analytic staff who can get into the data, make decisions, identify what is important, what is not, and then get that information to the people who count.
The next couple of slides are just some simple, somewhat stylized admissions of ways in which we are already trying to turn data into information. And I don't want this to appear at all grandiose. These are just readmission rates, and to a certain extent, there is a slide before this slide, which is the millionth of millionth of hospital claims that you have to comb through and link in order to generate the admission rates. But these are data on Medicare hospital readmissions from 2007 to 2010. We will have 2011 pretty soon. And one way of presenting them to one type of data user is here is a table that you can look at, or here is an Excel file that you can download and play with the numbers yourself.
Other folks are more visual, and they want to get a quick sense of which areas are doing best, which areas are doing worst. You can look at this and very quickly determine where your problem areas might be. And again, this is not just an interesting little map for research purpose. We have a $1 billion Partnership for Patients program right now, being run out of CMS, that is focused on reducing readmissions and hospital-acquired conditions. And so, we strongly feel that this is among the information that they need to be using and leveraging, in order to target the resources, and realize where they need to be moving.
The previous slide was sort of a national snapshot of what is going on in 2010, who is best, who is worst. This slide amalgamates the four years of trend data, and this is one of my favorite current slides that we have done. It tells a couple of things from this slide. What it really tells you is between 2007 and 2010, despite a pretty broad-based national discourse about readmissions being a bad thing and low hanging fruit, and something we really need to do something about, readmission rates in the vast majority of hospital referral regions in the Medicare program didn't decline a whit. So it is a call to action for the Partnership for Patients program.
And what it also tells you is that some places did get better, and some places disturbingly got worse. And if you look at the little piece of blue down on the bottom part of Texas, that is Harlingen, Texas, which is not necessarily a poster child for health systems that operate in an optimal fashion. But again, in terms of lessons learned and information, the QIO program had an intervention in Harlingen over the past few years. And they had significant reduction in their readmission rates. So we are pretty sure that there is a link there. Can we try and disseminate those practices to other areas, or learn from Harlingen? And likewise, there are areas that continue to get worse, which is disturbing, and maybe places that we need to focus on sooner rather than later.
Another example of the type of information that we work with, an example of non-claims information is we monitor the stock markets and the capital markets because CMS makes billion dollar decisions every day. And about a year and a half ago, we released a new SNF perspective payment rule. And pretty quickly after introduction, it became apparent that there may have been some miscalibration in the Rogue 4 system because SNF revenues rose dramatically by 15 percent.
And then, we flipped over to our stock market data, and we saw stock prices for post-acute care companies rising rapidly. So we worked closely with the folks at CM. They were aware, but again, we were able to bring multiple information sources to a problem, and quickly get to a solution where immediately, by the next rule cycle, we were able to adjust the payment rates. So you see the dip where CMS proposed rule, and the stock prices and SNF revenues gradually declined to historic normal levels.
Really what this slide does is just tell you in a slightly different way what I have just told you, so we don't need to spend so much time on it. So in conclusion, we are very committed, as I said, to becoming a data driven organization, to be meet both our existing and our new responsibilities. We are transforming how we view and use data, both for internal and external use, while maintaining our long-standing commitment to beneficiary privacy. We are realigning our business practices and policies to better support data information and development. And we are integrating data driven decision making into our everyday work. I would be happy to answer any questions from the committee.
DR. CARR: This is tremendously exciting. It really comes alive, all the different displays and the very simple information that you are putting out there. Marjorie, we have two reactors for the committee. We are looking for Bruce and Bill to respond.
Agenda Item: NCVHS Presentation - As Part of Reactor Panel
DR. COHEN: I certainly agree with your initial proposal that these data will be of tremendous value. I am in a state health department, so my focus is going to be less on the providers and more on state and community uses of the data. I think in your target populations for these data, you left off consumers. You certainly identified researchers, providers and state. I would certainly add community and individual consumers.
I am going to focus on the population health aspects of what you have to say at two levels. First, access to aggregated data, I think you have essentially two targets of users. You have a variety of policymakers, planners, community-based organizations, media, legislators, who need descriptive data for surveillance and policy development for community needs assessment for a variety of state and local activities.
The other thread that I will take up in a second is the researchers who need access to individual level data, whether it is all that is confidential, whether it is fully deidentified or partially deidentified, depending upon how you use those terms. I am excited about making these data more available, and I would strongly encourage you, as you liberate these data, to think about existing resources that you can build on.
And my particular orientation and bias is for aggregated data, the current existing and developing web-based data query systems. There are federal web-based query systems that are very robust and get used all the time. No wonder NCHS has vital stats, SEER stats, the EPHTN portals, WISQARS, there are an enormous number of existing data sets that meet the needs of a variety of users. So I think as CMS rolls out its product lines, it should take advantage of the approach that many of these existing web-based data query systems use, because they could address a lot of the general issues.
I think also about 25 states have their own web-based data query systems. And some of them are quite narrowly focused on vital statics. The one, Massachusetts, has data. We incorporate census data, we have hospital discharge data, ED data, we incorporate data from our Department of Education around graduation rates and employment rates. You need to consider the CMS data as one piece of the puzzle when you are addressing public and community health. They certainly need to be integrated into a larger context if providing these data with other supporting data.
I would love to see CMS develop a program to work with states to help them use and develop their existing capacity and their ongoing web-based query systems, to incorporate these newly liberated data. And different states have different levels. Massachusetts, our basic building block is the communities. Some are county level, some are census track level, some are neighborhood level. There are a variety of issues that need to be worked out. But there is already an existing infrastructure in many states that I think is an incredible opportunity to partner with these data as they become available. I would certainly encourage to use those strategies.
And these web-based data query systems, not only from state governments, but certainly the private sectors developing them, as well. And I would certainly encourage thinking about partnership, public, private partnerships to develop these web-based data query systems. They are used for community needs assessment. The Affordable Care Act and IRS requirements, requiring hospitals to do community needs assessments, is an enormous opportunity to put these data in play, in conjunction with a variety of other data sets related to understanding the public's health and quality of community life. I think the real opportunities as you move forward in developing your product lines, to think about partnering with the existing data entities who are generating this information.
Let me go onto briefly to discuss access to individual level data. I think your data enclave is spot on. Certainly, it is not a new concept. The research data center at NCHS and through Census, is a perfect example, creating a data enclave where there is confidential information, where people who need access to individual level data generate queries and get the results without actually having to hold the data. It actually benefits the user, as well as protects the data.
I would certainly, as you move forward in your data enclave strategy, again integrate it with your existing federal sister agencies, and what they have done in developing their data enclaves and providing ubiquitous access to users. It would be great if I could go to a designated research data center and get access to CMS data, as well as NCHS data, as well as all federal data. I think again, this is an enormous opportunity.
In Massachusetts, we are working really hard to develop our all payor claims database. It is being done by our sister agency, the Division of Health Care, Finance and Policy, that primarily collects and interfaces with the commercial entities. As a state agency partner, we regretfully heard that CMS current rules wouldn't allow us access to any of the deidentified Medicare data once our state gets it. I think the current regulations, as you mentioned, really limit access to the data that are being incorporated.
I think there is just an enormous amount of energy going on in developing state APCDs, that should go across the commercial and the Medicare, and incorporate the Medicaid data. I think you really need to loosen those rules around providing those data, and working with states so those data can be used by a variety of players. I think this has been a huge black hole in trying to use Medicare data for community planning in our Department of Public Health. It has been virtually impossible to get easy access to these data. I am really happy that you are rethinking your strategy for providing access to primarily deidentified data for more general policy development.
So congratulations, I am really looking forward to it. There are lots of folks out there who do state policy, who do community needs assessment, who will benefit enormously by having these data more ubiquitously available.
DR. CARR: Let me just do a check about what is the best model. I just looked at the agenda, and we have it a little bit differently. I am sorry about that. Did we want to do more presentation and then have a longer reactor time, Todd?
MR. PARK: It's up to you entirely, it's up to the committee.
DR. CARR: Why don't we go onto the next presentation then. I know a couple of folks have an early departure, so I wanted to make sure that you had the opportunity.
DR. PARK: So should we move to the data users and perspectives panel? I think what we will do now is move to the data users and perspectives panel, and then bring it back to reactions from the committee. And so, Kerry Hicks is next.
Agenda Item: Data Users and Perspectives Panel
MR. HICKS: Thank you for allowing me to participate in today's user and perspectives panel. My name is Kerry Hicks. I am founder and chairman of HealthGrades, a company built on the core principles of information transparency, provider accountability and consumer empowerment. We help consumers make informed decisions about either a doctor or a hospital, and to a large degree, rely extensively on CMS data to build the tools necessary for consumers to begin making those critically important decisions.
As both Todd and Niall indicated, the federal government collects and oversees a massive amount of health care data. This data can provide immense societal benefit, when made accessible to responsible organizations and managed appropriately within the current privacy and security parameters. There is a plethora of organizations in this country, I would argue both for profit and not for profit, which have the capability of creating enormous benefit to the health care marketplace, and ultimately to the public good, if given reasonable access, timely access, to the government's vast treasure trove of data.
A bit about HealthGrades, again just two minutes on this. HealthGrades.com is the leading consumer health care website used by consumers to find, to research, to select and connect with a health care provider. We currently have over 200 million unique users, coming again to select a health care provider to our website. In January, we had about a million visits per day. We expect that number to grow by about 30 percent per year, consistent with our past growth.
Today, we employ over 600 individuals in the major operations centers in Denver, Atlanta, New York and Madison. We work with over 800 hospitals in the U.S. As an underscored point, there is an enormous difference in provider quality. And ongoing analysis of the Medicare data is essential to both quality assessment and improvement.
According to our most recent study on health care quality, using risk adjusted Medicare data, on average there is a 73 percent lower chance of dying if you are admitted to the worst performing hospitals, as opposed to the best performing hospitals, across 17 common procedures and diagnoses. If all Medicare patients from 2008 to 2010 had been treated at top performing hospitals, approximately a quarter of a million lives could potentially have been saved.
HealthGrades is an example, I believe, of a successful public private partnership. We rely on access to a number of governmental data sets. Consumers accessing provider related information at HealthGrades will find risk adjusted performance data on all 5000 hospitals each year, for 30 common procedures and diagnoses. Hospital measure for patients satisfaction based upon the HCAP data, hospital patient safety information from 13 indicators of patient safety developed by AHRQ. Pertinent information on 750,000 physicians, gathered from hundreds of disparate sources, including data from all 50 states, and providers themselves can access and maintain their data through our physician portal.
We do enormous research on again this traffic that the committee might benefit at least from some of our learnings. And that is, 82 percent of visitors coming to HealthGrades are seeking information on physicians. Seventy-two percent of those are looking for a new doctor, 74 percent of the visitors will consider two or more physicians. Once a physician selection has been made, we know consumers act on that information. Fifty-four percent of visitors coming to HealthGrades will schedule an appointment with a doctor. Ninety-five percent of those scheduling an appointment will do so within a week, and 38 percent of those scheduling an appointment are doing so that very day.
There is a tremendous amount of consumer demand for any data that could provide comparative, meaningful information. Many organizations are gradually filling the demand where once there was a void. And if you look at just an overall macro trend, it terms of the rate of growth, in terms of internet usage, health care information is growing at four times the rate as the overall internet as a whole. So you can see again there is a tremendous need, out certainly in the marketplace.
We have partnered with the Centers for Medicaid and Medicare Services, and we enjoy that relationship. And we hope it continues to play a very large role in the process, through the development and implementations of standardized data platforms and delivery mechanisms that can make the data more accessible.
I applaud several recent efforts on this front, including the President's Open Government Data initiatives and the roles HHS and CMS have played to make the data more accessible, including the creation of HealthData.gov, the annual health data initiative conference that we have participated in every year, the data user roundtable held in December that allow organizations to share their challenges accessing and using Medicare data and providing a forum to offer recommendations on how to improve.
As CMS explores new ways to collect, package and make data even more accessible, I would like to offer some observations and thoughts briefly on what might be most useful to stakeholders of this process. The data use agreement is now indicated is in place for some data sets, such as the Healthcare Cost and Utilization Project, the HCUP family of data. But that data use agreement restricts access to only those organizations considered to be conducting quote pure research, which tend to be institutions of higher education and not for profit groups.
If other organizations were allowed to access the HCUP data, such as for profits who have the ability to invest resources, exploring ways to make the data more useful to the general public, this data would indeed be very useful to all consumers. It could, for example, provide confidence of performance information on ambulatory surgery centers, which currently does not exist in the marketplace.
We also believe that data should not be limited to purely academic endeavors. Reviewing the current data use policies is one way obviously to address this. Lack of physician's specific information, even at a basic level, meaning physician identifiers, procedures performed by and et cetera, make it difficult to provide consumers with any meaningful, clinical relevant information on physicians. The Affordable Care Act addresses some of these issues through data collection and reporting requirements, but we are still a few years away from being able to access much of this information. Indeed, what Niall indicated, the 10332 statute certainly lifts that veil somewhat. We would like to see the kind of broader application of the 10332 policy, again, making that data more available to more organizations.
In conclusion, CMS implementation of a specialized unit, overseeing data supply, demand and governance will improve on the great work that has already been done. The application of market principles, meaning a willing buyer and a willing seller, coupled with cost and quality, transparency, will inevitably lead to an efficient marketplace. I would argue, as Niall did, as well, we are still years away from that. But I think we get closer to it each and every day.
The direction announced by CMS today is aligned with HealthGrades' guiding principles of transparency, provider accountability and consumer empowerment. Health care quality can be used to improve quality and contain costs through effective knowledge transfer, based upon greater data availability. More efficient data sharing mechanisms, public private partnerships, will engage to empower consumers thorough more easily accessed and meaningful information.
The last decade has seen a tremendous evolution in terms of data availabilities. It is up to us to determine how to make best use of this data. The next decade, I believe, we will see exponential increases in uses of the data that couldn't be envisioned five years ago. And CMS and HHS are strategically applying resources to plan for the growth in this area, and indeed fostering innovation. I applaud their efforts, this committee's efforts and the direction that is being taken. Thank you very much for the opportunity to share my observations and thoughts.
DR. CARR: I have a question. On the Thomson Reuters and HealthGrades, have you ever looked at whether you come out with the same assessments of the providers that you look at?
MR. HICKS: We look at the correlation, and there is not tremendous correlation because they measure different things than what we do. They will take into account, for instance, perception in the marketplace with respect to quality, where we look at either mortality or a major complication, and only one endpoint in those 30 most high volume procedures and diagnoses.
DR. CARR: This presentation is very timely based on a hearing we had two days ago, three days ago, on measures that matter to consumers, and moved really from the long-term what is that magical measure to what do we have today. I am interested in knowing how you use consumers in developing what you put on the website.
MR. HICKS: That is a great question. So when we get a million visits a day, we can essentially survey any part of those groups in either an AB test or a strict just in a survey. And we will come up with an answer pretty quickly. I can assure you, having done this for about 14 years, whatever I would predict would be 100 percent inaccurate or wrong. But how we ultimately develop, what are those indicators.
We know, for instance, that 99 percent of the consumers coming to look at hospital quality will stop at the star ratings. We have a methodology, we have all the detail, but it is akin to Morningstar and the financial services. Once you get the answer, those of us around this table that are interested in how you got to the answer, 99 percent of the people kind of don't care. They ultimately want what is the conclusion. They will take outcomes, generally over processed measures.
And you think about again a lot of us assume or presume probably enormous health care literacy in the marketplace, which frankly doesn't occur. And meaning time to read perfusion, find acute myocardial infraction. If you had a billion dollar budget and an ad campaign, you could probably move the needle there, but not very far. I would argue, so I think that is one.
And I think the other variable is most consumers actively avoid or ignore provider information, up until the time that they need it. So their level of interest is very shallow, and then all of a sudden, it becomes enormous. So that timing of when you deliver information is a critical component, in terms of what we do and ultimately how we measure. But a direct answer to your question is either through survey or through A&B testing.
DR. CARR: Any other clarifying questions or should we continue on? Next.
DR. KELLY: It is really a delight to be here this afternoon. My name is Brian Kelly, I run informatics at Aetna. What I am going to really do is just make a couple of brief points. First, I am astutely delighted about what CMS is doing here. My talk really is entitled why data sharing is so important to making quality healthcare more affordable and accessible. And I know that data sharing is very important because at Aetna, I actually oversee our data governing. And not a week goes by that I don't get one or two requests for our data from some external, academic organization, pharmaceutical company, ACO or the list goes on. So every week, we are looking at who should we supply data to, why is it important, and I can tell you it is very, very important.
I am an absolute believer that sharing data is critical to how we transform health care. And that being able to add the 50 plus million members of data that resides in the CMS data sets will just hugely move the needle. This is how we are going to enable big data, which is going to transform health care.
But to do this, we really need a new paradigm around data sharing. And many of the aspects of that new paradigm will require public policies and a lot of consumer education. If consumers really knew how we could really help solve the affordability and quality of health care across the United States, they would, I believe, have a different opinion on how data sharing could be done. Obviously, we have to always do data sharing in a way that respects privacy, an individual's right for privacy. But I believe, and I am going to show you a couple of examples of how we can do that today.
One minute on Aetna, and I only do this because I think it is really important to understand that we are the commercial version of what Medicare is becoming. We are a health plan. We serve about 18 and a half million members. I have 73 million different people in my integrated database at Aetna, and that has huge value, and I can transform health care, and do really neat things for those members because of that data.
You can see the numbers. What is interesting on the bottom is we have 10 million members that have a personal health record, many that use that personal health record. And that personal health record is automatically supplied with all of the data we get on a member. Their claims data is there, lab data, their pharmacy data, their HRA data, and now more and more, their biometric data. And it is powered by a clinical decision support system that tells them what their preventive services have been done or have not been done, and what their gaps in care, based on very sophisticated things. We are using data all the time.
We interact with over a million health care professionals every year. And it is this data sharing between this member and this doctor, and these systems of care that is so important. The other thing we do, and I didn't realize this before I got to Aetna a few years ago, is we have 3,000 nurses and over 100 doctors at Aetna. And those 3000 nurses touch those 18 million members every week. And what they are doing is they are using this data to actually solve gaps in care and make health care better.
The last thing is that we are transforming in many ways into a health information technology company. We have invested over $2 billion in assets in this over the last few years. We have acquired Medicity, the US largest Health Information Insurance Exchange. As I mentioned before, on this integrated data set, we use a very sophisticated set of clinical decision support, what we call CareEngine, to identify gaps in care, and help route those gaps in care to both doctors and members. We have one of the largest data warehouses, and we have more health IT people focused on health care than Microsoft, Google and Oracle combined. We are using this data and we are making this happen every day.
If you go to the next slide, I just want to talk a little bit about how fast the world is changing. Two years ago, we did not have any accountable care organizations. We now have 10 under contract, we have over 20 letters of intent, and we have a pipeline of 50 other hospitals that we are in serious discussions with.
And these systems of care, which I believe will transform health care, will align incentives and the member and the doctor and the hospitals and the health plan, to all do the right thing and improve health care. They require massive data sharing. And it is not just the claims, the labs, the pharmacy, the HRA, the biometrics that we currently have. It becomes more and more granular data. It becomes that clinical data that is in the DMR. And more and more, it is going to require access to genetic information, and the lab tests around genetic tests to really make health care better.
When I went to medical school 25 years ago, I remember there was really one kind of breast cancer. Basically, you knew the person had breast cancer, you did the staging, you figured out where it had extended. Now, based on receptor testing, there are many, many different types of breast cancer, and they are treated very differently with different drugs. And if you don't get it right, you are harming the patient, you are exposing them to drugs that may not work in them, you are delaying drugs that might work in them, and you are driving huge inconvenience, side effects and cost to the health care system. So the sharing of data, and this whole new taxonomy, is really, really important, this whole concept of information common is critical.
What are we doing at Aetna to try to help this? Our basic philosophy is that we are data hounds. We try to get every piece of data that we have, and essentially what we do is we try to tie that together. So for these 10 ACOs that were already under contract, and the 20 other letters of intent, what we are doing is we are supplying our technology infrastructure, this $2 billion of investment, and now it is changing that information. We are sharing that information with the member, through a personal health record, we are doing very sophisticated decision support on it, that we are routing directly to the physician, caring for that population in these ACOs. So they know if I have 1500 members empaneled to me, they know exactly where they are on those critical performance methods that are actually going to drive long-term improvement.
We then use that same data to drive our care management nurses in what they do and what the hospital care management nurses do. We are, in many instances, embedding our own nurses in physician practices, who have access to this common set of data, who can really help coordinate that care and make a difference. That allows us to do population management, and that allows us to do risk management.
I want talk just for a minute on how this data can really transform clinical research. For the last two years, we have been one of the largest data providers to the FDA's Mini-Sentinel Project. Some of you may know what that is, but essentially it is a drug safety program. And the way Mini-Sentinel works, and it is a wonderful paradigm for how the government and the private sector can work together, and do things in a very inexpensive way that adds huge value, and protects patient privacy.
So what happens in the Mini-Sentinel Project is smart folks at the FDA will be looking at a new drug that was just released. And they will say I wonder if this new drug causes a heart attack or a stroke or liver failure or any condition. What they will do is they work with us, and we set up our infrastructure, so all they do is they send us a query that they have already programmed. And the query says Aetna, will you please look at the ICD-9 codes or the diagnosis codes for this set of conditions? And would you look for these side effects, do you see these conditions happening for a person on this drug?
In 24 hours, we can take that query, run it across our 18 and a half million members, determine every member in that 18 and a half million that is on that drug, and see if we see any evidence of the side effect they are looking for. It costs us almost nothing, very easy to do. Within 24 hours, all we send back to FDA is a list of saying we found 2000 patients on the drug you are interested in, and here are the incidences of side effects you're using. A wonderful paradigm, we can do a lot more.
I really think that this opportunity of what CMS is doing here is absolutely fantastic. My recommendations, first one is clone Todd Park, get more of him out there. I think that would actually work well. I do think that looking at all of the Medicare policies, because one thing I will mention is that when we run most of our queries for research right now, we are limiting it to our commercial data set. And the reason is that our lawyers tell us that our data use agreements, our Medicare Advantage programs, do not allow us to do the same.
I assure you that you should hold us to the same high standard you hold yourselves to in how we use that data. But I think looking at that type of sharing would absolutely graze that. If you think about it, I am most restricted in my ability to impact the over 65 members of our country through partnerships with pharmaceutical companies and other research entities, because that is the one data set I don't have access to.
Please do anything you can to educate consumers and policymakers on why it is important for data sharing. Over the years, I have seen a couple of wonderful children's cancer centers and children's hospitals have brochures that tell people that when they bring their children there with a rare disease why it is so important for their children and their families to participate in research. I think we can do this with data in a way that really does respect privacy and advances the industry.
And then, combining public and private data facilitates comparative effectiveness research is absolutely critical. I really do thank you for your time. I am delighted with where this is going. Anything you can do to further it would be fantastic. Thank you.
DR. CARR: Excellent, thank you. We will keep going then.
MR. GEIGER: I am Harley Geiger and I am policy counsel with the Center for Democracy and Technology. We are not data users. We are a policy-focused organization, although we have testified several times before NCVHS, other federal agencies and Congress on health IT policy, particularly as it relates to privacy and security. And today, I am here to talk about the underlying data architecture of many secondary use programs, including the programs that are supported by CMS data, but also looking beyond CMS. We have talked about this a bit already, particularly through the comments of Dr. Cohen.
First of all, I want to be clear that CDT strongly supports secondary use programs for all of the reasons that Todd mentioned earlier and that have been discussed here today. They can enable broad-based improvements in health care and they are critical to health care reform. But as HHS knows and has already been discussed, the health care system and the very usefulness of secondary use programs depends on patients providing full and accurate information to their providers, which in turn depends on the public, maintaining trust in the privacy and confidentiality of their data.
Now, the current trend for most secondary use programs is to pull all of the data into a centralized location that is maintained by the government, where it is analyzed and then released to data users. And unfortunately, the pattern that we have seen is that there is a new NASA centralized database created for almost each new data need. And regulations are locking plans into this model. Examples include CMS' own proposed risk adjustment program, state all-payor claims databases, and the recent Office of Personnel Management health claims data warehouse. Many of these, in fact, are analyzing the data for similar purposes.
Unfortunately, centralized architecture can exacerbate privacy and security problems because it necessitates the creation of multiple copies of the patients' data that is then held in multiple locations. So this can increase the risk and severity of data breaches, due to the volume of data in each database, and the fact that there are copies in multiple databases. It erodes public trust, as we have seen in fact with the risk adjustment program, and with the OPM data warehouse. There is a lot of stirring of public opposition against both of those programs.
It can also be expensive to maintain multiple large centralized databases. It is inefficient and burdensome for plans to maintain multiple feeds with multiple agencies, especially if those agencies are conducting similar analyses, but require different data formats. In our experience also, data that is held by the government often ends up being used for purposes other than the purposes for which data was collected. But because the government already has a copy of the data, the public has less opportunity to provide input into how that data is being used in the future.
And lastly, it is a poor long-term strategy to continually board a new massive centralized database for each data need because they are already so many data needs out there. And that need is simply going to explode in the future. So CDT hopes that HHS will continue to consider decentralized systems as alternatives where appropriate, not necessarily as a replacement for a centralized system in all circumstances.
And it is also important to note that privacy and security policies wrapping the architecture, regardless of whether it is centralized or decentralized, are very critical to maintaining the effectiveness of the program, although that is not the focus of this presentation. In a decentralized system, government researchers of course can keep the results of their analyses, but they never obtain a raw copy of the patient data.
As I list here, a decentralized alternative can reduce the risk of data breach by reducing the number of databases holding copies of the data, and also reducing the volume of data in these databases. It is more in line with public privacy expectations to keep data at its source. And a lot of plans have massive proprietary concerns with sharing raw copies of their data with too many entities. This minimizes data transfer, because you are really only transferring the results, not raw copies of the data. And as was mentioned earlier, it leverages a lot of existing systems, many of which are query-based.
There are two types of distributed systems that we recommend HHS continue to seriously consider for secondary use programs. A distributed query system where researchers and agencies write the code, they submit it to the data holders. The data holders then analyze their own data, and the data holders submit the results to the researchers or to the government agency. And this is sufficient, we think, for many common research purposes.
However, it has been brought up several times before that because you are allowing the plants to analyze their own data, it may not be appropriate for those categories of uses that can confer if competitive advantage or disadvantage to the plans. And so, for that category of secondary use program, we recommend what I am going to discuss in the next slide.
A distributed access system, and a key difference from a distributed query system is that the researcher or agency then accesses the underlying data, while it is still held with the data source. And then, executes the code or the query themselves, so the data is still behind the firewall of the data source. But the data source itself is not analyzing the data and returning the results.
To accomplish this, the data source can set aside a copy of the data in a secure environment that they themselves operate. The agencies can access this via secure interface, which should be flexible enough to handle many queries, and that can also support role-based access controls. And then, the agencies and researchers keep the results of their analysis as opposed to copies of the data. This can be also supported by auto controls to ensure accountability.
And the advantage here is, as I said, keeping the data at the source, using many privacy, security and propriety concerns. But also, the health plan itself does not have to run the queries, which can be burdensome on any small plans. And also because the agencies themselves run the analysis, there is less chance of fraud or inaccuracy for uses that can confer competitive advantage or disadvantage. Although there are unique challenges associated with the distributed access system, primarily as they relate to network reliability. A weak node can hamper analysis across nodes. This can be perhaps mitigated by having windows where the high availability ed server is open for analysis. And these challenges have to be addressed before deploying any distributed system on a broad population scale basis. So to be clear, we are not saying that this system is ready for primetime, but it is something that we think ought to be evaluated.
And so, that is our recommendation. One, please do not lock plans into a centralized model in the future, the way that CMS' proposed rule on risk readjustment does. Instead, word your regulations to leave open the possibility of decentralized systems in the future. And second, continue to test decentralized systems. There are many that are promising right now, including Mini-Sentinel and the multi-payor claims database. But these must be tested on a population scale basis for the sorts of secondary use programs that we see currently being conducted by all-payor claims databases, and CMS itself. And that is it, thank you very much.
DR. CARR: Thank you very much. Next speaker?
MR. DAVENHALL: I am Bill Davenhall with a company whose name is Esri, but it is spelled E-S-R-I. For many people in this room, you will probably recognize perhaps not the name, but you will recognize the maps that are created with the software that our company develops. So my first order of business is to tell you that most of you are our customers. All 50 state health departments, the CDC, HHS and every federal department is a user of this technology. And so, what I am going to try to do today is explain very quickly what this analogy is supposed to do for you.
First of all, this is a view of the National Health and Social Data Ecosystem. As you can imagine, this technology is about linking data that is geographically relevant. Now, what you see here are the things that the people in the health and the social world think about. Where are things, what are the hazards, what are the social resources, the health resources. And for any other industry, if you wanted to call it an industry, like transportation or utility, they build the same models. This technology is able to link all that data to health models. And health models can be linked to transportation models and utility models and water models and all sorts of models that you can imagine.
So it is a way to think about how your world is connected. It is really a technology, it just doesn't produce maps. It literally provides the framework that allows you to think differently about what you are working on. So I bet all of you, when Niall showed that beautiful map, you probably still in your own mind can remember where the darkest spots were, can't you? I know I did. That is the power of that technology is cutting through all of the millions of pieces of data that Niall had to sort through, to get to that point where you have in your image. You are probably going to ask him later can you see that map again, because you want to look at it more closely, to see whether you live there or you have relatives that live there or something like that.
I brought prepared remarks, and I think they may have been available to you, so I am not going to review those. But I do want to point out some things that probably are important. My remarks are really coming from 40 years of working with your data, both the National Center for Health Statistics and CMS data.
And I would say, as a graduate student who walked into his office and cubbyhole, and found 25 shipping boxes found with the Rainbow series, I thought I had died and gone to Heaven. And I carried those things around in a moving van for like almost 30 years before my wife made me throw them away, because she said aren't they all on the internet? And I think probably most of them are. So that is how I got introduced to the National Center for Health Statistics. They taught me how you can creatively use color to remember things. You all know what I am talking about, I suspect.
I am going to start where I wanted to end up, and then I am going to explain this slide a little better. There is a great laden opportunity in the wider use of CMS data assets, both for clinical administrative purposes that meet national, as well as local health policy, and human and social service deliver imperatives. The line is getting finer every day, between where does health begin and where does social begin. And I would say it is time to sort of put that to bed and say you know, it is all on the same continuum.
Any health or social provider serving a diverse population should have the ability to compare what they are doing to what the most popular governmental health and social programs are doing. Presently, most of us work in murkiness because the most useful CMS data is neither easily accessible nor practically useful at the lowest geographical levels. We call that finely grained, and I would say accountability demands finely grained data, with the provision that it must remain confidential.
So I believe that CMS holds an incredible key to launching a new generation of health data analysts in America, analysts that will be equipped in the right invest data, at the right geographical level and when they need it, creating an enhanced capacity to serve up data and encourage its intelligence use. So Niall is right on about data access and use. They are two very different things. Data accessibility is one thing and usability is quite different, but they have to be linked together. One without the other is not where we need to go.
Finally, I believe that CMS represents our best hope of helping the entire health and social ecosystem understand how our health system actually works, or for those of certain vents, doesn't work, for individual consumers, communities, providers and policy makers. So on this slide, what I want you realize is that this little bit of data that we are talking about here today, we know that there is CMS data and then there's 100 other kinds of data. It is all trying to serve as many people across many places for many different purposes. So utility becomes a big factor, leveraging the limited data resources we have becomes a critical economic driver.
When you take a look at the CMS data users view, which is where I have been for many, many years, I was answering these kinds of questions. And I would say probably most of my years were spent in the research community, so I was always asking who, what, where and why, and how much. And this is the technology now that I would say everybody in government is learning to leverage this technology, so they can cut through the haze and get right to what is most meaningful.
How do you make this data actionable? How do you get it into that position, so Niall could show you that picture of the United States? And he does that with a sense of not just urgency, but a sense that it is correct and right, the underlying data is accurate. I have this slide because we have a big data dam that is going on in this country. And it has to do, if you don't get the data right when you start, it doesn't get any better. You just clean it, but it doesn't actually get any better. And so a directly claim coming from a doctor's office or hospital is just passing it onto the Aetna's, and the Aetna's have to clean it. And they are going to pass it onto National Center and they may have to clean it, and everybody is cleaning the same data, when it should have been corrected at the first get-go, at the point of service.
This slide is just to tell you that some organizations are getting their data sets what I call GIS ready. Getting that piece of accuracy right, and they are going to go through the dam a lot quicker, and they are not going to be on the rocks. I have a lot of boats there that are in troubled water. You don't want to be an agency who has a lot of data in troubled water, because it just means that the data is accessible, but is not very useable.
This is my recommendation, and I really am just echoing Niall. They have already said they are going to do this, so this is really great. It is to create this data access and use program, add value to data before you serve it up, and assist users in consuming it intelligently. So there is an incumbent responsibility, I think, that both CMS and people like National Center for Health Statistics do, in explaining what we have. And I know the National Center has done a lot of that over the years. So it shouldn't be a big stretch for CMS to also get into that same business, where they help us as end users use that data intelligently.
This is an example. This is a recent piece of work that was done by Loma Linda University Medical Center. For those that don't know, that is in Southern California. It is where they did the first pediatric heart transplant, Dr. Bailey, and also the first proton accelerator. They are trying to step up to the Accountable Care Act, and this is a picture of the emergency department utilization, where they decided that the diagnostic information suggested they did not need to be in the emergency department. And this represents loss charges to that hospital, over $30 million worth of loss charges. And wherever you can see the brightest darkest color, that is where most of the loss charges accumulated.
The granularity of this is that census tract in block-group levels, and they know a lot about the people they serve. They almost know nothing about the people they don't serve. They could know a whole lot more if CMS takes a route, that begins to share that data at a more finely grained manner, so they have something to work with. So it is just one illustration of the process of moving from what we have been working with for many years, which is highly aggregated data, to something less aggregated, deaggregated, but yet still remains and meets all of this confidentiality provisions. If there are any questions, thank you very much.
DR. CARR: Great maps and great illustrations. But let's go on to our next speaker and continue on.
DR. ROSENTHAL: I am Joshua Rosenthal, co-founder of the startup RowdMap. A couple of months ago, I was at MIT, giving a presentation to a roomful, a couple of hundred people, MIT students, doctors. A couple of months ago, I am at MIT giving a presentation to a couple of hundred of groups of people. And they want to build the next best health care company, particularly around data and analytics. And MIT students, there are doctors, there are designers, there are Pure Play Tech guys there. And a couple of weeks after that, I am at Harvard giving a lecture to essentially the same sorts of folks. These are undergrad students, in computer science and business and in health care. And these two groups of people have the same question, where is the action, where is the opportunity, where is the most meaningful stuff happening in the health care system right now. Is it New York or Silicon Valley essentially? And I said you are not going to believe this, you need to sit down, but it is actually happening in D.C. And it is not nanotechnology, it is not biotechnology, it is actually transforming the payor system from fee for service to pay for performance. And they went nuts and got into all sorts of fistfights. No, they didn't do that.
But the point of the story is that, that is actually what is going on. You guys have done fantastic work in moving from fee for service, which is I get paid more to do more stuff with unwarranted variation, everything that comes along with that. Part of our background was around the Dartmouth atlas, I speak with some authority around that, to pay for performance.
I get paid more if I do better things, better clinical outcomes that are patient-experienced. That is fantastic, and it also means you are transforming the big fish in the eco system, the insurance companies from risk brokering adjustors to participants in the health care system. I don't just mean through ACO, I mean through their identity, the M&A activity. If you scan the newspaper, you have seen in the past six months, half a dozen billion dollar cash plus deals where they are requiring not just M&A populations, but providers and means to control those providers.
And that is really important because you, and I assume you have done this intentionally, have changed what it means to be a profitable life. You are no longer in the DM world where profitable life is someone who is at the low end of the critical risk strat. I think I am going to be healthy, so I am profitable. A profitable life is now someone in Medicare in an M&A program, where I am controlled by pay per performance. So you have aligned incentives brilliantly.
It does mean that you have some things to think about very carefully. And as the next slide loads up, you will actually see what I am talking about. So you are hearing all sorts of problems, and it's security, scalability, man hours, custom files, et cetera, et cetera, et cetera. Those are all symptomatic problems. Your key problem is that you have a systematic business change. You have done that intentionally, it is fantastic. But it breaks your historic infrastructure. So it costing you money to do all of these things and you have these issues. But you are telling providers, plans and everyone that they need to be data driven. And if that is the case, you need to make that data accessible. And when I say data, I mean information, interpreted data in a meaningful way. And that is system wide CMS data. Today, it is research and quality control, which is different than STAR and reimbursement and provider payment, and tomorrow Medicaid rolling out and other things.
These are two sorts of separate issues that you have to deal with. One is research quality control. Here, you have a small number of large data sets that is identifiable reidentification concerns. Your concerns are security, privacy and automation, and internal scalability. And you also have just as important, and geographically cross walkable by contract, this is the fine grain stuff we are hearing about. STAR and reimbursement, here you have a large number of small files, which are public. But your issues are coherency, usability and access, not just access, but access in terms of interpretive access.
And so, my suggestion would be, and I guess you are already doing this, so I will just echo that this is a fantastic idea. I couldn't have conceived to do anything better. Solve today's problems with the technical foundation for tomorrow's business paradigm. And that is some sort of system, we can talk about distributive access versus query versus centralized, but there is another way to look at it. A classic approach is a data extract system and tool. This is simple, it works, it is proven, reliable, and you have heard a couple of examples about that. It is centralized or has an abstraction layer with distribution. But the point is, I can pull together meaningful information on the fly with the UI tool creates it. And this works, everyone does it, solves security, privacy, automation, and uses something like this.
And if you pull into the non-beneficiary STAR stuff into the data structure in taxonomy, you can actually link all the stuff where plans make money, not just the fine grain piece. You can actually link the profit drivers to it, because you created that around your STAR metrics geographically. You can use something new, slightly different approach to that is what you call a cloud. It makes you seem cool, but there are also some technical benefits. I won't talk about that, you can ask the real experts about that.
All of these systems just have a few things in common, and it is worth just thinking about this a little bit, because the devil is in the details here. There is some sort of system or tool, where users can create things on the fly with an extract, with a GUI, or have a permission that is credentialed, and I have a certain level of access and an enclave. And it allows me to pick the grain, what I want to do, et cetera, et cetera. And you want to be smart about it, so you're not reprocessing everything, so you can be smart. You can basically do new processes, at APCD level, three types, new, update, cancel. There are different ways of doing it.
But when you build this, you can actually implement quality control metrics, and this would be incredibly helpful with your data right now. Basic check some type stuff, as well as universal constants, meaning there should never be more than 500 contracts here that have this stuff, that will filter out a lot of the slop that you find.
And most importantly is taxonomy, is their hierarchies. The stuff can't be completely flat. When Niall says interpretive meaning, what he means is a taxonomy. And when I say taxonomy, I am not talking about conceptual diagram or a diagram or a meta data model. I mean baking in your business questions, into the structure of the data. And Niall showed you a couple of examples of that, and that is really, really important. And when I say business question, I don't mean plan-making profit. I mean things that you guys think are important and you incentivize correspondingly, improved clinical outcome, improved patient experience, et cetera.
There are a bunch of slides and they are showing you very specific examples of how we have done that on our own, because we had to, because it wasn't done for us. And you can flip down and look at it later. And then, some sort of learning center, some sort of distribution, where I can actually share and learn in internet time with other folks. Not just share code and not just have documentation, what does this thing mean?
We are not to spot errors. In 2009, a contract meant something, in 2010, it means something else in your taxonomy. But actually share interpretive frameworks. And here, on one hand, you need greater granularity as Bill talked about. On the other hand, you have this sort of meta interpretation.
I want to talk about what it means, when I pull these metrics and I see Aetna versus Cigna. Having very sorts of different clinical rates by your performance metrics, in areas with very specific races, versus low access providers, high access providers and the Dartmouth stuff we pulled in.
And what does it mean when they actually implement HealthGrades, and it has very different effects on very different groups of people. And I can do all of that stuff right now with public data that you already had, at least on the Medicare population. And so, having the hooks to crosswalk that back, is incredibly important. And you will see an example of a learning center around that. I would say having someone outside the health care space is fantastic.
Also, extending that data into controlled views, data explorers. In the Pure Play tech world with some of these MIT kids, the things that are winning the awards are actually them looking at health care data with Google, with ReadWriteWeb, with TABLO, things that you guys aren't intentionally doing, but they are using your data. And there are tens of thousands of people using this. So building a good consumer-grade portal to actually get into, and there are some slides showing what that would look like, and pushing the data, at least the interpretive data, out into the ecosystem like little seeds and pollen. That is what has worked so well in the Pure Play techs. I would encourage you to take it a step further. It's like YouTube for data, you can play around with it. That is the easiest way to think about it. And finally, same system for public data, okay, fine.
So in a nutshell, you have databases, this is the beneficiary stuff, small number of large databases. You have files, large number of small files, which have this interpretive difficulty. And you need to put into some sort of structure for some sort of meaning, for standard taxonomy, not meta data, but around business. You need a learning center where I can go and figure out what the heck is going on. You need some sort of simple system where I can get access to it.
And then, if you are innovate individual, I have got a number of start-ups which have been successful, not as funded, but actually acquired by plans, by technology companies and by other folks, as well as private equity companies. I am speaking with at least what has worked for us. And we can do that because we have built these systems that Aetna and company uses, and around 85 percent of your commercial Medicare population through it.
But for the Harvard and MIT kids, they can't do that, that's really tough. They need to build up there where it says this, asking him to build all the way down into the data is just incredibly difficult. And my background is PhD Fulbright in Sorbonne's Applied School for Advanced Studies, and I assure you these kids are far, far smarter than me. So it is not an intelligence issue or a different species. But if you want to explode innovation, you need to do that, to make that applicable for them.
And if you do that, you have already done the hard work. You have already created the standardized way of looking at stuff. And I assume you have done this intentionally, because it is just brilliant, there is no other way to do it. The standardized way of looking at stuff in your population, that ties payors to providers, which is why you see all of the M&A activity.
So I'm a payor, I want to make a data-driven decision. How am I doing compared to my peers, because that is really important. Where should I focus, what should I do, which interventions, intervention being a product like HealthGrades. I am a data-driven intervention vendor. How am I doing compared to my peers, you asked a peer question about HealthGrades. Which members does my intervention work for most, meaning when I deploy this thing, does it improve satisfaction these metrics?
And these are out of all the health people we know, and stuff you guys see thousands of these great ideas coming out. When working with these kids at MIT and Harvard, 99 percent of them fail. And if you look through very carefully in the Health 2.0 stuff, you see 99 percent of those companies fail within a few months. Why is that? Because they haven't tied it to a meaningful business question, right? They haven't tied it to profit or profitability, and then they put a 299 iPad app and no one really uses it, and et cetera, et cetera.
You guys have built the infrastructure to allow them to do that. They can take that silly iPad out that says how fat I am today, and actually say when you deploy this with Aetna, you actually improve in these areas, these specific metrics, and this is worth X amount of dollars in reimbursement, this is worth Y amount of dollars in Medicare retention, et cetera. And then, you can do meaningful research. What do successful payors look like in terms of their impact, geographically, access, et cetera? What does successful interventions look like? What is the nexus between the two, what are the characteristics of key drivers to improvement, and how can policy accelerate these key drivers.
You have done this hard work, it's jaw-dropping. After our last successful ideas(?) that we are going to get out of health care, but you guys kind of shamed us into staying in it, because if you are doing this work, we can't go walking away now, right? So you have done that. All you need to do is put a couple of more chips on the table, to really capitalize on this. That is why it's exception when you say you are going to double down, that is beyond our wildest dreams.
You need to do two things. You basically need to build that infrastructure data information products and services, because you are asking everyone else to be data-driven, so you need to give them the ability to do that meaningful, that changes your infrastructure. You can't just give them a transaction list, like you go to a menu and say order this and it costs this much. If you are going to be pay for performance, then you need to have some interpretive framework on that. And you need to make it meaningful, which means taxonomy, and please look at the examples of what I am talking about. And you need to get people to use it, which means not only getting people to use it with kind of fairs and challenges, but getting a decent looking portal, and helping them tie their wonderful ideas to the specific drivers of profit in health care. Because when the Pure Play tech people come in from MIT and elsewhere, they don't understand health care is littered with perverse incentives, and that is why they fail. You need to help educate them through whatever you are building. Thank you for your time and attention, appreciate it.
DR. CARR: Amazing tour through some amazing minds. It really opens our minds to hear this.
Agenda Item: Continued Reactor Panel
DR. W. SCANLON: I can't replicate Todd's demonstration of enthusiasm. But let me tell you how enthusiastic I am about this and how positive it is. I started in health services research about 40 years ago, and worked very closely with HCFA. And I don't think you can imagine the data that was available then to guide policy. It was some combination of things on paper that were analyzed with colored pencils, and some computer output that took gosh knows how long sort of to create. And so, the fact that we are here today, talking about the potential that you are actualizing is very enthusiastic. Some might say well, it is 2012, so shouldn't we be here sort of anyway?
But that has been true for a long time. We should have been somewhere further along and we weren't, and the fact that we may be close or at the point now is incredibly positive. And I say all that, even though I spent these last 40 years having a much better experience on average than most people. I worked on government contracts that I had access to HCFA data. I worked at GEO and we had access to HCFA and CMS data. We weren't CMS employees, but we might as well have been. We were basically sort of in their face all the time and using all their data, so we could do anything that they were able to do.
At the same time, what we were doing was hard, and it wasn't sort of capable of meeting the needs of the time. I can remember in this last sort of 10 years, we faced the issue of the SGR with respect to physicians, and the big question has been are physicians dropping out of Medicare. And we always asked ourselves can we answer this on a timely basis. Because if you appear before the Congress, and you tell them three years ago, this is what happened, they say we didn't come here for a history lesson.
And so, we were saying is there anywhere in the CMS data flows that we can tap in, and try and get some measures of physician participation, and it virtually turned out to be impossible. So the notion that you are bringing data sort of closer to real time, very close to real time, is such a positive thing, sort of from a policy perspective, that I am incredibly enthusiastic.
It is particularly important, because I think just at the time we are at now, we have got a compelling need to improve our health care system. And I think that was brought home, or at least brought home for me very clearly, sort of over this last year, as we were discussing the deficit and we recognized the role of health care sort of in the deficit. And there is this feeling that we have to do something, and the risk is that we don't do something that is well-informed. And that is a risk of great magnitude, because we are talking about affecting tens of thousands, if not millions of people sort of negatively.
So being well-informed about the change is critical because I don't think of it as just trying to cut costs. I think of it as trying to improve efficiency. This is the economist sort of in me, which says we may reduce the cost, but we also want to do that in a way that doesn't harm access and doesn't sort of harm quality. In fact, maybe in the process, we can improve sort of on both, and that really should be our objective. But that involves a level of sophistication that we haven't had the capacity for before, because we were really lacking sort of the data.
You have covered all of these areas in your presentation and the CMS presentation, as well as sort of in the others, I think at three levels at need for information. One is at its most aggregate, which is a policy and program level, sort of for both policy development to sort of in program management. And then, I think as a second level, there is the clinical sort of side of things. And the ACOs were a great example because the notion of managing in an ACO without information, it's not a health plan. The trade-off here in terms of trying to keep people sort of interested and attracted to them is freedom of choice. And that means that the people in the ACO do not have sort of sufficient information, so we have to think about how do we compensate for that. And so, I think there is critical sort of information there.
And the third thing, which is the area which I think where we have to work the hardest, and this committee has actually worked on, in terms of its meaningful measures efforts, is how do we influence the patient in a positive way, in terms of giving them the information that they are going to find useful. And be able to sort of affect their behavior, sort of in a positive way.
At the top level, this aggregate level for program and policy management, again sort of the fact that you brought things into real time, you are realizing sort of much more about sort of all the data that is within CMS, this notion that it is not just claims, but it is cost reports, it is assessments, it is other sources of information. And the fact that those can be merged and matched, and there is real power in doing that, in trying to understand things better. That is an incredible positive thing.
I think we need to consider about how do we go further in that. In Bill Davenhall's presentation, his idea that everything influences everything else, I think is very sort of relevant. The slide about the readmissions, those are critical. It's not just the program and the initiative that we have, but we are also talking about penalties we are not talking about. And we are going to put penalties in place for hospitals. One of the issues which is an hypothesis that I have heard entertained multiple times is, what does socio-economic status have to do with readmissions. What are we doing in terms of the safety net in this country, if we don't take that into account when we think about which sort of policies.
We are living off and most Medicare policies are modeled on the 1983 DRG-PPS system. It has worked, but as we start to think about sort of being more efficient, we may need to think about how do we refine. This is a challenge because now we are talking about not necessarily that you do have available. And we have to think about sort of how do we access sort of that additional information. This committee had a hearing before the beginning of sort of the health reform discussion, about information for health reform.
And one of the things that was discussed at this hearing was how difficult data access is within the federal government. That going across agencies is not a no-brainer, and each time there was an agreement to do something, there was a start from step one. And it would take sort of a significant amount of time, sort of to get to a point where there could be the kind of sharing that was going to be useful. Moving forward on that is also important, and hopefully you can maybe get OMB to be one of your partners on this, to sort of push that sort of more.
As we release data, to deal with these more aggregate issues, I think it is important to think about what can you do to be of technical assistance to the users. I sort of both recognize when I was a user, and hopefully we were doing responsible things. But sometimes, sort of after a lot of effort, we would discover oh, my goodness, we are going in the wrong direction. We didn't understand that, we didn't have that sense of what was really sort of within this information. And the results you get comport with your biases, then you're assuming the analysis is right. You have to be sort of cautious about that.
If you can think about it as a point of your line of business, not just the information being conveyed, but what kind of assistance you can give, that would be sort of, I think, very positive, as well as maybe thinking about sort of how you convey information and the types of information you convey, as being sort of more failsafe than less.
I am not going to talk about what you are doing with respect to the ACOs on the clinical level, because I think that seemingly you are doing exactly the right thing, in terms that you have got to provide the support for these new types of delivery innovations, when they are not natural to the organizations that are involved. Again, we are not talking about a health plan, which may have the information. We are talking about sort of independent provider organization.
I think one of our big challenges, and there is a lot of interest in this, is how do we information that is useful to patients. And Justine brought up this issue of consistency of information. I have seen presentations about the group insurance commission in Massachusetts and their physician rating sort of efforts. And the fact that a single database was given to a set of payors, and they rated physicians, and all came back with different answers about the same physician. And that may all be legitimate, but it is the transparency, I think, is a minimum that we have to ask for. Sort of why did you get this result versus someone else's result. If you are having a line of business, you need to think about one of the prices you may be asking sort of users for is transparency. That we know sort of how the data are being used, so that people will be able to evaluate it.
Another thing I think we should be thinking about is, and you already have, sort of if they have data, you would like to have it, too. And I think this is a very big thing because again, sort of going back to the whole world is interconnected, we shouldn't be thinking about Medicare or Medicaid in isolation. We should be thinking about them sort of in the markets that they work in, and sort of what is happening sort of in those markets. For that, I would salute Aetna. You didn't mention this, but Aetna, along with three other large insurers, has contributed to this health care costs institute, giving them the claims data, and Kaiser Permanente is sort of one of the others, and United and Humana are the other two. One of our problems in policy has been we have had no clue what is happening sort of in the private sector. We have known a lot about Medicare, but not enough. But we have had no sense of sort of what is happening sort of on the private side.
So this notion that we really need to share information, so that we can get a sort of more detailed and sort of refined picture of different sort of markets, because being an economist, I have to say I think markets matter. And so, we want to know what happens sort of locally, it is absolutely critical. It raises some questions about these models in terms of not sharing the data itself or having it centralized. We are going to have to have some data to migrate, in order to be able to pool sort of information.
The other thing that has been a handicap in the past, in terms of letting sort of others work the data, in terms of understanding the context for it, is that when one has data from one source with individuals, and you want to match information about their environment, that can be as revealing as their identification code. And so, if becomes a bit difficult to say well, I need to study this in context, but I can't tell you anything about the context. And we have to think about sort of strategies to overcome that.
And I guess the last thing I would say is I am as enthusiastic as Todd. I haven't sort of probably conveyed as expressively as would, but this is an incredible movement forward.
DR. CARR: So let me open it up to other members of the committee. Do we have someone on the line?
DR. TANG: This is for Todd. And one, I share Todd's enthusiasm about what this represents as a means to transforming the health systems. And I think to engage patients.
But I had a couple of questions. One has to do with maintenance. So we mentioned that in the state summit, there were a lot of databases, and not everybody knew what databases were. Potentially even the owner of the database didn't know what the fully existed. So one question has to do with maintenance, and that certainly happens in our organization where we have these reports, and some of it doesn't seem to be around anymore.
The other question I have is related to that. In this phase of the health data initiative, I think its active data that the government currently has. Is there a thought of moving to the next stage, almost like meaningful use, and having shared consideration of what data could be collected, that they should contribute to the value. So for example, in the old days, a doctor-finding website might say, where did you graduate, where did you get your training and are you board certified? Nowadays, it includes a video of your views on life and health, et cetera. And it's just that the data collected and are meaningful to the consumer of that data, change over time. Would the government be open to considering adding new fields that may increase the value for the consumers of that data?
MR. PARK: Terrific, and my colleagues should actually also weigh in, as well. So Paul, the first question was about maintenance, is that right?
DR. TANG: Correct. So let's say for contractual reasons, you require your contractors to supply certain data. Does it get maintained every year, more often? So for example, if you want to use, let's say, data on social services, the updates to what services are available and what tests that certainly could change over time, are these databases specifically maintained.
MR. PARK: With respect to maintenance, I think it is useful to think of the HHS data universe as a highly diverse eco system. I think that the routines for maintaining and updating data are as varied as types of data themselves. And so, if you think about what you mean by data, it is everything from the latest and greatest scientific knowledge at the National Institutes of Health, Medicare claims data, FDA recall data, community health performance data, et cetera. So it is really quite different from place to place to place.
What I think that we are actually seeing that is enormously beneficial is think of the different data sets within HHS each as data sets are owned by a particular business owner, whether it be someone at Medicare or someone at NCHS or someone at National Medicine(?) Center. What we are actually seeing is that it is incredibly valuable to have those data owners interact with people in the outside world who actually use the data. Because in some cases, data updated every five years could be perfectly fine. In other cases, it is completely useless. In other cases, it is something in between.
The thing we have to move toward is a world where the data set owner has a lot more intelligence about how their data is actually being used and how it could be used, so they could actually dial it into their plan for how to actually maintain and update the data, and so that the data set owner is actually armed with more information, to go back and make the business case internally for more funding, because they could actually improve public health at XYZ dramatically, improve health reports to XYZ in a dramatic way, fi they actually just got the data out on say a monthly basis or a quarterly basis with a six-month lag, as opposed to that sort of with a three-year lag.
This has already actually been happening, which is fantastic. And I think that one of the key to-dos, I think, of all of us that care deeply for the health ecosystem is actually to treat it as a public space which we need to get the suppliers and the users more closely intertwined and talking to each other a lot more, whether it be at physical datapaloozas or via what data force will build in terms of HealthData.gov 2.0, so on and so forth. I think the more dialogue that happens between suppliers and users, the better the maintenance of supply will be, and the more targeted and social ROI investments in data will actually become. I think that is critically important and it is already happening.
I think with respect to the collection of new data, so first of all, absolutely. Again, it is hard to generalize because the kinds of data that the government has and is liberating are so diverse. But are these data sets or data programs iterating? Absolutely, absolutely. Just look at Hospital Compare, which is evolving to actually add more metrics, with respect to the hospital conditions. It is actually learning a lot about what is working there and not working there, and iterating beyond that, so on and so forth.
I actually can't think of a data set to suggest that is actually static and will never change ever again. But I think they will all live and breathe and grow in all kinds of ways to try to add more value. And again, just to kind of return to the punch line, very important for those investments in data set evolution to be informed by how best can this data be used to generate value, especially in the context of a health system that is now halleluiah, moving toward a world where it is really getting increasingly focused on, and is actually incentive to and rewarded for and supported to improve care and improve health and lower cost.
So again, dialogue between the suppliers and the users critically, critically important. And actually, as a final point, again in the kind of context of kind of steadily improving and involving data, HHS is just one supplier. The healthy initiative is not an HHS initiative. It is an American initiative. We are very happy to be an anchor tenant, we are very happy to be an anchor supplier. We are very happy to be in the somewhat unfamiliar position of actually being on the cutting edge of doing something.
But what is actually happening is that other people are joining the party, other data suppliers are actually joining the party. So the state of New York actually just announced that it is launching its own healthy initiative. And it has launched something called the Metrics website, where it is publishing more and more data sets that are machine readable and downloadable and accessible by the American public. The state of Louisiana is actually beginning to make a move in this direction, as well. Private sector companies like Gallup Healthways are moving in this direction, as well.
Maybe one of the most interesting examples is an example that I talked about maybe a year ago called Blue Button. Blue Button is an initiative where the Department of Veterans' Affairs, the VA, the Department of Defense and CMS decided about a year and a half ago to do something that seemed incredibly simple, but was actually in retrospect pretty radical, which was allow veterans, members of the military, and seniors served by Medicare to actually download an electronic copy of their own information. And it is actually something that we weren't exactly sure how population it would be, because we said well, how many people really want their own data.
Secretary Shinseki, who was the secretary of the VA, in fact was told that if the program were wildly successful, that 25,000 veterans would ultimately choose to download their data. Well, basically no marketing, and the vast majority of seniors, members of the military and veterans still do not know Blue Button is out there. But to date, 750,000 veterans, members of the military and -- have actually chosen to access and download a copy of their own data, on average multiple times each.
And there are anthropological studies now, which have actually shown that your veterans, what are they doing? Well, they are actually printing it out, for example, and they are taking it with them to their docs. It turns out that half of the care provided to American veterans is provided not by the VA. And what are all the meds they are on, when was the last time they saw a doctor, what were the diagnoses, what did they say.
Now they are actually passing it along, and the veterans have literally said, because I did that, my doctor realized I was on a med that I didn't remember I was on. And thereby, changed the medication regime away from a course that actually would have put the veteran in the ER, for example. People were uploading their personal health records. People were doing all kinds of stuff with it, which was actually very exciting.
But the maybe even more interesting part of the Blue Button story is that, after we did Blue Button, word started traveling in certain circles. And we actually got calls from data holders in the private sector. And the question we got from them was, are you allowed to do that? And we said, can you clarify the question? And they said, are you allowed under HIPAA to give patients and consumers a downloadable, electronic copy of their own information? We said yes, absolutely, absolutely you are. But I think no sub-regulatory guidance or detailed memo would have possibly been as persuasive and definitive as Medicare, the VA, the DOD just doing it, and actually increasing that.
So what is happening now is that, more and more private organizations, like Aetna, United, Walgreens, Mechassin(?), actually Louisiana, Vermont, et cetera, have either Blue Buttoned or committed to Blue Button their data. So we think that actually, by the end of the summer, well north of 50 million Americans, probably actually closer to 100 million Americans, will actually have access to Blue Button data. At the end of the day, a bunch of those folks will be Medicare beneficiaries and veterans and members of the military. But there will be many, many, many others who access their own data through private organizations.
I think at the end of the day, the government is only one holder of health data. And health data is sort of really about sort of everyone who cares about health and healthcare for America in responsible ways, improving accessibility to and use of data, so that we can actually power the kind of health and health care improvement that this country really, really needs, and which we are actually beginning to see happen.
DR. TANG: That was a perfect answer and an exciting one. I don't think if this is even possible, but I think I am even more enthusiastic than Todd. Speaking as a provider who not only wants to consume some of the data, that is out there, but be partnering along with our patients on involving the data set so it has richer and richer data that is meaningful, and then can be reflected. It is just totally exciting, thank you so much.
DR. CARR: Okay. So I have Bob, Larry and Walter.
DR. KAPLAN: I am Bob Kaplan from the NIH, and actually I have been in government a relatively short time. But during that short time, I have had the opportunity to hear Todd speak several times. Actually, one digression that the NIH directors meet on Thursday mornings and we invited Todd to come. He is veering his head. So what happened was, Todd was giving a little talk to the NIH directors, and his cell phone rang. And he sort of ducked away from the podium and he said this is my wife. And he said my wife and I are having a baby. She is on her way to the hospital. And he said, and I have to move through this next dozen or two slides quickly. And actually, all the physicians and the NIH directors group seemed much more nervous than Todd was.
My question is, first of all, I think everybody loves all the stuff you are doing, and it is going in a really interesting direction. But I wanted to raise another question about the connection between suppliers and users for the information. So I served on an IOM committee last year that was interested in, among other things, data needs. And one of the concerns was that they refer to a problem that they called indicatoritis. And the concern was that people who are making decisions in health care, primarily directors of public health departments, are so overwhelmed by data and by indicators, and by the lack of harmonization of indicators, that they don't quite know what to do.
And so, if you look at some of our big data needs, a committee like this for example, how are we doing as a country in advancing the health status of the population. And this committee concluded that, well, what we really need is we need a good harmonized summary measure of population health, like a quality or something like that, in addition to all of the stuff you are doing. I don't think it's either or, but there was concern about are we missing harmonization or opportunities. Are we sort of feeding indicatoritis without getting at the basic things we need.
MR. PARK: This is a phenomenal point. I would say you're absolutely right, it is not either or. In fact, I think one of the most important goals of data liberation is to accelerate R&D on what the truly meaningful measures are. And also, to recognize that meaning, as you know better than anybody, what a meaningful metric is. In certain cases, it is the same for every American, and actually in many of the other cases, it is not. And so, I think that the notion of actually democratizing access to our data, so many, many, many other smart people, besides just us, can really turbo charge R&D, and what really is a meaningful measure, and to whom and when. I think it is critically important.
One of my favorite examples of this actually is the section 10332 provision, that is an unbelievable breakthrough. Don Berwick says it is one of the five most important things he helped to do at CMS. The whole idea of actually allowing provider identifiable metric claims data to actually be accessed by parties outside of Medicare, mashed up with other data that produced truly comprehensive quality reports and performance reports, that are shared with providers and then actually vetted and shared with the public.
One of the benefits of this is that, on top of actually allowing critical mass of data to be put together, to then produce new transparency performance for providers, which by the way, is not just helpful for consumers, it is very helpful for providers. So I, as a doctor, know where I stand relative to other people and how I might improve.
The other provision of 1052, which is I think amazing, is the qualifying entities are A) supposed to use like this inventory of measures. But then B) if they get local support, are allowed to come up with new measures, that they will actually then propagate. And you can imagine then a significant quickening of our understanding of what really works and what really makes sense to a doctor, what really makes sense to a patient, because I think all of us would agree, quality measurement for all of the brilliant work that has been done, is still in its infancy. And I think a lot of the reason why it hasn't progressed as far and as fast is because access to the underlying molecules that you need to do that kind of research, it hasn't been as broad and as deep as it should be.
So I couldn't agree with you more. I think that the notion of actually really finding meaning in the data and finding a way to communicate that, in a way that a doctor, a public health official, a patient can really understand and use, critically important. And I think that actually data liberation, done in the right frame, as we are talking about, can actually significantly accelerate progress on that front.
MR. SOONTHORNSIMA: I will be brief. Thank you very much for those comments. To follow up on what Todd and Bob were just talking about around data liberation. I think specifically around performance measure, there is a slide that you had, Niall, when you touch on those activities that are well underway of recent progress, well underway such as providing data to HCOs, and the second bullet point was around Medicare data sharing for performance measure.
On that particular point, and I heard around the room, particularly from Aetna, that marrying that data from multiple sources, multiple payors, private and public, would be a lot more meaningful for performance measures. That is stated. What are then some of the qualifications, you said in your bullet point that the data would be provided to qualified entities. So what are some of the parameters, in order to accelerate, last point, and advance some of these initiatives that are happening across the state, particularly in Louisiana and other parts of the country?
MR. BRENNAN: So specific to that program, very high level, you need to bring data from other sources to the table. You need to demonstrate experience in combining claims data from different sources accurately, into a single database, either using a centralized or distributed approach, if that is your choice. You have to have experience in calculating claims and or claims plus clinical quality measures. Experience in public recording, and that is pretty much it.
You also have to undertake to allow providers that confidentiality review and appeal the reports before you make them public. And also, I think a key distinction here, and one that we tried to clarify in the final rule, a qualified entity is not a monolithic organization. So all of these skills, because they are pretty highly technical skills, don't have to be under the one roof of one company. Qualified entities can meet these criteria through partnerships and contracting and collaborating, to get the necessary expertise in the door.
MR. SOONTHORNSIMA: And when you talk about performance measure, are you talking about at the facility level?
MR. BRENNAN: The individual provider level, technically providers and suppliers to services. So it could be physicians, hospitals, skilled nursing facilities, home health agencies. And again, as Todd mentioned, quality measurement is still, despite a lot of activity over the past 10 years, still in many respects is in its infancy. So we don't have a lot of measures for certain areas, for certain types of providers. We have made a lot of progress on providers, a little progress on physicians, and then some of the other areas, not so much. And so, because of this alternative measure process, it gives people the tools to innovate, in partnership in many respects, with the providers themselves, to develop measures that are useful to everyone.
DR. GREEN: Without exception, I thought that your presentations were not only interesting, but they were fun. And I wanted to thank you all for coming. I would like to make a quick observation, but I mostly wanted to direct a question to any of you that would be willing to address it. The observation probably links most to Bill Davenhall's presentation, and it also cuts back to the initial slide set. This committee has learned over the last couple of years that there is an evolving contagion across the country, at the community level of communities, that are feeling like they need to accept responsibility for their own health.
And in the users groups that were identified, I didn't see community as a user. And yet, Bill was talking about linking data that are geographically relevant, and to get the accountability requires finally green data sets. That means this has to be driven down to local levels. And so, my observation is that we came to the conclusion that the country is missing a critical infrastructure. When you guys have succeeded at all of this wonderful work, how does it actually get sorted out at the community level, and where does that occur? Where is the organizational framework for that? My question is about workforce. There is a lot of analytic work to do here. Who is producing the analytic workforce that is going to be needed?
MR. DAVENHALL: I will jump in to that. Most of that is being done through community health advocacy groups, which DHHS has sponsored for many, many years, really empowering the local community. Most of them work, as I said, in murkiness. They haven't had necessarily the tools and they certainly haven't had all the data they need. So they are actually being forced to deal with national policy implemented at the local level in the absence of data.
And I would say when Todd first started to talk about the Blue Button, I said I want a Blue Button for communities. That is what communities want. They want their own Blue Button for their community. They want to know how their health as a whole community sort of speaks to the population health issue. But right now, to assemble that kind of Blue Button for a community, I would have to think about that for a while. That is not an easy go to create that.
MR. PARK: Just to build on that, actually interestingly, the entire health data initiative got started as the community health data initiative. Actually, it was initially focused on community empowerment and community health data. And so, one of the early products was this help indicators warehouse, where we, for the first time, amalgamated across every single HHS agency and other sources, like EPA and USDA, 1200 metrics of national, state, hospital region and county level public health performance, health care system performance, and determinates of health performance, like access to healthy food.
And that was actually where Medicare, for the first time, debuted a whole raft of prevalence of disease, prevention, quality, utilization of health care service data at the HR level. And it is available at HealthIndicators.gov, and it is available both as a website and via a webservices API, where people can actually access and integrate the data into lots of other tools, which they have done.
Now, one very interesting, speaking of the dialogue between suppliers and users, now they have actually made that data much more accessible and exposed to a lot more people. We are getting a lot of feedback about the many, many, many ways we can actually make it better. So actually, people asked for new indicators. So actually in March, there will be 53 new indicators, now derived from Medicaid, community health center population, new prevalence of disease metrics that Medicare has actually produced, Lyme disease, which I am going to check that out immediately.
A action second point, said you know what, I know why you did HRR. But you know what, I don't think of my community as an HRR. And in fact, the Los Angeles HRR, it is like a small country. It has got 20 million people in it, so it is not incredibly helpful. So one of the ideas that we have been exploring, actually based on the community Blue Button idea, based on Bill's comment, is called Choose Your Own Adventure, Choose Your Own Community Tool, where essentially what will happen is hypothetically, you could pick ZIP Codes and say that is my community.
And then, essentially CMS would auto calculate metrics, and it would suppress them of course if there were privacy problems, because there are too few data points. It would suppress if the statistics weren't actually valid. But they seem to recognize the fact that my community and your community may not be different. We may live in the same place, but we may have different definitions of community because we are both considering different things. And so that, to me, is just freaking awesome. And Medicare can do that because it's got all of this micro data that it can actually draw upon.
The third thing people have said is they have said it is great that you have this data, but it is from 2008. And so, he had the best zinger, and it wasn't aimed at us, it was just aimed at health care in general. He said health care data these days, and he was talking in the past, it's like having a speedometer on your car, and having it tell you how fast someone else was driving down this highway three years ago. Which I guess at some level, it might be useful, but really not very useful if what you are trying to do is optimize performance.
So CMS is actually going to be loading up very soon, '09 and '10 data, into the health indicator warehouse. And one of the things we are exploring, and I have no idea if this is actually doable, but I have asked Niall and Niall is an incredible dude and he does impossible things. I said well, what if we could actually present community health performance data, it yields agency services, quality, prevention, et cetera, quarterly, with a quarter lag. And Niall said, you know, let's take a look at that.
And I think the caveat of that would be, of course, that you haven't had 100 percent run out and all of the things aren't final yet. But I think people understand that. We live in a world where US government publishes GDP growth stats and unemployment rates every quarter, and then revises them later. And everyone understands, no one actually gets indignant when the rates get revised because they understand it is preliminary. They would much rather know what unemployment was last quarter in some reasonable timeframe, then have to wait for 18 months to actually get it right.
But again, the common denominator on all of that, it's actually going back to one of the themes I was articulating, is that we know this now, because data users came to us and said, if you did this, here is what we could do to improve health care. And so, one of the things I think this committee could do, one of the things I think we actually want to do in general is just get more of that to happen. And we will respond, especially now that we have a data and information products line of business, a specialized unit, that is going to focus on doing nothing but increase the access to utility of our data to improve health and health care.
DR. KELLY: One thing that I really do think will change things a lot in the next couple of years is the emergency of the ACOs, because ACOs almost always are local structures. In the ACO model, you begin to line incentives correctly. That local structure now has an incentive to keep people healthy. I will tell you, I spend my first two years at Aetna as the head doc for our large commercial clients. So I can tell you those employers that have large populations in those areas where there are ACOs are going to be very interested in participating.
I can also tell you that there are a lot of retailers that are out there right now, that are extremely interested in figuring out how do they play in the community to foster health. And if we get the incentives aligned at the provider level, just to keep people healthy, they are going to want to work with the community to lessen the incidence of diabetes and obesity and hypoglycemia.
DR. GREEN: How will they do that?
DR. KELLY: I think they are going to get very creative, because the best thing you can do is align incentives, and let very smart doctors and very smart providers figure it out. They will do it in a million different ways, but they will do it because they will have data to say you know what? I am actually going to not only improve the quality of my community, but I am going to get paid more if I have a healthier population because they are going to drive lower risk costs over time. So if you align the incentives and you empower people at the local community, they will engage the ecosystem in ways that they haven't, because the incentives have to be aligned.
DR. ROSENTHAL: That might be where the marketplace comes into play, as well. There is probably a dozen entrepreneurial groups that wanted to do something like this, to take a product out for these. Now that the financial incentives are aligned at the community level, they want to build something like this. I am thinking of three or four right off the top of my head. They kind of do it because they didn't have access to the data.
I think one of the risks, and I don't mean this is an real risk sense, is that you are going to have to be very smart about where you have official data products and information products and services, versus where you push things out and let the market take over. You can do that on your own, but to your point, you are already being incredibly intelligent about this. You are not going to be able to do it as smart as MIT Harvard kids, and that is where you need to let them do it. And there are a couple of dozen groups that are playing around, but wanting to bring something like that.
Now, why are they doing that? Why didn't they do it before? Because for the first time, the money is there, meaning incentives, so they are going to do it. And for the first time, the data is actually there to allow them to do that. So creating those conditions is absolutely imperative.
And on that note, if you ask how do we know what we need to do, you can always get user feedback, you can always have groups of people in a room like this. But what do we know and what do I know. If you actually build the infrastructure, you can do data driven product development, or data driven information development, meaning you look at what are the files people are using in the enclave. You look at what are the views they are talking about, you look at what are the discussions, and they leave the comments. You can definitely have the live stuff, it's not either or. And this is tried and true in financial services and ecom and everything else outside of health care. So you set up the incentives right, which you have done, that is why I said you have done the bulk of the heavy work. You liberate the data so people can come in, smarter people than anyone here, no offense, myself twice included. And you let them go at it.
DR. GREEN: I take it that none of you think that there are any workforce issues here.
DR. PARK: There are absolutely workforce issues. But supply, in this case, follows demand. And so, one of the things that happened at the last health datapalooza is the University of Michigan announced the launch of the nation's first consumer health informatics program, which they promptly stole Chuck Friedman from ONC to go run. But it is a joint venture of their School of Information, which is the rebranded School of Library Sciences, and the School of Public Health. And that will absolutely become the way of the future.
And their only problem is that the 30 people that they actually are going to graduate A) they are going to be 20 times that number that apply, and B) those people are going to be fought over viciously by all of these entrepreneurial groups and new outfits that are actually trying to build the services to actually help docs and hospitals succeed as ACOs. There is going to be, there already is, rapidly rising demand for this kind of expertise.
DR. CARR: I would just add, wearing my other hat at Steward Health Care, where we are one of the 32 pioneer ACOs, almost overnight, the dialogue changed and we have already created community health workers that are culturally compatible, to understand why the care that was given, now the receptor arm, why wasn't it working or why did they not follow up on the appointment, why did they not take the medicine, why did they not let homecare come into their home.
And it is very exciting to see, and I think in many ways, it is analogous, you put up the map or you put the picture, and suddenly it's like, oh, why didn't we think of that. So Bob, I know you want to speak, but we have Walter and Judy, and then we have public comments. So I don't know if folks will be around for a couple of minutes at the end, but I just want to make sure that we give fair amount of time. So it is Walter and then Judy, and then I think at a quarter of 4:00, we have two public comments.
DR. SUAREZ: Thank you very much for those wonderful presentations. I am baffled by the fact that we are not only seeing a liberation of the data, but we are also seeing a growth of the number of data collections and databases that are being created, which is a challenge, too. And that is the question I have, it goes out of my just simple count, we have HIEs now that are going to begin to collect data, or are collecting already.
We have certainly CMS collecting not just Medicare data, but also collecting potentially multi-payor claims data. We have states collecting data across the board. OPM, the Officer of Personnel Management, trying to create a federal employee claims base data. I think Bill mentioned the Health Care Costs Institute, where more payors are trying to get this.
One factor is all of this data still is a payor-based or a payor-driven data, or a lot of the detail and counter level data is coming from that source, which incidentally in light of the discussions that we had in the last two days on ICD coding, it is based on ICD coding. And it is based on ICD-9 coding at this point, so it will be interesting to see when we go to the ICD-10 code, the significant benefits that that will bring.
I was looking at the maps that you were showing, and I was dreaming of how, in Google, you can go today and begin to zoom into a particular area, and go even down to the house or the street, and how we could try to do that kind of same analysis on a particular condition or a particular topic in health, and go from the country to a state to a city to a block, and even to a particular location.
But my question is then, with all of this plethora of data sources and data collection efforts that are happening, how can we ensure that there is some consistency and harmonization really across them, so that when someone is doing an analysis on some topic, using some of that data, the results are not going to be widely different. And because again, Kaiser is an example. We are 10 different states, and the district we participate in a number of these data efforts. You can pull out data from each of those sources and come out with completely different stories about the same topic.
So how can we create that consistency in the source of the data, so that the analysis of the data, which is at end of purpose, will be coming up with consistent information and not misleading information?
MR. BRENNAN: So first of all, I bet Josh has some opinions to share on this. But it is sort of the classic, again, example of how data liberation or data sharing can actually help. Because right now, what you have is a lot of people analyzing their data in silos, and making individual decisions while I am going to attribute physicians based on a 30 percent threshold. But I am going to attribute physicians based on a 35 percent threshold, or I am going to say a gold star physician meets the clinical criteria, nine times out of 10.
And I am going to say a gold star physician meets the criteria seven times out of 10. And that is how you end up in a situation that Bill referenced in Massachusetts, where the group insurance committee gave combined data to different insurers, and ended up with one insurer said a physician was good and one insurer said the same physician was mediocre, and a third insurer said the physician was bad.
When you start to promote data sharing, I think that inherently promotes standardization and harmonization. Now, I am not saying it is going to happen by magic or it is going to happen overnight, and that is where also things like, I am thinking of George Thomas' stuff, Todd, better data tagging, like better sort of Medicare dual-eligible beneficiary like there is just one definition of what a dual-eligible is. And we know the data points that go into making them a dual-eligible, whereas right now, about eight people have eight different opinions over what constitutes a dual-eligible, even at CMS, let alone outside of the building. I don't know if anybody else wants to add to that.
DR. ROSENTHAL: It might be worth looking, I put together some of Hendesey's and my slides, addressing that particular issue, in doing it in two ways. But I am calling taxonomy, which means structuring the data in a specific way, and then sharing, which is clarifying it. And by that, obviously on one hand, data standardization becomes more important and more difficult. But by liberating it, it is going to naturally happen, provided you have some basic structure.
Everyone does taxonomy, you either do it well or you do it poorly, that is the question. And by that, I mean, please look at the slides. You will see you are going to have to get better about some of the basics, like consistency. If something is missing in a cell, you can't have free-hand typing three sentences and things like that. If contract entity means something in 2009, guess what, it means something different in 2010, you need to label it. So there are some basic things you are going to find around that. But by sharing that data with a community, putting in a center where you can capture that, the people doing that work will be your users largely.
But you do have to display your taxonomy, because you do have a relationship with the payor, the contract provider, you have various structures embedded in those files. They aren't available in the documentation. And by showing pictures of that to the users, that will provide the framework to allow them to do that work, provided you are actually able to allow them to share that. So on one hand, you are going to have to do a little bit better job around increasing the transparency of what you already done, because you have already done that difficult work and giving them the electronic means to share and do that work for you. And that is not unlike you find in other industries, by the way.
DR. KELLY: I absolutely agree with all of that. I also think, though, that the incentives in the new models, and the engagement of the consumer, I found if the consumer is a doc is actually a powerful QA tool. If they download a copy of their Blue Button and they are not on these drugs, they have never seen this diagnosis before, they are usually pretty vocal about it to me. So that, and actually the fact that, with the pioneer grants, with all these ACOs, we are jointly defining very specifically how quality will be measured, and how they will be paid. So I can tell you that people will now pay a lot more attention, at least those initial measures. So we are not going to get there overnight, but I actually think the consumer and these new tandem models will drive better data policy.
DR. ROSENTHAL: One other quick thing, these conversations are not unrelated. What are the meaningful quality metrics and what is the data consistently? Those are both around user creation transparency and taxonomy, to say I take this molecule and this molecule, and I combine it.
DR. WARREN: Mine is kind of very detailed. So when you talk about you can look at the data according to provider, what kind of providers can I find out information?
MR. BRENNAN: Are you talking specifically about 10332, the Medicare data sharing program that we have referenced, or sort of our more general ability to identify providers and our data?
DR. WARREN: Well, both. It was the former, but I want the answer to the second one, too.
MR. BRENNAN: Qualified entities will get 100 percent extracts of A, B and D data. So theoretically, that is going to enable them to measure any type of provider that we do business with, because the provider IDs will be available on the files.
DR. WARREN: And you're talking about NPI?
MR. BRENNAN: Yes, NPI will be on the file, and also some of the more legacy provider identifiers, like UPIN and the like. So you should be able to identify every provider. I know that there are some issues that were also dealing with, in parallel below other activities at CMS, regarding sort of like a gold record for providers, and ensuring that somebody really just has one NPI. But generally speaking, we believe the provider data is pretty solid.
DR. WARREN: So if I wanted to go into this database and find out for a community, what was the care provided by hospitals, long-term care, homecare, physicians, clinical psychologists, nurse practitioners, physical therapists, can I get down to that granular level?
MR. BRENNAN: So again, I want to make sure we are talking about the right thing. If you are approved as a qualified entity, and you have private sector claims data, and you combine it with Medicare claims data, yes, you can. If you are talking about the Health Indicators Warehouse, which is at the hospital referral region level, or future iterations of that, which may be define your own community, you won't be able to identify individual hospitals. But what you will be able to do is say, our long-term care hospital utilization rate is three times the national average, why?
Agenda Item: Public Presentation/Testimony and Discussion
DR. CARR: I would like to now open it up for public comment, and the first person from the state of Louisiana Bureau of Policy Research and Program Development, Lucas Tramontuzzi.
MR. TRAMONTUZZI: Thank you very much. I will be brief because I know everyone has flights to take. My name is Lucas Tramontuzzi. I am the chief data officer for the Louisiana Department of Health and Hospitals. I would like to thank this committee for the opportunity to briefly share one state's perspective about how we use data from CMS and from HHS generally speaking, to try to provide value for consumers and citizens.
The Department of Health and Hospitals contains both our Medicaid agency, as well as our Office of Public Health, Office of Aging, Office of Citizens with Disability and our Behavioral Health, in order to serve 1.1 million Medicaid recipients of our 4.5 million residents. And that number, 1.1, we anticipate to rise closer to 2 by 2014. And so, as a result, and going back to Bill's point, I saw exactly where those dark spots were on the map, and they were all on Louisiana. And so, it goes to show that we are ranked 49th for a reason, and it is a combination of uncoordinated care, we have patients with chronic diseases, with not the right management and engagement. And so, it is a big challenge.
We have a workforce issue. We do not have the horses in our analytic stable to try to address this as a department or as a state. And so, the one thing that we have to do as a state is really reach out to your private partners, public partners, in order to work together to figure out how are we going to address this.
And so, one of our challenges when it comes to data is how do we make sure we have the authorization in order to be able to work together, to make these differences. There are a couple of requests that I have made CMS, and that I have posted to this committee. We need to minimize the operational barriers to access the data. For example, the usability of parts A, B and D, the CCW versus the TAP files. We need to get the standard formats, the historic versus more timely data, it is an issue. For each year that data is delayed, it just makes it difficult to help build out things like the tumor registries and other data sources that we need as a state, not just the department, but as the state in order to provide better care.
Content, certainly we are all uber concerned about ensuring confidentiality of our residence. There is technology in place, we can use double hex encryption. There are ways to do it and we shouldn't allow that to be a barrier. But we really need to have conversations very quickly about how do we best do it, so again, we are not having these massive data dumps into places and trying to do it after the fact. We need to really think more forward about how could we do it, so then that way we could start linking it appropriately and start doing some amazing things with it.
The next is the standardized and the practice of the painting the data. We states have gotten very good about sharing the ways in which we are able to get it. Hey, this is my application, this is what I wrote. Here, you try writing the same thing and see if you can get the data. And sure enough, it doesn't work out. And so, we really need to work together to figure out how do we make it more predictable to do that.
The other thing is, it is very, very difficult just to try to anticipate tomorrow's research questions. So when we request the data, we have to request it for a specific use. But if something comes up tomorrow, we can't use the data to research that question. And so, we need to be allowed some flexibility in what we can do once we get it. Again, we want to make sure it gets used appropriately. Hold us to those high standards, and prosecute us when we don't meet those standards. But we need some flexibility.
The third part is emergency management. The MDS data is invaluable because it is our only source of really knowing how is in a nursing home. Two hundred and eighty two of the 285 nursing homes in Louisiana report to MDS. When a hurricane comes in, we need to turn on our systems. We are not allowed to bring that patient level data into our management system. So when a nursing home evacuates, we don't know who is in that nursing home. Unless we ask the nursing homes to actually type in each recipient that they are moving. It is a waste of time.
They need to be working very quickly to get those patients out of there, instead of trying to report to us, again, the state, not the department. The data is already there. Help us leverage that, so then that way, we can put emphasis on those time-crunching moments into the right activities.
Another part is just coordination with Social Security. It is nearly impossible for us to manage the eligibility between Bendix and the EBD as we manage where these recipients are going. We need better cooperation with the other federal agencies, because again, we are just losing time and energy, and trying to match who is going to qualify for whatever the appropriate program is.
The last time I ask is your support, and we support Todd and his initiatives to formulate these data commons for researchers and others, to leverage in a way that is meaningful. Not only for the community, because again what we see in Louisiana is that it is at that level that we are going to get the impact.
Also, allow us to work with you, to develop a single Blue Button, a single place for our residents to get all of their data. It is great that you can do it for CMS, it is great that you can do it for Blue Cross or for the other ones. But as a parent, my children's data is with one provider, my wife's in another, I am in another. By the time we get to CMS, our data is all over the place.
We want to work as a state to be able to unify in one place, so then that way, from the user standpoint, I don't have to fish for it. It is all right there for me, as I move across the system from private insurance, eventually into Medicare, if it still exits. But again, it would be nice to have it in one place, and to allow states to work with you, to kind of bring it together. And with that, again I would like to remind the committee, please be agents of change. States are so reliant on you to help guide. You really are in a unique position to help move us all along. And again, I thank you for this opportunity.
DR. CARR: We have one additional public comment, from New York City Department of Health, Pat Lynch calling in. Do we have Pat Lynch or designee calling in? Okay.
MS. GREENBERG: I just wanted to make sure people also realize that they can submit comments.
DR. CARR: While Marjorie is looking for that, is there anyone else in the room who would like to make a comment?
MS. GREENBERG: To CMS.data@CMS.hhs.gov until March 16th.
DR. WARREN: I have a question. Given the nature of our discussion and debate about ICD-10, what would be the impact to all of the ability for you to mash up your data and do reports, if we delayed implementation of ICD-10? And I am especially interested, as you start describing communities and populations.
MR. BRENNAN: Well, I would say we are reasonably comfortable with the way we use and analyze ICD-9 data. So if ICD-10 data were delayed, it wouldn't necessarily affect many of our current and projected plans. What it would effect would be potentially the content of some of those products, because ICD-10 has so much more granular detail.
DR. SUAREZ: Have there been any analysis on your part then on the benefits of having, and perhaps even examples, data quoted on ICD-10, to generate some of the reports, and some of the information that you are producing? Has there been any examples or analysis done about that?
MR. BRENNAN: To be honest, that is a little bit outside of my personal bailiwick. CMS or I don't know if other health plan reps, or Todd wants to comment. Again, I obviously know that ICD-10 is considered by many to be a much richer source of coding information. But let's not forget that ICD-9 is five or however many thousand ways of identifying clinical conditions, too.
DR. CARR: Okay, I think with that, I would like to make just a couple of closing comments. So NCVHS has been in existence for over 60 years, coming up on 63 years, I think. And as you look over the history, there are kind of moments in time that ignite excitement and change and imagination. I think in 2002, 10 years ago, we published Shaping Health Statistics Vision for the 21st Century. And interestingly, at that time, we identified that the population's health was about health and disease, but functional status and also wellness.
But we also identified community attributes, context place and time. And it is very exciting that now 10 years later, when we look at the way we are now taking the data available to us, and putting it on maps in communities, mixing up medical data with community data, financial data, employment data, we are actually approximating what was the vision for the 21st century, 10 years ago.
So I want to thank you tremendously for your very exciting, illuminating and stimulating presentations. You have really inspired us by your leadership and sparked our imagination by your creativity, and we look forward to ongoing collaboration and participation with you, at any time, in any way that you see fit. So thank you very much.
And with that, we will adjourn the National Committee on Vital and Health Statistics meeting. Thank you very much.
(Whereupon, the meeting adjourned at 4:00 p.m.)