[This Transcript is Unedited]
National Center for Health Statistics
3311 Toledo Road, Auditorium A
Hyattsville, MD 20782
DR. CARR: Welcome to the second day of the NCVHS Quality Subcommittee Hearing on Meaningful Measures. Yesterday we talked about the meaningful measures supply chain and building measures that matter. Today, we are going to continue that discussion but in light of national priorities we ended the day yesterday with care coordination. Today, we are going to be talking about value and efficiency, population, and disparities.
What I would like to do then is start by going around the room. I am Dr. Justine Carr, Co-Chair of the Quality Subcommittee, Member of the Full Committee and from Caritas Christi Health Care and I have no conflicts.
DR. TANG: Paul Tang, Palo Alto Medical Foundation, Member of the Subcommittee and the Full Committee, no conflicts.
MR. QUINN: Matt Quinn, Agency for Health Care Research and Quality, Health IT Group and I am Staff to the Quality Subcommittee.
MS. JACKSON: Debbie Jackson, NCHS, Committee Staff for NCVHS.
MR. MOY: Ernie Moy, AHRQ, Center for Quality Improvement and Patient Safety.
DR. CLANCY: Carolyn Clancy, AHRQ, I work with Ernie and Matt.
DR. FITZMAURICE: Michael Fitzmaurice, Agency for Health Research and Quality, Liaison to the Full Committee and Staff to the Subcommittee on Quality.
DR. GREEN: Larry Green, University of Colorado, Member of the Committee, Member of the Subcommittee, no conflicts.
DR. SCANLON: Bill Scanlon, Health Policy R&D, Member of the Committee and the Subcommittee, no conflicts.
MR. REYNOLDS: Harry Reynolds, Blue Cross Blue Shield, North Carolina, Chair of the Full Committee, Visitor to this Committee and I have no conflicts.
MS. KANAAN: Susan Kanaan, writer for the Committee.
MR. CARLTON: Tom Carlton, Blue Cross Blue Shield, North Carolina, Director of Information Strategy.
MS. VIOLA: Allison Viola, American Health Information Management Association.
MS. HOLMES: Julia Holmes, NCHS, I work in the Division of Biostatistics.
MR. ROSKI: Joachim Roski, Brookings Institution.
MS. CHRISTIANI: Jeannine Christiani, Contractor for the Committee.
DR. CARR: Paul and I, wanted to start off today with a little bit of a recap of some of what we heard yesterday. We stated out the day hearing from Helen Burstin and about work that is being done in the National Quality Forum, with a focus on shifts to composite measures, measuring disparities in all that we do, harmonizing measures across sites and providers, promoting shared accountability and measurement across patient focused episodes of care, and focusing on outcome measures, appropriate measures, and cost and resource use measure, coupled with quality measures.
We also heard interesting work by the American Board of Internal Medicine or American Boards. I think what was interesting about that was the work that they are doing of having providers look at a population and look to see whether they have achieved all of the appropriate care delivery elements. I think what was so impressive was the engagement that came about because of that and finding gaps and then addressing them. It weighs the issue about engaging providers in these measures, having them be meaningful to the providers, and also I think as Frank Opelka said, making them actionable so that when you look at them you can deal with them.
Another point I think that came out yesterday also, was in terms of actionable, to not just have the element, but to have the capacity to drill down and stratify the groups and subpopulations. We also heard about in the PCPI Model, integrating quality measures into EHR and focusing on the timeliness of the data, having it available, also the incubator groups and working through things.
I think that several questions emerged in our conversation at the end of the day. I think one was is there a strategist for measurement? Who does that, who holds that role? We heard actually many excellent presentations from different groups but they were not the same, they were different approaches to the same thing. The question is, how are we going to reconcile all good approaches but not the same because without that standardization the vendors cannot make EHRs that approach these. We know that NQF is updating the endorsement criteria and measure developers are developing measures. I think what we were wondering about is are these new measures, are they a retool of old measures, therefore, the CHIM I think was very interesting. I think that Matt brought up a great point at the end of the day. What about the world of social networks because we are trying – we are gathering data and do we get data from that.
I think a lot of the conversations came out at the end of the day when we heard about work that is going on about coordination of care from NCQA. I think it raised the question of what is a publically reported measure and what is performance improvement. Performance improvement being done locally and public measure being a simpler thing that is outcomes oriented, that engages and raises awareness that is an important element. It is something that triggers a response for improvement but is simple and compelling.
We had concerns about the prescriptiveness of what we heard yesterday because it sounded more like QI and it sounded like it was going to take a long time to get the multiplicity of measures that were being put forward.
The two other things, who drives and enforces standardization? That includes not just the measures but for the risk adjustment algorithms. Then also, as we heard more and more we really have been implicit in all of this measured development - is the need for a data aggregator that even EHRs with good registries may not have all of the data elements that are needed to create the denominator or to risk adjust or to identify and exclude.
DR. TANG: So maybe one of the things that we tried to examine yesterday was what are the attributes of a meaningful measure? Some of the characteristics that I think that would drive our health system forward rather than backwards is if the measure were inspiring, engaging, and actionable as Justine said. Those are things that need to pull the health professional team forward as well as the patient and be understandable. What we do not need, and I think that some of this is tethered in the days when we only had administrative data are measures that are prescriptive, that are burdensome, and that add cost to the system in a sense. It has been said, no money, no mission. In an era of health reform where we want to have an option other than paying for volume it may be no measure, no mission, and perhaps no money.
I think that we really want – as we look forward to today particularly, Carolyn’s remarks, in what is the vision for the future of measurement and its role in driving and not just retrospectively reporting on the health care that we provide. So it is with great pleasure that I introduce Carolyn, I think to say that she is the head of the AHRQ would be an understatement of her accomplishments. To say that she is a champion of research and quality would equally be an understatement. I think she is a champion and leader period of all things related to health and health care. Probably the thing that most aptly characterizes her is when Mike Fitzmaurice said yesterday that, when the Secretary announced that she was appointed to the Head of the AHRQ during her administration and you had to tie people in their seats to stop the applause. I think that is the indication of the respect and adoration that folks not only in her agency but around the country have for her. So it is with great pleasure that I introduce Carolyn Clancy.
DR. CLANCY: Good Morning everyone. First of all I have to say thank you for all of the fan notes about Matt’s work with this particular hearing. We know he is terrific but it is always lovely to hear and you really did put together a fabulous agenda. Between Matt’s wrap up and your key points just now I think that I have got a good flavor of what I feel a little bit deprived about missing especially, since I spent a good chunk of yesterday sitting like a sardine in an airplane.
However, if there was one take home message that I have is to be one of excitement and humility; excitement because of the possibilities ahead, humility because it is going to make us confront all of the weakness of what we have been doing in assessing and improving quality. Peter Pronovost has probably done more writing on this in a mainstream medical way than anyone that I can think of. This issue of data aggregation and enforcing standards and all of that, we do not do that at all. I mean we have got the threat or perceived threat of the occasional audit. It is not even clear to me that the auditors actually know what they are doing. I mean if we were to really get extremely concrete about it a lot of what we are seeing and reporting is self reporting. Now with that said it is a very powerful tool and it is probably one thing that there is actually bipartisan agreement. I do not see this actually going away. I am really thrilled to have an opportunity to share some thoughts.
I think the other message I would leave you with is it is really hard to transition from a world where we have always asked the right questions. What is important? What is the greatest burden of disease? Where can clinical care make the most difference and so forth? Then it gets to that final funnel of what can we measure. Feasibility drives all existing measurement activities. It is very hard to transition from that to saying, wow, we can see right over the horizon a health care world where data will be ubiquitous and the question we ought to be focusing on right now, if not before this is what do we want to measure. My own personal hope is the phase of retooling the existing measures or retooling EHRs to capture some imperfect measures has assured us that we can make it although, I think it is inevitable that it will be there.
I am going to hit on just a couple of key things here given the time and really the incredible opportunity for conversation I am not going to spend a lot of time on each slide in case any of you are nervous.
Obviously, a lot of very, very important activities, I am sure that you have heard about the national priorities partnership from Helen Burstin yesterday which although it is still 15,000 feet above the ground, we are down from 50,000 feet above the ground. It has been an exhilarating experience to participate in that, to really step back and say okay, what makes a lot of sense here. The reason I think that is so important is what I just heard from the two of you actually has an adherent conflict. Paul just described what I as a clinician, believe in my heart of hearts, you give me information that makes me say thank you and makes my job easier. Wow, that is fantastic. I have heard clinician friends say that to me.
At the same time, many stakeholders think that there is actually quite a bit of good to the just pure old accountability fashion and making sure that people are actually checking the boxes. That is part of a democracy so most of our efforts in getting to quality measures, approving them, and endorsing them, and so forth have been a very large exercise in small democracy. In some cases, we have really let go of what is very important. If you think about it what makes clinical medicine intensely interesting is not saying, being a hamster on a treadmill where you do exactly the same thing every single day. It actually is taking scientific knowledge and tailoring and customizing that for the unique needs of an individual patient. Most of our measurement enterprise does not reflect that yet.
I was saying to Justine earlier, I think that some of the leading edge institutions in terms of improving quality are starting to get that. I heard someone tell me yesterday for discharge instructions, what many people actually do is – or what a number of institutions have figured out to do is everyone gets the basics and then they ask for a read back. Those people who clearly get it and are clicking and do not need the extra supportive services and so on and so forth may have less complex illness, they say, goodbye, good luck and we hopefully see you elsewhere but not here. Other people, they use that as almost a screening tool. I do not think we have been very smart about that at all. Of course, we all want outcomes and so on and so forth. We have given very little attention to either in the development of guidelines or on measures thinking about workflow and I think that is very critical.
We do not know actually very much about the methods to do this and when we get to the efficiency one of those e’s in the six dimensions of quality, we know very little. By the way, for health reform, what everyone wants is high quality, affordable care. They are not looking at us just continuing to spend a whole lot of money and you know, measuring and making better report cards. The question is when are these external, transparent comparisons helping our cause and when are they not? I sometimes think that we have gotten so granular in clinical quality measures NQA was endorsed over 500 I think. Some of that has to do with the fact that there are so many physician specialties that it feels to me again, like when the pilot gives you too much information. I do not actually want to know what is the problem today. What I want to know is are we taking off or not and do I need to make alternative plans. Clearly, I think that there is a huge interest in making this information actionable. This is from a slide about efficiency measures which I think is a huge, huge gap in the landscape. I think that what we are very good at with the proprietary tools as far as I can see, is actually pinpointing that sick patients cost more. Wow, a pretty profound, I will leave it at that.
Frankly, I would say that we were much more excited about our efforts in improvement. I pointed out the Keystone Project and NSQIP here because that actually is closer to the vision that Paul just described. When people collect enough data that is actionable and helps guide their efforts. But that is the fundamental purpose for collecting the data. NSQIP started off in VA and we actually gave the College of Surgeons a grant to expand it to a couple of hundred of civilian hospitals. We are very proud of the CAHPS surveys but sometimes it feels as if we are going to spin it off as an independent company. Ultimately, we have got huge challenges vis-à-vis attribution, right? On the one hand we are busily developing measures to assess the efforts of individual members of the team and yet what gets people really excited is the curriculum that promotes good teamwork, a skill that is terribly new to most health care professions.
This little picture here is intended to be from the slide about the fact that there are still institutions and organizations purchasing electronic health records that think that somewhere in that box of instructions and all of these computer guys who now live there full-time, is the instructions on when you hit F7 to upload your quality measures. We have electronic health records that support a transaction-based system that rewards volume rather than quality. It is not remotely surprising that registries are an exception rather than the rule and that the ability to actually give us any information about like groups of patients is primitive as it is. It does not mean that we are not there and we are very excited about some of the work that the Health IT expert panel that Paul chaired that actually led us to begin to pave a roadmap from our imperfect world today to a better place in the future.
Obviously, this is complicated stuff. I think the one bright promising start here is the Recovery Act which gives us a huge amount of resources, both in comparative effectiveness and in Health IT. I see, and we have gotten very clear feedback from Congress, it is not intended as a job function but really is intended as a down payment on the scientific infrastructure that we are going to need to make health reform sustainable.
We know that Health IT could make a whole lot of this easier and sooner or later, I must have heard this from Larry Green at some point, because it feels like something that he would have said, sooner or later we are going to back into the question of why do we collect data and what data do we collect as a part of routine care makes sense anyway? It is an issue that in my view has gotten very little study. Don Berwick once pointed out to our Advisory Council that if you were to look at hospital charts today, the structure in terms of how we record information has not changed in at least 50 years, the antibiotic names are all different and so forth and more gizmos and technology that we are dutifully recording numbers from, but the actual process of thinking about what information do we need to provide care for a patient? What is the purpose besides billing? It has not gotten any systematic examination at all.
We have been very pleased to be funding some of this work through our Health IT portfolio and also through one of our search projects. Again, this is largely retooling existing measures and trying to figure out how easy or challenging it is to do that.
One very exciting area gets to the issue of data aggregation that one of you raised. Two years ago, we actually funded some prototype distributive data networks, at least one of which as I understand, has just gotten a boatload of money from Recovery Act funding from NIH and I think that Larry Green has been very connective to the DARTNet Project.
One of the strategic issues which we have not addressed in discussions about Health IT, quality, or anything else, is do we imagine that data aggregation in the future is going to be a centralized repository model or that we will have regional aggregators with common standards that are audible and all of that kind of stuff for those aspects of care that we do want to be publically recording.
This is actually groundbreaking work in terms of figuring out how challenging it is to develop common definitions and infrastructure as we are focusing on trying to make electronic health records more useful for conducting comparative effectiveness research. My understanding of why the clinicians in DARTNet, this is a practice network of relatively small practices working with some hospitals in Colorado, why they participate, what they get back. I think that is going to be a very critical piece of this that we do not give enough attention to at all. What do I as a clinician get out of this? What is the incentive for participation? What they did was quality benchmarks which is very helpful to them to know how am I doing and where can we actually improve our efforts. Many people, including Farza(?), the Deputy Director at ONC, believe that distributive data networks are definitely the future. I can tell you right now, having done a request for information on a data stewardship strategy a couple of years ago we have got almost no insightful comments; we got lots and lots of comments about privacy, a ton of them. That was about 70 to 80 percent. So we cannot let go of that in terms of making sure that that is factored into the strategy as well.
One of the things that we are very attentive to at AHRQ these days is the fact that it gets very easy to focus on data all of the time rather than information that you want. In fact, I would have to say, I think this is an area where the federal government excels. We are absolutely fantastic at building databases that you can send us data to and if you are lucky we will let you know that we received your submission but do not necessarily do anything for you. I think right now we are hearing hospitals rebel a little bit about this for health care associated infections, this is actually a fabulous research database and for hospitals with a lot of infectious control folks it is terrific. For small community hospitals it is kind of not working for them and it is much more intense than they need to guide efforts to improve it. That kind of interaction and figuring out what is the incentive for collecting and reporting data I think may need a whole lot more attention.
One of the areas that we have been very excited and actually have some clear resources is looking at CHIP and Medicaid. For a variety of reasons, all of which have something to do with the fact that CMS has been able to use QIO resources for much of what has been done in quality measure development and they have done a fantastic job. But you cannot use that for people who are not in the Medicare – you cannot use it for any work that is not potentially relevant to Medicare.
Kids have kind of been left behind. So the CHIP Reauthorization Act lays out a very thoughtful quality roadmap which effectively says, the Secretary will release a list of measures to be voluntarily reported by states in January 2010. Not a lot of time to do this in 11 months. Not a lot of time for the usual process. This is not going to NQF; this is leaning very heavily given the economic climate that states find themselves in on measures that are already in use. Because we have had an interesting transition here in terms of people coming into leadership positions recently have stepped up to say, you know we have got a terrific advisory council and we could create a separate advisory group much like the AHIC used to do to focus on this. We have had lively, intense multiple stakeholder discussions about, why don’t we blow this up and start with much better measures on the one hand and states on the other hand telling us you know, last year my quality department had 20 people, this year I have 4 and I do not know if I get to keep them so I have got to lean on what I am doing already.
The good news is after that effort there are actually clear resources identified in the bill for moving forward, both for developing better measures and for developing a pediatric electronic health record, whatever that is exactly. I am here to tell you it is not a smaller one in difference to people whose main passion in life is providing and improving child health care.
I think that there is a really important opportunity for synergy there so your efforts could not be coming at a better time. A lot of money and comparative effectiveness, the only details that I would call to your attention is the Secretary’s money gives us a lot of opportunity to focus on infrastructure that we will not ever again have an opportunity to make those investments. So big investments coming and I cannot give you much detail now because we are still in that intense multiple conversations with the OMB period, but big investments coming in infrastructure, all of which I think or much of which can actually be focused on assessing and improving quality of care as well.
The Institute of Medicine gave good guidance here as well. It also focused on some infrastructure needs as well as a list of the top 100 specific questions that they felt were very helpful. Notice the word prospective registry here? Clearly that is relevant both to conducting research and also to assess quality of care. I think that what we have got to figure out is how can electronic health records through the meaningful use incentives actually pre-populate some of these registries? We have seen these be incredibly successful are from those organizations that have the resources to pay a dedicated data collector, you know it is a standalone effort but I think it has got to be a much more organic connection with the delivery of health care.
Ultimately, what we are trying to get to I think is an information-rich patient focus health care system. The glimpses of this that I have seen at some organizations that I think have begun to take these challenges on very seriously are that it literally transforms interactions from reactive, as in what are you doing here today, in so many words; to an interaction that is proactive, where the clinician and the patient start this conversation based on how they have been doing, what preventive care they need, that kind of thing. It is not that doctors do not aspire to do this. It is just finding that information is painfully difficult because for those of you who are clinicians, I am sure you have had many of the same conversations I have had with patients over the years. I would just like to hear about this in your own words again, to make sure I have a clear understanding of the problem, which really means we cannot find the chart again. Clearly at AHRQ, we believe, and you will hear much more about this from Ernie and Kalahn, that quality and disparity have to be linked very tightly and that is also a strong focus for the investments we are going to be making on behalf of the Secretary for comparative effectiveness.
We are talking local data here now, okay? We are not talking a huge centralized repository because it is a given both from what we know about disparities as well as what we see in the Dartmouth Atlas that the solutions are likely to have to be fairly customized to particular communities. That does not mean that there is not generalizable knowledge. I think it stands to reason that, and the Mayo Clinic can tell us what works well in Rochester, Minnesota does not necessarily export easily unmodified to Jacksonville or Scottsdale. I think that we are going to see that from many aspects of quality improvement. Clearly, with the reform momentum that we are seeing, with the opportunities in CHIP, your timing could not be better. I really do want to say thank you.
The good news is we have got a lot of opportunities to improve which I guess on some level means that it is hard to make a mistake. We have got a lot of opportunities to connect the dots. If there is one area that makes me humble it is that we rely a lot on Paul Tang and Janet Corrigan to be bilingual in the language of Health IT and quality assessment and improvement. They need a lot more company. Those two communities by and large do not overlap a lot.
I think that the meaningful use incentives will actually make some of that happen kind of logically. A lot of organizations now are hip-deep in electronic health record implementation but I will tell you what, one huge challenge with electronic health records is still going to be as far as I can tell, there is not a killer app that makes any clinician’s day easier because they are using an electronic health record. You can say it is professional confidence and I believe that with all of my heart but boy, it would be lovely to make it fun as well.
I am thrilled that you are thinking about social networking. You know the importance of a roadmap which is what I heard from both of your comments, I think is self-evident. I will stop and I would like to just sit down so we can have some back and forth if that is okay.
DR. CARR: Thank you so much Carolyn.
DR. TANG: One of the things that we forgot to mention about Carolyn is her tremendous eloquence and intelligence, sheer intelligence. I always enjoy listening to you. Some questions maybe about maybe the future and thanks so much for your presentation and guidance.
We heard a lot yesterday about more measures about components and processes and we sort of took a pause and said, look as medicine gets more complex, maybe paradoxically, measures should get simpler and maybe even both the who is queried and who benefits is different. So should we just outright ask the outcome? Justine suggested, can’t we just ask the patients, were the discharge instructions clear rather than, were they printed, were they handed, were the et cetera. Then maybe we will get closer and closer especially in today’s world – because I think in general the health literacy and the appreciation of what it takes to get something out of your encounter with your health team is getting more and more understood by consumers. Not that it is just missing but that we do not still have complete health literacy across the entire population. Just because of the internet people are more engaged. Perhaps asking patients more about how we are doing is our version of social networking because they are used to rating, they are used to reviewing, they are used to providing each other information. Maybe we can just actually learn from that. That is one piece.
Another piece is you have talked about what is the killer app? I certainly have felt that in our practice, my killer app is actually getting that data back. So you mentioned the bidirectional. There is this huge sucking sound. Data goes in, 18 months later something comes out and has something to do in theory with what you are paid, you know, your pay performance. Nothing is relevant. You give data and we give data back but this is on a quarterly basis, plotted and transparently so everybody can see everybody’s data. That really riles them up. It almost does that magic killer app; you get that killer app sense when it is probably going to change the next diabetic you see today because of your score this quarter in a sense.
So I wonder if we do help some of those keys, and someone yesterday was saying, you know what, well, we do not have a lot of power. I think that as you said the whole Recovery Act and the stimulus money indirectly and directly means that the people who are designing the measures upon which we are going to be judged have a lot of power, a lot of transformative power as well. To draw a couple of your messages; one, is looking for a killer app and maybe the bidirectional, the feedback, the timing feedback may be one of those killer apps because that is just how physicians are. But anyway, comments on getting simpler measures, fewer of them, more outcomes oriented, and from the patients.
DR. CLANCY: So I think those comments are really terrific. You know one killer app that I hear lots of doctors asking for is actually figuring out could they get information about which of their patients is having challenges adhering to medications. Most of the time we actually do not know that in a clinical encounter so what do we do? We go into the same usual collusion routine where both sides are pretending that everything is fine. Then we say, we give patients the same kind of little sermon, you know, it is really important to take those medications. Okay, see you in a few weeks. It would be really terrific to know who is having challenges or not doing this. Now this gets sensitive. Maybe some people do not want to but again, it would be something that helps me customize what I need to do and also helps me know where I need more effort.
I actually have moments where I think the key; the magic to fixing health care is actually two things. One is some strategy in place to systematically look across an organization or a practice or whatever the unit is, I do not know weekly, pick your timeframe to say, where did we screw up this week. Where are we dropping the ball? Who did we refer that got lost or whatever the issues are. We do very little about it.
My favorite example is radiologists I gather can buy a CD with mammograms because we know that volume has a strong relationship to quality and skill there. I have not actually found anyone yet who systematically looks at their own performance in practice which I think makes a lot of sense. To the extent that board certification is promoting that. I think it is great but it is not just about reading a mammogram. A lot of this is about people get lost. That is actually what causes the lawsuits or at least from what I read. I do not know if I have got a good database for that as much as whether the film was read correctly. Yet, we have got a system that actually has people reading these things at home without every looking at whether their system is working for patients.
The second thing, for me would be something about being responsive to patients. Now, with that said, I think we have got to be a little bit more activist about it because I think, I cannot be the only person who has periodically heard or even received things that basically say, if you rate me well as a mechanic or whatever, I mean I am not even talking about medical care, I will be really pleased and it is really important to me to get recognized or rated well. I do not think that you want to push people into a situation where there is a clear imbalance of power and say, how are we doing?
Read back has a lot of appeal to me. I did not actually learn that in school or training at all. I learned it when I worked at the free clinic and I heard a pharmacist do it one night on the other side of our dividing wall. I did not even have a name for it but I knew it was powerful. He downloaded the instructions and all of this and then said to the patient, tell me what you heard. Wow, again, I did not know what it was but I knew it was really big. When we began using that in our clinic it made a big difference.
DR. CARR: Just to add to that I think one of the models in safety is to say the percent of patients who left their hospitalization with no errors, no near misses, that everything went perfectly and it was a sobering number.
DR. SCANLON: Thanks very much. I think you touched on a number of important things. I guess I also for one would like to highlight a sense of urgency, particularly with health reform. In many ways, what we are doing now is an evolutionary process which may end up in a very good place but it is taking a long time. Justine pointed out the problem, well what are vendors supposed to do in the interim as we keep changing what we sort of want?
I wanted to talk about something that actually is being discussed at MEDPAC and it is likely to lead to a MEDPAC recommendation next month. As part of a congressionally mandated study to look at the issue of comparing Medicare Fee for Service with Medicare Advantage Plan, the idea is what we should be doing is we should be asking for more information from providers, through using electronic health records and meaningful use. It is asking not for measures but in some sense the building blocks for measures because if the measures are things that we are going to keep changing. What really need to think about what is it that we can use as the component of measures?
One thing that comes up and this is an old MEDPAC recommendation, is we should be getting lab values. HRQ is showing that we had a hearing a number of years ago where this makes a difference in terms of risk adjustment and obviously in payment policy that is a critical thing. I guess the question here is kind of how much should we be moving down that path because it seems like it is a faster path and one that the vendor can deal with more readily and there would be fewer adjustments that would need to be made over the short term. Over the longer term we may get a whole different set of building blocks that we want get incorporated into the information that we have.
DR. CLANCY: I think you are definitely on to something there. I do not know to what extent the Health IT expert panel got discussed here at all but the general gist was to say, of the 500 odd measures that have been endorsed can we find a subset that we think are probably more important? You know, care for heart attacks, we want that to be good. You know some other very narrow focus the process measures are not quite as important. If you create that subset can you identify data types or components as you would say, that are important. I sure would not want to steal Paul’s thunder here, he did a spectacular job of leading this but I think it is exactly the right approach. There are some big training implications here as well. This is not part of how you are trained at all. Doctors are trained with two themes in mind. I think nurses and everyone else says pretty much the same thing. You do the very best you can with each patient and you move on to the next one. The notion of looking back just is not there at all. The other major thing for doctors is they are not all that great at peer review because I was not there. This doctor may have seen something important that was not described and captured and all of that. I think the components are just right. I certainly did not mean to diminish urgency. I was more trying to say that –
DR. CARR: Yes, I mean just in terms of the components, just thinking about if we collected times of everything. You know the measures we could construct of timeliness would be huge. I mean we do not need to know which measures those are but if we had the times we could do that.
MR. REYNOLDS: Thank you, always outstanding. So as we hold this hearing, as you know, we usually move forward with some kind of comments, recommendations, or something. So you get to write it this morning. What are our focus areas? We might not get a chance to talk to you again before we do this. Give me a framework where you think we could make the most difference. What we could do, just those things.
DR. CLANCY: I think we need more work on the level of attribution. There are two things inform my saying that.
Number one is to look at disparities you really cannot do that for very many conditions at the units where people get care. It is too small. In hospitals, only a fraction can even report on stratifying measures even for heart disease because you just do not have a big enough sample size. So we say, yes, we want to do that and then we go away from it, we have not said, then we will report at the state level. I think Massachusetts is doing some of this which is really terrific that they can say to you confidently a proportion of Hispanic patients who report that they have got a usual source of care has gone up dramatically. We are very excited about that. I think that has got to be part of the roadmap moving forward.
I do not know what the rest of the recommendation is. I have to think about it but I am in touch with Justine on a fairly regular basis and would certainly be happy to share something. I also have not had a chance to do brief with Matt because we have been in different places.
MR. REYNOLDS: So I am going to ask you just a little differently then so, yesterday and I am sure later today, there is as Justine and Paul noted there are a lot of people working on these measures. Where are the clear indicators because if you have 10 working on it and we need to move it to speed that it has been mentioned at, where should the focus be at least in the short-term to kind of get a –
DR. CLANCY: I am very pragmatic. What I would do frankly is look at the current drafts of health reform bills and figure out what are some common elements. Secretary Sebelius, when she visited last week said she herself was humbled by the number of sections of these bills that start off, the Secretary failed… Now my interpretation of that having had lots of conversations with folks on the Hill is the Secretary shall often precede an area we do not know what to do. We do not know what the ideal data collection strategy is but you know what, it would sure be helpful to do that.
I think if you were to take a look of some of those components of bills which in the town hall meetings and that kind of intense period feeling have gotten less attention; it is pretty impressive what is there. I would be using that as a map for how this committee can help and know potentially specific elements that are not there. That is okay for a bill but it will need attention by HHS because someone is going to call this party. When you asked about who is the strategist, what I have noticed in recent years with absolutely no resources is everyone thinks that they are a strategist. I will include AHRQ in that. Everyone is thinking about these grand designs and plans, now we actually have an opportunity to make this real. That is incredibly exciting.
DR. GREEN: Carolyn, first of all, one comment and then Carolyn I would like to ask you to just talk more about two or three other things that you mentioned.
The comment is this conversation plus yesterday’s is merging for me around an unstated assumption that I want to make explicit. It is the assumption that we have to gather a bunch of data and put it somewhere in proper fashion and way so that we then can use it to get the answers that we seek. Of course, we do not agree with what the questions are. We actually do agree that we do not know what the questions will be. Now we know the timeframe is such that a development of a measure in this sort of assumption that probably by the time that we are ready it does not matter particularly in the face of health care reform.
Carolyn mentioned DARTNet briefly and I only know enough about this to really be dangerous but there is a concept here that I want to get out on the table. It is the concept that you go get the data you need at 2:00am in the morning, when you know what the question is without ever acquiring the data. That is the fundamental, transformative idea in DARTNet. What these guys are doing is they can now do it for six or seven of the big EHR vendors.
While you sleep, the clinician or the patient at 2:00a.m., there is a data query that goes to the EHR and gathers the seven measures from the clinical database that enriches – we have only talked about how to enrich the administrative database forever. It can unite those. It can query that administrative database, the payment, the services, the CPT 4 numbers, the codes, whatever they were. It can also go in and grab the lost charts and non-lost chart, that record, and get the blood pressures for everybody that is on this list. It leaves the data there. There is no consenting. There is no IRB. There is no privacy and confidentiality. The d-identify comes back and there are 29 of them and 28 out of 29 are in target range. One is not. From a system level you now have a 28 out of 29 performance measures of some sort and from the local accountable care organization or the accountable clinician you can at 8:00 in the morning get the name of number 29 and it can have a little flag on it.
That is a powerful idea for what we are talking about in my view. This connects back to the exchange we had with Justine about where is the aggregator? In my mind, that sort of really changes what we are talking about around the aggregator. The aggregator is a DARTNet thing. There is no data warehouse. Are you with me on this?
DR. CLANCY: There is no permanent data warehouse.
DR. GREEN: That is right. It is a virtual data warehouse that is constantly – you mentioned the word prospective registry and that is one of the things I wish you would say more about what you are thinking about prospective registries because in a way this is like an ever evolving prospective registry that can be customized.
So if you could just say more about prospective registry and could we go back to this attribution thing again? I was not here for it and I hear you saying that the discussion with the American Board of Medical Specialties, that MOC stuff, what the boards were doing was useful. The boards, all of them are struggling with the attribution issue. What do you mean by attribution?
DR. CLANCY: Okay, so first of all your comments on DARTNet I do not think were dangerous but actually illuminating so thank you for that. I should point out that Joachim Roski is here and he and Mark and others have been working very hard on a set of distributive approaches to assessing performance and so forth. They have actually come up with a strategy that this could be dangerous and I will see if I can say this correctly, where you can get the information that you need but the personally identifiable health information does not leave the entity at any time. I think that is very valuable.
I do not know if aggregator is the right thing or what but even with DARTNet you need an entity which is facilitating all of these queries and can get you the information that you need and so forth. That is the genius of it. I understand that everyone who prepares the presentations in the two groups gets way more excited about DARTNet and so forth.
I do think that in the end there is probably something about being able to merge the idea here of a distributive data network and prospective registries. If you ever want to have fun you can Google the word registries. It is pretty interesting. You get wedding gifts, sex offenders, a few other things but it makes you realize that we kind of take this terminology for granted.
I would say in our current phase, in anticipating better electronic and smarter, virtual strategy downstream, it is as much about getting a commitment of clinicians and patients to say, we could do a better job here and we need to be able to do so. I do not think that it has to forever be linked to a central repository anywhere although, I think that is how SGS and others do their work. The boards are struggling with the same issue. The attribution for me is which aspect of performance are we trying to capture? Some of this is about differences among stakeholders in terms of what they want.
When open season commences I get calls about what doctor should I have? Now, the real answer to that question is you know, walking people through contingencies and so on and so forth for everything from where you live to do you have a family, et cetera. It is a fairly complex question but boy, they want that individual.
I have never seen an issue of the Washingtonian or other magazine that says, the area’s best doctors that do not actually do well on this stance and so forth. Even though we know that measuring the contribution of an individual clinician to the care of a patient, especially the patients where you want some really good information about how we are doing is not so caught up with and complex in terms of the interdependence among the members of a care team that it gets very messy. So that means we have to get into very funny rules about under the control of a clinician or health care system or practice. Well that feels fair on one level. On the other hand, boy, does it limit our imagination. What you end up seeing is if you were to peruse NCQA’s HEDIS measures even organizations that are taking care of insured patients who have electronic records for 30 years, decision support, the whole nine yards, 60 percent on intermediate outcomes of chronic illnesses, not rare stuff, diabetes, cardiac risk factors, 60 percent is a high water mark. Seventy percent would probably get you into Ripley’s. We just are not doing very well.
Now, we know why that is, right? We cannot make patients do things. This is all about how they live with it. What we ought to be challenging ourselves is this is a community challenge, right? Then how do we figure out how we can use some of these tools to work more effectively with community organizations, whether that is the health department, whether that is the church, whether that is the Verizon store for that matter, I mean wherever it is that people go. I have finally figured out that the one common denominator for the population is probably motor vehicles and Verizon or other phone stores. You might want to fill in the blanks for what is going to work in your particular community. Does that help?
Well let me say it in a different way. You know what I would like not to fund anymore? Studies trying to isolate how much is surgical skill and how much is attributable to the team at a hospital. I want it all to be graded. I just do not want people to be padding their CVs with more papers that address that specific issue. It has all got to work.
Now for purposes of improvement you kind of do want to know. But for reporting I do not think so.
DR. CARR: Michael –
DR. FITZMAURICE: Yesterday, we heard from a lot of different people with a lot of different projects. It was very well put together by Matt, Paul, Justine, and the rest of the staff. We heard a lot of good things. I mean it is hard to say, well that is not so good, this is better but a lot of good things but it was hard to piece them and fit them together. When we look for leadership is it medical leadership? Is it someone representing the consumers who say, this is what we want in terms of quality? Is it the states and the federal government? We are looking for someone to put it together or to make the recommendations to have all of this put together. So do we have the right kinds of partnerships so far to move quality ahead? We have all different kinds of partnerships or does it take time to play out as we get more findings and we find out what works things will coalesce. What can NCVHS do to be the catalyst to help this move faster?
DR. CLANCY: Again, I am going to come back to my pragmatic response a couple of minutes ago and say, I would actually look at what is moving in terms of shaping the landscape of opportunities and that is going to be health reform legislation. I think that the multiple stakeholder input is incredibly important. Part of the reason that I think that is in multiple meetings mostly about safety, but about other aspects of quality as well, the game changer is actually an articulate consumer sitting at the table who says, I know it is hard but like, I am sorry why should I be permanently damaged from this infection or whatever? Put to people well, it changes the conversation from gosh, this is so hard and maybe we will go from 60 percent to 63 percent this year that is our goal to yes, we can. That, I think you want to capitalize on that.
DR. MIDDLETON: Good morning, Carolyn. I apologize I came in late. Blackford Middleton from Brigham and Woman’s Hospital, Partners Health Care, Member of the Subcommittee, Member of the Full Committee and no conflicts.
Carolyn, first of all it is great to be with you again and thank you for the comments, it was spot on. You will be happy to know that AHRQ funded research at Partners Health Care found a tool that actually did seem to delight doctors in use. This Smart Forms idea, several of us have been working on it for a long time, tries to combine in the course of the clinical workflow all that you need for kind of quality review, data review, documentation and decision support. There are issues still with usability and some of the technical underpinnings. I think there is a way to actually make the management of health care information much more delightful and thereby to delight the doctor and the patient.
That kind of leads into the second idea, which I think we need more work on that, but the second idea, how do we conceptualize quality to ensure this new world order so it is what I do for each and every patient that I see and for each and every population that I am responsible for. I think that we have work to do there to bring the quality management idea into the routine clinical processes of care. Smart Forms may be one method of many.
The other ideas might include sort of something that came up yesterday, how do we engage the patient further? What are the social networks that might apply to the patient, to the provider? Certainly, if I am at peer group review and if I have a quick question how do I manage that from kind of the social networking point of view and from the participatory medicine point of view. How do we engage the patient, not only to activate the patient but as we have seen to see how the patient may further activate the provider in useful and interesting ways?
I guess the question on the table I will ask you is you have already pointed toward the interdigitation of this analysis with health care reform. What are the couple of breakthrough ideas that you see that will take these efforts on the way that you have been leading for years in HIT and quality management and patient safety and hooked them to attributes in health care reform that make them sustainable. What are the breakthroughs that we need?
DR. CLANCY: Well, that is big and profound. First of all let me say, I am thrilled to hear about the Smart Form. I do not know that I would say the legislation itself contains breakthrough ideas. In fact, I do not think legislation ought to contain breakthrough ideas personally. I think it ought to provide the opportunities and the space to create that. So between the Resources and Recovery Act, which is very sketchy in terms of directives and the Health Reform Legislation I think there is a use base in a very clear and imperative - to move forward. I do not know what I think is the magic bullet. I do think particularly for chronic illness that consumer engagement is pretty critical.
I think that we have got to get smarter about how to do it. The Secretary made a comment the other day that I totally loved. She said, you know, isn’t this generational because after all, my father will never every questions. Rumors are kind of in a different place and my kids think of them as a legitimate source of a second opinion. It is not a one size fits all kind of strategy.
Injecting the notion and making it part of the fabric of care that you are routinely checking to see how did I do, I think would be very powerful. How to do that is less clear to me. I love the idea of social networking too so I was thrilled to hear that Matt brought it up. I think I am really too old to know what it means. I think my nieces and nephews do it. I am on Facebook but I am about as boring as it gets. For them this is a different mode of interacting. I have seen it at your place when you showed me how the providers working on guidelines and some other activities interact asynchronously but again you are solving a problem right? You know, to have a meeting and to bring in all of these people and convene them together and all of that just is not going to work. I am sure they have to meet sometimes but absent that it really fits into their lives. Some part of this has got to be getting information and stuff that consumers need and want to them when they want it. Not when they figure out how to find us but when it is convenient for them.
DR. TANG: I want to pick on one final pearl that I heard in your presentation and see how we can mine that. You talked about using the signs to customize the treatment for an individual, how can we measure that activity or that success?
DR. CLANCY: Oh boy that is a huge challenge for us going forward. The freeway in my brain is very much about comparative effectiveness because both the process is informing the Secretary’s allocation of resources for both the Institute of Medicine and the Federal Council. Both groups independently working expanded the definition to include something like care delivery interventions. We do not even have good vocabulary much less definitions. Now if you are prescribed a pill for your cholesterol we know what that is because we happen to know if you are taking it but we actually know what the content is. For disease management, care management, you name it we do not even literally speak the same language across discipline and health care sectors which does not mean that we cannot get there. I think it is going to be very exciting. We will be making some investments over the next couple of years. I am hoping that we can learn something about that.
DR. CARR: Carolyn, thank you so much for your time and also for your dialogue over these questions. It is very helpful to us. Thank you.
(BREAK)
Agenda Item: Meaningful Measures of Disparities
DR. CARR: Okay, Ernie we are looking forward to your testimony today so thank you.
MR. MOY: Okay and I will try to be fast. So first to context, I work on the National Health Care Quality Report and Disparities Report and so we have a very specific kind of focus on disparities. We take regular old quality measures of effectiveness, safety, et cetera and look at it by subgroup so that is the perspective that I am going to take. There are other ways to look at it but this is what I know so that is what I am going to show.
Also, when I first started to do this I asked meaningfulness, do you mean meaningfulness like ONC? They said, yes so I took that literally and started with ONCs perspective that meaningful use of data begins with capture but also must ultimately improve clinical processes and improve outcomes. Applying the disparities data, first of all realization, to me meaningful use is really putting it in the context of quality improvement so not all of the other ways we might want to look at data or disparities but for specifically honing in on what is relative for quality improvement. Looking at disparities from that perspective, the data sharing then obviously becomes data sharing now by subgroups, different populations, and in particular populations that are experiencing disparities in health care and they are amenable to quality improvement, so specific kinds of disparities but perhaps not all disparities.
Ultimately, this must yield then improvements in clinical processes and what does that mean? Disparities we know that there is a gap in the clinical processes between different groups and if we are then going to reduce that gap we must actually accelerate the pace for improvement among disadvantaged to a rate that is greater than the rate of improvement among the advantaged group in order to narrow that gap. That ultimately will be the acid test for improving processes of care, to narrow the gap we must make the rate of change among the disadvantaged faster than the advantaged group and ultimately to yield improved outcomes similarly to reduce that gap you have to accelerate great improvements among the disadvantaged group to a rate that is faster among the advanced group in order to narrow that gap. Those are the ultimately then the ways of assessing whether or not we have achieved meaningful use of disparities data using an ONC kind of model.
Before I move further, I want to ask the question do you actually need disparities and data to improve quality. Is it even meaningful or necessary to look of the issue of disparities and my answer is in an ideal world I think you do not because in an ideal world you know there are no disparities when 100 percent of people are getting 100 percent of the care that they need. In that context you do not need to know really about disparities but we do not live in the ideal world, we live in a non-ideal world. In our non-ideal world, I think disparities in quality are related, but they are not the same things so therefore, I believe it is meaningful to look at disparities and this is just one illustration of it looking at geographic distribution in this particular case on the left. Quality of care is one particular matrix that is very commonly used, diabetics receiving hemoglobin A1c. States caught up into quartiles from BRFSS, on the right you see a difference instead, a disparities issue in this particular case, an income-led disparities issue. The main point is it is not the same states that are doing really good or really bad in these particular matrixes. Quality does not equal disparities when you are looking at variation across states. They are distinct issues and in an imperfect world I think it is meaningful to look at disparities of care to improve quality of care. One way that we can use them is to use them together to target intervention.
I think that we are familiar with the quality chasm, the difference between actual care and the high quality care we aspire towards. The problems that intervene in effective care, unsafe care, et cetera. There is also acknowledge of disparities gap, the difference between care received by the advantaged and the disadvantaged, we see some of the barriers that exist there. Ultimately, when you put them together maybe you get a really big gap which might be then a good target for intervention. This is one of the ways that you can use disparities data I think in a meaningful way to target interventions, to improve quality of care efficiently.
One of the questions is how are we doing? First of all this is information from one of our disparities reports a couple of years ago looking at data capture related to different disparities populations. These are your OMB groups race, ethnicity categories as well as looking at the poor. You see that these are the areas where we do not have good data so you see from that very earliest meaningfulness assessment of data capture we are not doing particularly good from many of the OMB groups, so not so good.
How are we doing? If we are looking at the more stringent criteria of actually reducing the gaps and processes and outcomes and again, a report a couple of years ago, although not a whole lot has changed. You see that when you are actually looking at the size of disparities and sorting them by those that are getting better in the yellow and those that are getting better about the same or getting worse – you see most stuff is not getting better. From the more stringent criteria most of our processes and outcomes are not narrowing based upon our observation of measurement activities related to disparities. I think overall, how are we doing? Not so good.
How can we make disparities data more meaningful? That to me means how can we make it so that they can actually be used for quality improvement? I think there are a couple of different areas where they can be used to guide quality improvement activities. First is targeting. I think I alluded to that already. I think implicit in that is the use of disparities data is primarily making the process of quality improvement more efficient. So if you can identify specific process defects in specific geographic area, effecting specific subgroups you can now target intervention for those folks, for everybody to try to improve some – for me the benefit of disparities data for targeting is actually an efficiency problem.
They can also be used to guide intervention once we have identified these particular people that you want impact. I think disparities data can improve effectiveness because I think most of what we do relates information and not everybody gets information in the same way. If you know a specific group and you know what kind of media they use, maybe knowing what kind of language is also important, maybe knowing about some of the cultural time bombs that might exist there might also be important. This might then prove the effectiveness of specific kinds of interventions.
Lastly, again, tracking progress is important because if we say that meaningful – using disparities data means making sure that it is really having an effect on progress outcomes you need to track it. The disparities data, because you only need to capture it for this particular subgroup, can improve the efficiency of that data capture.
What geographic areas? I alluded to some of the variations across states. This is now a network to kind of quantify the differences of disparities across states. This is just one measure, colorectal cancer screening, the differences between Hispanics, Non-Hispanic Whites. You see that there is a big variation in that absolute gap across the states. You see the all state average in the middle. Just by way of comparison, how big is this? This is the state gaps. This is the difference between the best state and the worst state. You see a lot of disparities in this case were actually bigger than the best state and the worst state. They kind of put that into perspective, the magnitude of these kinds of disparities.
How do you use this from the meaningfulness perspective? We you might want to work on some of the states on that right-hand side that have really good gaps. You might not have to then invest in working on it in those low-gap states.
When we start looking at state variations the next thing that people ask you to do is look at variations across cities. You look at variation across cities and there is variation across cities. Then you look at variations within a city and there are variations within cities, overall, I think one of the conclusions that we have come to in terms of trying to help people trying to make disparities data meaningful is that the small unit that you can get to, the more valuable they find it. I think that is one of the issues there. Disparities data on one hand is more available at the higher levels but then it is less actionable. Going down, it is more actionable but then it is really harder to get to.
Very quickly another issue, what subgroups? I think that we stick to OMB usually but when we start to parse out to different Hispanic subgroups in this particular case by ethnicity, you see that there is variation. When you parse it out by Asian groups you see that there is variation. The main point is the way that we normally look at disparities from an OMB perspective is probably suboptimal. There is a lot of variation across the granular ethnicities. In fact, as a consequence, the IOM in their recent report recommended collecting information about OMB granular ethnicity that goes beyond OMB but of course using the CDC categorization there is a whole lot of different kinds of groups which obviously creates a challenge. One of the issues is which ethnicity to focus on.
I very briefly alluded to language as also being important. You can see that there is a lot of variation related to language proficiency, English proficiency in this particular case, regardless of racial or ethnic group. Again, OMB recommends collecting detailed language information but this is just which I find very interesting. It is a number of languages in each of the different states. You can see that all of these numbers are really, really high.
I think that it is appropriate and it is actually beneficial to define meaningfulness of measures in terms of quality improvement. I think it is very applicable to the issue of disparities.
How are we doing? So far the disparities measurement has been spotty. Some optimal data collection has not really let to any improvement in processes and outcomes to a significant degree. I think that you do see some examples where there is some improvements but in general, it has not been very successful.
I think disparities data to be meaningful, should help to guide targeting, development interventions, tracking interventions, and it should focus on specific subgroups within specific geographic units. I think that gives a best efficiency perspective. On the large number of granular ethnicities and languages in the US is a challenge.
Carolyn did say that I could give you my personal recommendations that reflects only my thought and has nothing to do whatsoever with AHRQ. She actually has not seen these.
I think that it is important to support collection of disparities data consistent with the OMB recommendations. We need to start collecting OMB race and ethnicity and I think beginning to collect information on English proficiency is kind of important to cover that language perspective.
I think the granular ethnicity detailed language is really hard and so the first step, what I would recommend doing is identifying those that are meaningful for national tracking. This is, I think we had a disclosure, this is an area where obviously I do have a vested interest because it would help my reports a whole lot if we could identify those ethnicities and languages that are most meaningful for national tracking.
I think in that process we would probably develop methods that we could then give to states and other private organizations to help them define what ethnicities and what languages are most relevant to their local circumstances.
I think that as we think about quality improvement you need certain amount of data. We need to collect enough data to support quality improvement for every geographic unit that we are talking about.
I think that we ought to promote disparities measurement and the disparities reduction approach. That is one way of improving quality. A lot of times people say, well, you can just reduce disparities by improving quality. A rising tide will sail boats. It typically does it just typically lifts them in parallel and why not put the constant with disparity.
I think that disparities reduction by targeting specific subgroups in particular geographic areas may be a more efficient way of actually improving quality and at least folks should think about that.
Lastly, I think we need to assess our disparities data measurement activities to see if they actually improve quality improvement, to see if they are actually changing processes. If they are not, we consider whether we are measuring the right thing and whether or not that activity is worthwhile.
DR. CARR: That was great. Can I ask you a quick question? The groups that you identified as having a disparity are based on – my question really is do you also look at income? In Massachusetts, we discovered that with their health care insurance that we have a group of people who are poor but they have insurance and they cannot afford the co-pay. It is sort of an allocation of resources but it is sort of a new group that we have not looked at. They kind of do not necessarily fall into the traditional groups here, any thoughts about that?
MR. MOY: Yes, so our mandate is to look at disparities related to race, ethnicity, and social economic status so income is inherently one of the disparities that we look at. It is very large. I mean there is a huge amount of disparities related to income even when you stratify by insurance for the reasons which you stated.
In terms of this meaningfulness discussion I think one of the things is it does not, it is not really necessarily important how you define these particular groups that are experiencing difficulties. They may very well be defined by the intersection of race, ethnicity, income, and other kinds of characteristics. The important thing is that they are identifiable and that they can be targeted efficiently and that they are experiencing disparities.
MS. TAYLOR-CLARK: Just to add to that a little bit, one of the reasons there is a focus on race, ethnicity is of course after you control for, and often times after you control for socioeconomic position is what I would call it, there are still disparities that exist among race and ethnicity. That is part of why we actually have a focus also on race, ethnicity outside of socioeconomic position.
I want to thank you for inviting me here today. I also want to thank Matt Quinn for inviting me and thinking of me. He saw at the ARHQ annual meeting that we are very excited about the stuff that we are doing. I am going to be speaking from my own perspective today, not from the perspective of my institution, although I will give a shameless plug for the work that we are doing at Brookings.
So today the roadmap is really to think, I have been asked and charged to do three things. The first thing is to talk about current measures of equity. The second is to provide some opportunities and challenges of current measurement strategy. Finally, to have some insight I hope, on what makes disparities measurement meaningful. In that inherently I am going to provide some recommendations. I am not going to provide specific recommendations as Ernie outlined.
Just to bring us back to the beginning, the IOM has outlined six domains of quality. One of which is equity. What we know is that there are measures for safety. There are measures for effectiveness. There are emerging measures for patient-centeredness, timeliness, and efficiency. What we also know is that there are virtually no measures for equity in care. Currently what we do when we are trying to measure equity in care is to stratify clinical effectiveness measures. When I say that, what we are doing is we are collecting measures of race, ethnicity, socioeconomic position, and others. As Ernie suggested, what we then do is we take these measures of effectiveness, potentially even patient-centeredness and timeliness and we then stratify them to develop some understanding of what the disparity looks like. Then we may be able to develop interventions to affect equity.
The question I then ask myself is what makes meaningful disparities measurement measures. I am going to argue three things to you or submit three things to you today that we could certainly talk more about.
The first is a problem that Ernie mentioned initially. That is we simply do not have a discipline. I am talking about standard race, ethnicity, and language but we can certainly talk about income or other socioeconomic conditions and other demographic information. We have no standard race, ethnicity, and language data across organizations. People, organizations, are collecting this information in a number of different ways, using a number of different categories. When I actually took this position I thought I would have a really easy job. They said, well, you know, all you have to figure out is first, how do we think about collecting the standard way race, ethnicity, and language. Then how do we get that into the system and then spit some data out so we can look at disparities. I thought this is going to be simple and as it turns out that is not the case. We have a number of different ways that data is collected and a number of different categories. I am going to talk a little bit about how the Institute of Medicine has dealt with that.
The second submission that I will make to you is that we need to have, and I have heard a lot about data aggregation this morning, but we have to have an ability and a capability to integrate data systems. That is to say that where we collect and require demographic data may be very different from where claims sit, clinical data sits, lab data sits, so ultimately, our inability to actually integrate those systems means that we have an inability to effectively look at measure of effectiveness stratified by race, ethnicity, or other demographic characteristics.
The third point I am going to argue today, is that ultimately, one of the reasons that we may not have measures of equity is because we simply do not have incentives to collect or report or to utilize those data. I am going to show you a couple of points that have been made by private organizations to start thinking about a crediting organization in order to align incentives for providers and health care organizations to actually acquire these data and develop some measures of equity.
So the first point I made was that there are no standard race, ethnicity data. The Institute of Medicine of August 29th of this year developed a really interesting and really important recommendation that said we absolutely need standard data. Now this is a very busy piece and let me see if I can break it down.
What we are going to do now is to think about the local reality versus the national reality. The local reality is exactly what Ernie points to and in fact what Carolyn pointed to. It is to say that it is very nice that we have these large OMB categories of race including Asian groups, and Black groups, and White groups. Ultimately, at your local level we cannot act efficiently on that information. I cannot say that if I am looking at someone who was “Asian” whether their status as Cambodian or Vietnamese or Japanese is actually more important to me at the local level. What I am trying to develop is an intervention both in terms of language, in terms of culture, in terms of other points that are really important to the historical data that you live in now.
The issue here is that we have a local reality versus a national reality. What IOM has suggested is look, it does not matter at the local level what data you want to collect, it matters that we have some standard way to roll those data up into these standard OMB categories. So that is in fact what they have endorsed. They said, what we can do is collect this information but we need some sort of map. We need some sort of map that will allow us to say you know, in my local population we have a large number of Vietnamese folks, we have a large number of Japanese folks and ultimately at the national level what we are trying to do is track Asians. How do we actually roll those categories up in a standard way among all health care organizations so that we can actually look at these data appropriately?
In fact, that is the first argument that I make to you is that we absolutely need to have that map in order for health care organizations to follow it so that we are actually comparing apples to apples and oranges to oranges when the data is done.
The second point that I am going to make is that we need an integrated data system. Ultimately, you see here that there is a number of places where we get data. For AHRQ’s purposes and the National Health Disparities Report we are getting data from surveys of population, health care facilities, data extracts from health care organizations, and ultimately surveillance and vital statistics information.
At Brookings we are very specific in one area which is the health care organization. I show you this very busy, but this is my favorite slide, a very busy slide to say that we are getting this information mostly from the patient. The patient gives a number of organizations, a number of entities their information about a number of things. It is about their satisfaction of their care, about their race and ethnicity, and other demographic data. Again, those data systems and what you see and hear in terms of data exchange and transfer, those data systems do not speak to each other well enough so that we can pull the clinical or the claims or other administrative data and have them speak to demographic data.
In terms of disparities, one of the things that we have actually noticed is that there might be other data sources. One of the things that we are doing at Brookings is actually working with employers as a potential data source. I am not asked to speak about what are the current data sources but what might be some new data sources. This is just one example that we are using. That is that employers right now are acquiring these ethnicity data for the purposes of equal opportunity. As we know they actually have to acquire those ethnicity data. The question is how do we figure out, putting an identifiable flag on those data so that we can then integrate a system in terms of health care that would allow us to stratify some of the measures, some of the effectiveness, patient safety, patient-centered measures by race, ethnicity so we could actually look at disparity. The major difficulty that the health care system and these other organizations have is actually getting the data. It is actually acquiring the data from the patient and particularly race, ethnicity, and language is a major challenge.
I wanted to talk a little bit about this aligning of incentives. I show this again, very busy slide here to say that there are organizations, private entities and I hope that HHS takes it up as well in terms of public entities. In thinking about aligning incentives to not only collect, not only report but also utilize and efficient and effective way as Ernie described, these data. So what you will see is actually three organizations that I am going to describe The Joint Commission, NQF, and NCQA are all – well the Joint Commission and NCQA are trying to develop measures of equity so that their organizations both hospitals and health plans are actually accredited based on some of these standards. What we know about National Quality Forum is at this point they have endorsed 45 practices to guide culturally appropriate and patient-centered care.
My argument to you today is that the best measure of equity that we can get at this point, given that we actually have their measure of equity, are to think about developing strong, structured, efficient patient-centered measures that can be then stratified by race, ethnicity. That would be an argument that I would love to hear arguments back to me on because I kind of toil with this idea well, what would an equity measure really look like if we had our own equity measure? At this point, my argument to you or my submission to you is that we really need to think about patient-centered measures that would actually lead to outcomes. That is one of the big pieces that we need to think about, effective outcomes in terms of measurement.
NCQA, just to make this last point, is now developing new HEDIS measures that will be based on the OMH CLAS standards which are culturally, linguistically appropriate standards which includes data collection as well as the use of these data.
I am going to actually end here by giving the shameless plug that I promised to give which was that the racial and ethnic equity initiative, and Dr. Roski is going to speak about, my colleague here is going to speak about the high-value health care project at Brookings. This is something that we are actually undertaking right now and we are really trying to look at organizations and entities that are doing this work that will culminate in March of next year in hopes that we can put forward for example, the recommendations that your committee will make today.
I thank you for this opportunity and would welcome any questions.
DR. CARR: Excellent, thank you so much. I would like to open it up now for questions.
DR. TANG: Thanks very much to both of you. I had the opportunity to hear Kalahn at Brookings maybe twice because I am on a number of Brookings Committees too.
One question I have is, as you will note we put it in the 2011 Meaningful Use Measure, at least the capturing the data, and we are also tracking I think the CDC version of that. I asked the IOM Committee to submit their comments when it goes back to them for public comment because that came after the draft. What ideas do you have about making these – so part of meaningful is actionable. So what ideas do you have on how we can act on it one patient at a time? I do not just offer up an example so it is not an example of what we are trying to do. We have a wellness program and even wellness is not one size fits all. One of the great examples, a physician in our group did, there is a sizable population in the San Francisco Bay area of South Asians. They have a higher risk of early cardiovascular disease. It would be inappropriate to suggest that they change from their high carbohydrate South Asian diet to an American diet of high fiber. What we have is instead customized both a test and a video that talks about the conversion in South Asian terms. It seems like that is the kind of “customization” that Carolyn talked about that we have to do for each and every encounter. Different cultures have different attitudes about medications or shots or diet or exercise, all of those things and we almost have to do this – that would be the most effective effort at least that is my simplistic way of looking at it.
Other ideas that you have in terms of how to make this data now that you are helping us get the data, then we have to make it in front of ourselves so that we can make it actionable. How do we study the effectiveness?
MS. TAYLOR-CLARK: Dr. Joe Reed at Harvard Medical School has actually developed, and others, has developed programs for medical education. I think that would really be the place to target some of the findings that we have to say look, there are these differences in the cultures. There are these differences in trust of the health care system that we know absolutely exist among racial and ethnic subgroups. What we are really absolutely need to do in the medical education point which I do not know is the charge of the committee but it is to make those data available to students in medicine so that they can actually develop culturally appropriate services, which is a term that I do not absolutely love but I will use it for the sake of this point, so that they can develop culturally appropriate services and interventions but really knowing what their patients are, catering to their patient. That is why these patient-centered measures might very well be so important because they are actionable.
MR. MOY: I think that you hit on just right on how disparities can be used for that customization because it is inefficient to work with each individual patient to refine their precise diet whereas if you can cluster the different population subgroups then you can actually develop products that target that particular subgroup. I think the important thing is maybe having some kind of inventory systems that these things can be shared across institutional and geographic settings where others in other parts of the country or in other institutions in Boston might be able to take advantage of the same kinds of tools.
DR. SCANLON: I have a question about how we get the disparity data that we want. It seems partly about data flows. This committee actually has a recommendation from about three years ago or so, we did a report on race and ethnicity and recommended that there be an effort to collect the sort of granular data that you talked about but not at the provider level. That is where IOM seems to be saying that at the provider level we should be able to have this kind of information. I think our logic was that collecting it once, right, given the complexity of it is better than having everybody collect it, submit it, and then have someone have to deal with the discrepancies that sort of exist among them.
I guess my question is is IOM going that far in saying that once they collect it is should also be transmitted which then I think we have this issue of the discrepancies. Then there is also a question of is it really useful at the provider level to have the granularity given that what you have talked about in terms of the complexity of it and potentially that some higher level aggregation is very important at the provider level but we do not need to confuse things in the process.
MS. TAYLOR-CLARK: The IOM actually has made very clear that they think that there is going to be better data submission in transfer protocols between health care organizations so that is first. They also think that redundancy in the system does not work. In Massachusetts right now we provide technical assistance to the state to figure out how can we actually get from the hospitals, and just to speak to the hospital point, acute care hospitals are required at this point to acquire the information. They are doing a very good job of it. Almost 98 percent in Massachusetts have been correct. The question is how do we develop these data transfer protocols that would allow health plans to acquire the data so that they do not have to reinvent the wheel. They are also creating an all payer system which will be very helpful because that demographic data will flow through it.
Your point to the provider level is a very good one and one that I think even Carolyn made which is that the sample sizes would be too small for providers to do anything with those data. Ultimately and unfortunately, from the consumer perspective and we have done a lot of work with consumers, we know that they are more comfortable with their providers and or hospitals collecting and acquiring this kind of information. They can see clearly why you would collect their race, ethnicity in terms of quality of care. What they do not really get is why your health plan is acquiring this information. The entity matters in terms of consumers.
MR. MOY: I also think that sharing is very important but I think that your point as to collecting information that is actually meaningful to the person who is going to be primarily using it is also very important. I think at this point at least, I would not say we are at a point where they are collecting tons of data and just not know how to collect it. I would encourage the providers as a start to collect information on the groups that are particularly meaningful to their practice. Then later on down the road once they have gotten these back they may think about collecting more detailed data that might not be meaningful to them as a practice but might be meaningful for a geographic unit for aggregation. As a start, I would start with what is most important to them that they can actually use in quality improvement.
DR. FITZMAURICE: I think it would be nice to have, more than nice to have a study on population where you look at the disease incidents by a race, ethnicity category. Then for the same population you look at treatment services for that particular disease by race, ethnicity category. Then you look at the outcomes information by race and ethnicity category so that you get an overview of here is what we have. Here is what we are doing. Here is the result of what we are doing. Then to follow up at a more individual level, maybe to form a registry of certain disparate groups, with their permission of course, to follow them over time so that we have the same kind of information, actionable information to do something with as opposed to separate studies in different part of the country for different areas where you do not make them together and you are further away from cause and effect. Although, we think we have some good evidence for cause and effect.
Are there areas where that is being done or is that a good model that is also difficult and extensive to do we are not doing it?
MR. MOY: I think we try to do it in the reports, and I will say this is not just specific to disparities, it is in measurement in general that typically processes are collected in one place and outcomes are collected in a different place, where health is collected in one place and health care is collected in a different place. Then it is potentially somewhat less meaningful because you do not know exactly where the lesion is. In the report we try to do that. We try to link process measures with outcomes measures at least so that you can look at the two in tandem, if they are going in the same direction you might have a little better confidence in the processes are in fact effecting the outcomes.
I think it is a very valuable thing to do but whether or not that is universally achievable is probably more difficult. They typically are collected in different areas and different data collectors.
DR. GREEN: Ernie you had a slide where you color coded it on the right-hand side. What the figure was showing was better, the same, or worse. What can you teach us about the nature of the data that were necessary to get to that slide?
MR. MOY: You mean just taking the measure and cutting up the states into better, same, and worse? It is fairly straightforward.
MR. GREEN: What are key attributes of the data and the data collection process that allows you to summate that to the point that where you could say, at this point in time things are getting better, they are not changing, they are getting worse. Now that is the sort of matrix in my view that, to follow Carolyn’s advice and we looked at the Health Care Reform Bill and I think what we are going to want to know is are things getting better, are they staying the same, or are they getting worse? What were the attributes of the data that let you put a slide up there like that?
MR. MOY: You need to have the same measure that is being trapped over time the same way using you know the same kind of sampling frame but besides that –
PARTICIPANT: off mike.
MR. MOY: The same population, let’s put it that way that you are sampling from are not the same people or the same units necessarily. In general, I would say that is not that hard to achieve. We have many databases that are continuous in nature and that we can track stuff over time. This continuity has of course hurt us so when it does not get funded for a year that hurts us. Most of the things are actually achievable. It is not impossible to do, let’s put it that way.
DR. GREEN: I certainly take your point that you need to not allow the variations and the answer there is is it getting better or worse be based on the fact that you have totally change your data collection mechanism. I understand that part but as we are trying to think about meaningful measures that can be derived, I just wondered if you knew something else about what it took to build up with what we have got to get to where we want to be quickly, rapidly as opposed to deciding that it is going to take us eight years to decide what the construct of race is and what we are going to represent it as and how we are going to validate that. Is it going to be distinct from geography or not? Is it economic or is that really – you know, you can get the tone – I may be the Lone Ranger but I think that this Committee is beginning to consolidate again around pragmatic ways for now. That is the nature –
DR. CARR: So Larry was complementing you. Is that fair to say? Larry gave you a compliment that this is very pragmatic information.
DR. GREEN: From Carolyn’s point of view, practicing medicine tomorrow, you know you want to be really nice – I would like to know if my patients are getting better, staying the same, or getting worse. I do not need 37 graphs coming back for 16 of these and 9 of those and 2 of the others, that –
DR. CARR: Blackford will have the final question and we are very grateful for this opportunity to talk with you.
DR. MIDDLETON: Thank you for presenting. It was really great to meet you both and hear from you both. I guess the question crossing my mind is in a way, culturally appropriate services as a reflection disparity is sort of a one dimension of an analysis from many that might look at what is the right combination of therapy or intervention for the patient at hand? Other dimensions might include of course, what is the genetic makeup? Is the hypertension therapy appropriate given a sequence analysis? What are the payer appropriate services if you will which is the hardest one untenable of course on face value but will this service be covered for this patient before me.
You have described a number of ways to assess culturally appropriate services, I guess my question is in any of the work, it is not in my literature at all, when you think about the disparities or the assessments of culturally appropriate services, is there a way to take into account these other dimensions or even one more patient’s preferences? Despite any cultural orientation of course, patient preferences may dictate and sway decisions one way or another. It seems like that is already being considered.
MS. TAYLOR-CLARK: That is in fact what – the submission that I gave to you about equity and trying to develop measures of equity actually centered around this idea of patient-centeredness which may in fact center around some preferences. So that is, can we develop measures that are not necessarily being stratified per se, but that get to equitable care? The only measure that I can think of where we are not stratifying is to say that the patient came in and they requested translation services and that becomes the denominator, all of the patients that request translations services, why? That means that they are limited English proficiency so they are now the denominator.
In the numerator, we have a combination. We have a combination of the patients who received the services and potentially were satisfied with that service. Some combination in that numerator and now we have a measure of equity that is not being stratified but that actually allows us to look at those things. I think that patient preference comes into this idea of patient-centeredness if we can develop a measure that would look at preferences that could be objective. That is the difficulty with these patient-centered measures of course because what we know about different subgroups is that there are some groups that are more trusting, some groups that have absolutely different preferences based on their experience and their historical experience in a health care system. It gets a little bit tricky to develop that measure.
That is why we are here. What we have got to figure out is how can we actually develop a measure based on preferences that will allow providers and others to make effective, actionable choices when they are developing interventions.
MR. MOY: This is one of the headaches we dealt with because the disparities purists want to exclude patient preference from the equation and so when iowa(?) did it on equal treatment disparities exclude you know, the people that did not want the particular service. From a data perspective of course, it is almost impossible to operationalize give what we currently have. We do not know anything about patient preferences. We kind of ignore it in our reports because it is the best that we can do.
However, I do note that people are increasingly are talking about maybe tracking information about patient refusals so that when we are getting the information about the different kind of screenings to report because the patient refused it. That might actually be a kind of measurement that would be used in tandem to incorporate the patient preference.
DR. MIDDLETON: Just to follow up briefly, I think that is a very interesting way to look at it if you go from the compliment or the inverse side being refused is an expression of preferences at some level. I guess where I get concerned, and this is may be a pure Brookings sort of thing, from a value perspective, values underline patient preferences at some level and values may vary dramatically and be expressed through the preferences if you will. So even within a single cohort culturally homogeneous – the values may be all over the map.
MS. TAYLOR-CLARK: I will say that, and you may or may not back me on this, and I do not dismiss this point of preferences but what we find in terms of disparities and outcomes is that preferences are not driving many of these disparities and outcomes and I will put that on the table. When they have done smaller cohort studies they have found that preferences are not in fact driving these disparities.
MR. MOY: I think one of the important concepts is making sure people are expressing their preferences after they have received all of the information so they are making an informed choice as opposed to you know an uninformed choice.
Agenda Item: Meaningful measures of value (including efficiency)
DR. CARR: Thank you very much for a wonderful presentation. We are going to transition into our next group which is meaningful measures of value including efficiency. Joachim Roski from Brookings, Managing Director of Health, Value Health Care Project at the Engelberg Center for Health Reform will be our next speaker.
MR. ROSKI: Good morning, thank you very much for inviting both Kalahn and myself to talk about some of the work that we have been doing.
What I am hoping to do this morning is you know trusting that Mike will provide some more detail to comments, particularly on what CMS might be doing, talk a little bit about just basic nomenclature so that we are all talking about the same thing or at least use words in a consistent way. I found that to be one of the key stumbling blocks in some of these discussions. Then I will give a quick snapshot about how I see the environment in terms of measure development. What is being deployed now? What are the advantages and disadvantages? Then I want to talk a little bit about the infrastructure that is required in order to put such measures forward in picking up on some points that Larry has made earlier and that we heard Carolyn talk about, talk some more about the distributive network opportunity and how that may be a pragmatic and sophisticated way as a matter of fact to move forward in doing measures of value and efficiency as well as measures of quality.
In terms of definitions, there are certainly lots of them out there. AHRQ has commissioned a report that was published not long ago that goes into a lot of detail about issues of efficiency. I am not claiming to be comprehensive in my comments; all I am trying to do is sort of quickly set the stage for what some terminology might be.
As you might imagine, the concepts of cost of care, efficiency of care, and value of care are not synonymous although, in some discussions they are being treated as if they were. I would like to call out how I see those differences.
These definitions are based on some work that the AQA, the Ambulatory Quality Alliance has done a while ago but I think it is very useful to quickly discern differences.
Cost of care really pertains to one part of a ratio if you will of where the ratio is made up of some definition of quality and some definition of cost. So cost is just one part of that and it measures total health care spending including resources use and unit prices.
Efficiency of care would pertain to a particular cost of care for a fixed and chosen degree of quality of care. You can take any of the IOM categories or any other definition that you may have but the important part is some stakeholder’s particular fixed view of what efficiency is. In today’s discussion when we talk about efficiency it’s typically the efficiency as the payer would see it or as the consumer might see it, actually it is more likely the payer would see it efficiency.
Value, and that goes to Blackford’s point is really cost at a rated preference of quality and that value of care may be different for different people in the room. Just as some of us may value a Mercedes more than we might value a Yugo even though both of these vehicles might get us from point A to point B but we have different, other issues that we are concerned about when we purchase cars. That is I would argue the same here.
If these are some of the definitions then the next question and I will actually be focused largely, initially here on cost of care and how we measure that. Then, when we think about cost of care they are actually different costs to different people in the health care system. By now it has probably become sort of commonplace to say somebody’s overuse is another person’s income.
It is important for us to be clear about what particular perspective we adopt in talking about cost. For one there is the cost to the consumer. Typically today, unless you do not have insurance and would aptly pay out of pocket for everything, all you would see is the out of pocket cost above and beyond what your insurance might cover. That may have little or nothing to do with what the real thoughts are that go into all of the prices for receiving particular services.
For plans and employers, what they would see is discounted charges so nobody pays as we all know the actual charges that are being put through, they are being subject to negotiations between a plan or an employer and the provider. That becomes then the cost, the unit cost multiplied by the utilization if you will.
In addition, from the plan and employer perspective, we have the issues of administrative costs on the plan administration side. I will not talk a whole lot more about that other than to say it would be great to know a whole lot more about the big problem from a pragmatic point of view as we do not have very clear accounting standards for how to put that actually into buckets and to know how for example, we should think about the cost that a health plan might spend on a disease management program and how to cut a deal with that. Of course, employers would be very concerned about issues of indirect cost and productivity above and beyond what might be the outlay for the direct cost.
Now from the providers this turns out to be a very different part of the equation because they have to be concerned about what costs am I going to lie out in order to render a particular service? How many staff do I need to hire? How many investments do I need to make in terms of sophisticated equipment and so forth until you have fixed and variable costs that you have to be concerned about? That is an important perspective.
From a societal point of view which is typically the perspective you will see reflected in academic articles on how to think about cost, it is typically not from a business perspective where some of these other perspectives – here issues of disease burden, quality adjusted, life years and others might be concurrencies in terms of how you might evaluate if something is or is not a valuable service. For example, from a societal perspective one of the cheapest interventions that we know of in health care is advising smokers to quit which is a frustrating thing to be engaged in at a physician level typically because you have very few people that actually take you up on it. It costs very little to deliver and there is a certain percentage of patients that still respond to it. On the other hand, mammograms for example turn out to be from the societal perspective a relatively expensive intervention in terms of how many years of life you might save across a population and so forth.
The next issue that I want to sort of drill in on is when we think about cost what becomes a unit of cost that we want to think about? Here I will particularly think about cost to the payers – in terms of the charges that come through on the health care side. Just to put some nomenclature on that, I can think of at least three ways you can think about a cost. One would be unit-based, basically just counting up how many images are being done by a particular physician per a population. That can be a general population or it can be a very specific population with a particular condition.
You could think about episode-based approaches which are much more complex but would be more in line with for example, a person-based approach to measurement where you rather than counting up individual services, try to string together a meaningful concept of what it means to have asthma or to have a heart attack and to string together all of the costs that would be incurred for treating a patient with that particular condition. That can be more or less complex based on the type of conditions that you are dealing with, the type of co morbidities that are associated with it and so forth.
If you engage in this sort of measurement unlike the former, you are much more likely to be working in the relative cost area. What that means is you are much more likely to take an approach where you measure this person is so much more expensive or percentage wise more expensive in treating a particular condition relative to some reference point which is typically the average that is chosen for any particular collective of providers for example, as opposed to dealing with absolute numbers. You would have to do some math to get back to what the absolute numbers would mean.
Episode of care measures as some of you who are familiar with the work that MedPAC for example has done, are not a panacea because they are also subject to if you will, challenges that have to do with the data sources that we rely on and what gets into the data system in the first place. Here essentially what you are saying is the more effective that we need to treat a particular condition, the relatively less costly you are to somebody else. We have all heard about these examples where you know you can be incredibly efficient treating patients who did not need the service in the first place. If you do not separate that out you are going to have a one-sided point of view.
One way to balance an episode-based cost of use point might be a per capita approach where not only would we measure how effective are you in treating a particular episode, it is also keeping an eye on how many episodes are you actually generating and how does that compare to somebody else that we are interested in.
In terms of measurement approaches, again on this side of the ledger in terms of cost to the payers of the health care system I can think of for example, three types of approaches. Some of them are more comprehensive and enhanced than others. In my book what I think are probably are methodologically the most advanced, I am not commenting on how useful they are, but methodologically, the most advanced are in my mind proprietary episode-based approaches. You may know them as episode treatment groups, ETGs, ERGs, as promulgated by the firm enGenic, or you may have heard of MEGs, episode groups promulgated by a firm formally known as MEDSTAT, now known as Thompson METSTAT. It is very similar in approach trying to define essentially the universe of diseases into particular types of episodes. That ranges from a universe of about 500 some episodes to some much larger number and some smaller number that is probably for this point of discussion not particularly important. They are in wide use today by health plans around the country. CMS is experimenting with some of these approaches and I am sure that Mike will talk about what they have been finding.
There are some other approaches – one concern with these approaches outside of the utility of them in the first place is a concern about transparency meaning that you cannot find out how actually enGenics is defining particular episodes of care unless you buy the product and they will sort of open the box. It is certainly not in the public domain. A head to head comparison for example of these tools is not available although CMS has been experimenting with that and maybe Mike can address that.
A second type of approach that is much more recent is basically trying to reinvent the wheel trying to develop something in the public domain if you will that exists in a quite sophisticated fashion and nontransparent way in the public sector. For example, some of the work that we are affiliated with and the American Board of Medical Specialties is trying to develop episodes for 12 conditions. Remember this is 12 out of a potential universe of 500. I am not saying they are all equally as important but it is just a lot more limited. You may have heard about the approaches by Promethius which is an effort that is funded by the Robert Wood Johnson Foundation which has at its core an episode-based measurement approach but they put some additional methods on top of it basically trying to classify cost you would expect to occur in a health care system or in a clinical encounter for an episode of care versus trying to tease out potentially preventable costs of care.
These are typically based on costs that are associated with treating particular conditions meaning that you are dealing with the costs that are particularly incurred for treating a patient with diabetes. Different from that for example would be costs that would be incurred for the same patient who broke a leg where you would argue well, treating that really has nothing to do with the diabetes for the most part. Those costs would not be included for calculating diabetes related cost of care.
This third approach and I am not exactly sure if this the right classification but I have called it a transparent condition specific per capita approach that NCQA has adopted for six conditions. In full disclosure in my previous life I was at NCQA and helped develop them but here the concept is basically focus first on episodes that are relatively easy to define at least timing wise. Basically, chronic conditions and it has this is indeed cardiovascular disease, asthma, and so forth and try to count up the total cost of care that it spends in treating these conditions. This would include not only care that is specific to cardiovascular disease but include for example, cost associated with a broken leg.
What are some of the key challenges that the measure developers have to deal with? For one, it is notion of well are we dealing with costs? Are we dealing with resource use? Are we dealing with paid amounts? The answer to that can differ a little bit. If you deal with one payer only, what you would probably deal with is the paid adjudicated amount for a particular cost of care. If you are trying to do this across payers which for example, NCQA is doing by comparing the two different plans, you have to find a different unit because the fee schedule of health plans as you know is as securely stored as gold at Ft. Knox. You will not get that. You will have to develop some alternative way of putting a price on something that is not the actual price paid by anybody in particular.
I can talk more about what some solutions are to that might be including how you might extend based on some work or the fee schedule that Medicare has and impute other stuff that they either do not have in their benefit package or that is not defined there. Then you would talk more generically about resources as opposed to any specific dollars.
In terms of the methods for episode-based approaches you will first have to figure out well how do I define an episode? How long is it? How do I translate a clinical concept that I have about what might constitute an episode and operationalize that in my measurement environment in a way that I can come as close to that or approximate that as best as possible. To date as you all know, EHRs or clinical data systems are typically not used for measuring cost of care mostly because they did not exist for the longest time. Second of all, the accounting standards are not exactly clear in how you would put a dollar value for example, on certain things.
Typically, the infrastructure that we are dealing with is administrative data full cost. You still have the problem of how do I approximate out of administrative data some clinical concepts of an episode of care that I want to come to as close as possible? Just as with anything else we sometimes do pretty well and we sometimes are way off and quite inaccurate. We would have to test how close you are with your approach. You have a problem or you have an issue relative to sensitivity and specificity. We all know that cost of care and Carolyn with her eloquent brief about that this morning, sicker patients generally cost more. When we define episode, we need to either on the definition of the episode itself sort of rein in the availability in patients to get to a homogeneous group of people that we want to compare in different settings or you have to try to deal with it on the risk adjustment side and no risk adjustment system that I know can really take care of a large amount of unmeasured variation. You have to sort of deal with that.
You have to deal with issues of exclusivity and composites. We heard this morning about how or to use a reference from yesterday how the future in quality measurement and Paul had talked about that also is probably not the 789th process measure of was XYZ rendered within this timeframe as opposed to did the patient walk X amount of time after they had hip replacement surgery. You have the same issue here. If you want to construct episodes that you can put together in terms of composites, meaning that we are not measuring it only at the this micro level, but we want to be able to roll it up to have a better point of view of what the cost of care might be, you then have to figure out how they can stack.
Then you have to deal with the problem of exclusivity of assigning patients two different episodes. That meaning that if you are, and this is obviously a very common problem, if you have a patient who has diabetes and who has CHS and who broke a leg last year, you at least have three episodes but you need to figure out if you wanted to measure that doctors total cost of care you do not count that person three times if you wanted to do that.
In the interest of time I will not go into a lot of detail on this risk adjustment, I know you are all very familiar with the challenges with that.
In terms of the data sources measuring costs we already talked about that administrative data is probably for the next few years be the only data source that I know of that we have available to measure cost of care in this way. Obviously, cost measurement systems for example on the hospital side who have cost reports and so forth but in my estimation they have not proven to be all of that fruitful and I do not hear a lot of people talking about building on that in any particular sophisticated way. However, there are opportunities now and I will talk about that in a little bit, how we might be able to get a little bit more precise on our administrative data if we link in some clinical data. For example, one of the problems with measuring through claims is that often the risk adjustment or the precision on the denominator decision is not there because clinical detail is missing. If we could connect some other clinical data sources that might work provided that these data actually exist in a somewhat ubiquitous way across the country.
We for example, currently have a project underway in California where we are linking the registry data, the clinical data from the Society for Thoracic Surgeons with WellPoint administrative claims in all California hospitals. Here the opportunity that is aside from measuring quality is that we could use the clinical data that exists on the registry side to better risk adjust our cost measurements that come through on the administrative side. We can probably think of many, many more examples of how that could work.
I talked a little bit about the problem with standardization already. One of the issues for example that we have such a hard time getting a handle on how high is a health plans administrative cost is this problem of standardization and accounting standards for what exactly should go in what bucket. I think as we all know there is a lot of wiggle room if you will to measure that at the moment.
We talked about the issues of if you measure across payers how you have to find multipliers I call them or a fee schedule that is not a proprietary fee schedule but that could be used. Obviously, in terms of comprehensiveness and this is generally true if you try to measure provider performance based on any one health plan or payer’s performance or even CMS what you will encounter is that you get a partial view obviously because that does not represent all of the care that is rendered by that physician. Ideally, if you do use administrative data try to shoot for all payer data that is informing that particular result.
In the interest of time I am going to skip over some of this. Key challenges obviously are risk adjustment and that you do not want to over adjust. You do not want to adjust away differences that are real that you would like to get a handle on.
What we do not have to work on at all as far as I know is actually the concept of efficiency in the sense of linking costs to a particular level and fixed levels of quality. NQF as you may have heard has not endorsed any cost measures as a matter of fact until not too few years ago this was sort of considered anathema to their mission. With the arrival of Janet Corrigan that changed luckily. There are now some frameworks that have been identified but I think as Carolyn would say they are sort of at a 15,000 and 30,000 level foot view. How to operationalize that is not exactly clear but we expect that an endorsement process will go forward sometime early next year with measures being submitted. A lot more work to be done on how exactly would we link measures of cost with quality to get to an efficiency.
Then the issue of endorsement obviously has to do with trying to get a consensus. That is what I want to get into in a little bit more is how in the world are you even if we had this would we implement it in a consistent way? What might be a practical and pragmatic way to think about the infrastructure? Here I want to make a few points about why a distributive network or a federated model might be viable here as well. We are actually trying to test that in some projects both on the quality side and soon on the cost side.
I wanted to make a couple of overarching points in terms of how we got to our conclusion. Basically what we are saying, and Paul said this before is with the ARRA and with the arrival of more sophisticated IT technology and the funds hopefully to pay for them, we will see data sharing between providers increase hopefully significantly to improve care coordination around the country. However, providers will come together with their business associates in a variety of different arrangements and data sharing environments with probably different capacities to do certain things. For example, you have providers coming together in integrated delivery systems be they brick and mortar or virtual in the future, that may be one arrangement. You may have another arrangement where providers may work particularly close with health plans who have figured out ways to support providers with information systems.
I think in Massachusetts there may be some early signs of how health plans might be able to do that in a somewhat sophisticated way. You may have other arrangements and this by the way might differ a little bit by condition. You may have other arrangements where providers work very closely with registries be they specialty based registries or be they regional registries that have been set up. In very advanced environments which I cannot think of many other places than Indiana and Massachusetts quite frankly where you would have actually communitywide health information exchange where information is being exchanged.
A lot of diversity and I think that from a national perspective what you want to do is take advantage of the many issues that are out there and try not to be too prescriptive about particular ways that you have to get to an end point for which you have to be more prescriptive.
The basic notion here is that we are saying that you know, this is of course preaching to the choir, providers who have come together in different data exchange environment, that is the blue box and then out of that exchange providers get value added information in terms of patients lists, decision support, alerts that would allow them to act on particular issues.
Payers and we for example have seen this on the CMS side, on the disease management side where for some time CMS tried to provide claims data into that environment which for example informed them about re-hospitalizations and so forth. What we are then saying is out of that environment, where PHIs being exchanged, we should be able to extract in a consistent way, numerator and denominator statement very much along the lines of what Larry had talked about earlier. You can do this as frequently as you need it to be. That information which does not contain any PHIs, it is just basically a rate of how many people with diabetes got XYZ service can be used by public and private payers for incentive payment. It can also be used to inform consumers about selection of providers and by the way, consumers also can contribute information to this data exchange.
This is what this whole picture looks like together. Basically what we are saying here is this should be done in tandem with the several policies that are being now advanced on the federal side both for meaningful use definitions of IT, increases of value-based purchasing and so forth that the definitions of measures and requirements should align and should ideally be the same. That would give us the biggest bang for our buck. In terms of a practical path forward we think that these distributive data models have a lot of promise. We are now for example, experimenting with a way to consistently query health plan data not just for sentinel events as for example that FDA is now doing but to query them for some performance information which over time that data will be increased with clinical information and so forth.
If we do that in a consistent way we can answer through these pilots a number of very important questions that I think all you will have and again in the interest of time I will not go into that but maybe you can read about them afterwards on the slide, to answer critical questions about how to connect data and how to get the right information out of the data and then act on the data. We believe this requires leadership on the federal side or on the public sector side in terms of coordination and planning. For example, your entity to figure out the strategic vision methods and timeliness for setting the expectations for what should happen. Then the implementation happens both on the public and federal sector side in a coordinated fashion and the private sector side in terms of agreeing on certain queries if you will, and then use those queries to go after distributive data to bring back information that does not require the sharing of personal health information.
With that I think I have gone over time and I apologize. Thank you very much.
DR. CARR: Thank you very much for a very rich presentation and we will study in detail your slides. You have given us great food for thought. I want to hold questions and ask Mike Rapp to pick up from there.
DR. RAPP: Good morning, thank you for the opportunity to present today on the subject on value-based purchasing, combining costs and quality. I heard reference to an interesting, pragmatic ways forward. I am appreciative of the kind of conceptual framework that we had in terms of practical ways forward. That is what of course we have to deal with at CMS because usually we do not have too much time to implement many ideas that come forward, many of the ideas from the private sector find their way into legislation so then it is our job to implement them.
I am going to kind of try to go through a variety of things fairly quickly just value-based purchasing conceptually. What our implementation is currently. I want to focus on outcome measures so when we talk about combining costs and outcomes so where are we on outcome measurements. I want to review consideration and the use of these. I want to spend a bit of time on our thirty day mortality measures and our thirty day readmission measures and reflect on moving forward.
I will do a little disclaimer. When you heard that CMS might be experimenting on measures, we do not like to think of ourselves as experimenting but implementing or engaging in pilots and so forth. In any event, what value-based purchasing means to CMS is transforming Medicare from a passive payer to an active purchaser of higher quality, more efficient health care. The various different concepts that Joachim talked about I think are interesting and I do not disagree with him but we kind of use the term of value-based purchasing and value a little bit more broadly. It refers to a variety of tools that we use including measurement payment incentives, public reporting, conditions of participation, coverage policy, QIO program. We have pay for reporting, pay for performance, gain sharing, competitive bidding and so forth. Currently our only program authority to pay differentially for better quality is in ESRD. When MIPAA Legislation passed in July of 2008, Congress also required by 2012 that we implement value-based purchasing for in-stage renal disease.
They did it in connection with bundling payments, bundling payment particularly with erythrocyte stimulating agents so those previously were paid for separately and now they would be bundled so that the incentive would not be any more to use it would be to not use it because you are getting paid for it anyway. This idea then of value-based purchasing or measuring the quality and having a differential payment of two percent based upon differential quality is first authorized in that.
There is broad support for value-based purchasing. We implement it in many ways in terms of demonstrations in particular. We have our pay for reporting program; once again I will not go into detail on that.
In terms of measuring value, the basic concepts here are bringing together cost and quality. In terms of the quality side of it we have different measures available to us. Outcome, I think that most people would describe what we want to really use if we can. Process measures, but then also other measures like experience of care.
Potential costs to consider well, you can consider all the costs of care for a particular beneficiary or you could consider the costs associated with a particular professional. You get into all of these attribution issues, what is fair to hold different parties responsible for?
Then what is your level of attribution? Are you going to focus on individual doctors? That is always a challenge. I personally think we should spend less time on that and more, at least in an initial start at groups of professionals or even higher levels. Are we going to have accountability of facilities, professionals, and how will we allocate among the facilities and the professions. What kind of time period are we talking about? We have often talked about episodes of care. Those are a little bit hard to implement I would say in terms of identifying when it starts and when it ends. You might have multiple episodes or you could relate it to a particular health care event. For example, hospitalization which is a much brighter line and it deals with a subject that is closely associated with the Medicare program and the costs involved in Part A of course would be hospitalizations or post acute care, that sort of thing.
Considerations in measuring value or efficiency we need to integrate the quality and cost. It is not resource use alone as Joachim talked about. We do have resource use reports that the Congress in the MIPAA Legislation required us to share with doctors but those are not publicly reported and there is no authority to do that, those are confidential reports that are shared but we do not look at that as a value per se. It compares on a relative basis the use of different things. Another way of integrating cost and quality are never events and appropriateness criteria. You would say the cost is just not justified. In that case, you can integrate them.
What are valid cost measurements? You have to have a valid cost measurement and analysis. Think in terms of the same population. What are the scope of costs that you are going to consider? What is a perspective, as Joachim talked about the patient, the professional, the provider, the payer? Of course, we always have to think about the adverse consequences in anything that we do. You push on one part of the balloon and something else goes out. The health care system, it definitely when you make payment adjustments or even publically report information they adapt to it and try to deal with whatever is put into place. What is the proper attribution? We will talk a little more about these as we go further.
So as I mentioned, you could use various on the quality side of it, you could use different measure types. There are advantages to each of them and disadvantages. On the process measures in particular, what we have found is they rapidly become topped out. At least if you have a measure which has to do with do a certain thing, give a certain process of care. The ones that do not tend to get topped out are the timing measures, that is hard to necessarily get to optimum there.
You have to focus on the processes. You have to think about how they impact the outcome too. With outcomes you of course, they are less available but the advantages are significant in the breadth and scope. They are certainly less subject to becoming topped out.
The experience of care measures are definitely good since it gives the perspective of the patient. They also have a hard time being topped out. You could also add structural measures to the mix if you wanted to.
I am going to go quickly through where we are with outcome measures since I think that is where we would like to get if we can. I think most people would. In the outcome measures used by CMS, I count them as 74 right now but do not hold me to that number since I always have a hard time knowing for sure about every last implementation. We have 28 in patient measures, 8 physicians, and so forth. You see them and I will go through them quickly.
In our RHQDAPU and QIO Program we have paper reporting for hospitals, they are given a two percent incentive or they avoid a two percent penalty I would say if they report the measures to us. In the RHQDAPU Program currently as far as outcome measures we have a 30 day mortality for AMI, heart failure, and pneumonia.
We have implemented selected AHRQ measures of selected medical conditions. We use mortality and then AHRQ measures for surgical conditions and procedures as you will see listed here, other complications of surgery.
We have our readmission measures which are outcome measures but we look at them as a form of efficiency measure with the idea if you avoid readmission then you are avoiding an unnecessary cost or you are avoiding a cost.
There is an all patient readmission rate that we use in our QIO Programs and in our transitions of care theme which I will tell you a bit more about. Then finally, we have intermediate outcome measures which is 6:00a.m. controlled glucose.
A set of outcomes for the hospital, we include some outcome measures in the Premier Hospital Quality Incentive Demonstration. Mainly they are inpatient AMI, CABG, heart failure, have some outcome measures with regard to hip and knee replacement. There is a plan as the Premier Demonstration continues on to add some additional measures to test them further.
In the value-based purchasing plan that we were required to submit to Congress again in 2007, we identified a number of tentative measures that we include in that. That included a 30 day mortality measure as well.
Other ways beyond public reporting or showing these differences among parties are our Hospital Required Conditions Policy. In the Deficit Reduction Act, the Secretary was required to identify high-cost, high-volume for both conditions to the extent that they were not identified through or present on admission. Indicators having been present on arrival at the hospital then those complications that occurred would not be paid. The basic payment would be made but insofar as if there was a complication. Foreign objects retained after surgery, air embolism, blood incompatibility, Stage III pressure ulcers, falls and trauma. These things were felt not to – they were on the never event list of NQF most likely - so the things that should not ordinarily occur. So that was the test. The legislation did not require it to be something that should never occur but ordinarily should not occur. They were put on the list. What happens here is insofar as they do occur as complications or secondary effects of the basic diagnosis that additional amount would not be paid.
Other items, manifestations of poor glycemic control, catheter associated UTI, and vascular catheter associated infection, surgical site infections, deep vein thrombosis, and PE with total knee replacement and hip replacement. So this is an example that no one would ever suggest that a DVT/PE should “never happen” and certainly that would be the goal but you could hardly say that. Nevertheless, through rule making that was put on the list and insofar as this is a complication of total knee replacement and hip replacement there would be no additional payment given to the hospital. In a way this is combining cost and the quality in one but in somewhat of a different way that Joachim was discussing.
In terms of what this is going to do for the Medicare program and save it from going bankrupt as you see here the estimated savings here are $21 a year. That is not going to save the Medicare program or probably any other coverage for health care. Nevertheless, that is where we are on that. Some of it has to do with how good the present on admissions indicator works. How much time people spend demonstrating that they do not have it.
This was extended for national coverage determinations for hospitals and physicians so that in fact, not only is there no coverage for the complication, there is no coverage at all if you operate on the wrong leg, wrong patient, or wrong surgery on the patient. We do not have too many people arguing with that but of course, if there is the wrong surgery on the wrong patient, how about the right surgery and so forth.
In PQRI we have now some 170 measures or so in PQRI. We only have a very few outcome measures for physicians. Diabetes, control HbA1C, LDL, and blood pressure control that we use in NCQA measures. There is a CABG measure, deep sterna wound infection, stroke/CVA, these come from the STS measures and they would be collected through a registry.
Basically if you look at the hospital we have got an array of measures that are outcome. Some reflect cost in a physician world where we do not have many. In a physician group practice demonstration we are using those intermediate outcome measures. We are required through MIPAA to provide Congress with a physician value-based purchasing plan in May of 2010. So in working through that plan certainly outcome measures would be under consideration.
Home health measures are mostly outcome measures. Things like acute care hospitalization and following home care emergent care, whether they are discharged to the community. Functional measures, pain medication management, surgical wounds, complications, and incontinence, they are basically all outcome measures. What we need there is a few process measures.
The nursing home for the long stay not a short stay necessarily we have pressure sores, functional status, pain, incontinence, UTI, mental health, and so forth. These are outcome measures.
In the short stay nursing home we have percentage with delirium, moderate to severe pain, pressure sores and so forth.
With ESRD, we currently post patient survival, the amount of hemoglobin control for ESA therapy and hematocrit below the minimum level.
In Medicare Advantage we have use outcome measures.
We have got an array of outcome measures. We have also a number of considerations we have to think about in terms of getting data. A variety of potential sources for that certainly electronic health record would be something for the future. Now Joachim talked about distributive model of getting this data because of the concern about privacy and so forth. Currently that is not the way that we approach measurement. We collect the data. In the hospital world, where the charts are extracted by the hospitals, all patient data and that data is sent to CMS in the QIO program and the measures are calculated.
The advantage the distributive model has the advantages that he mentioned getting the data together in one place, and we are talking about all of the patient’s data on all aspects of the patient but just those data elements for the measures themselves prevents one to first of all do risk adjustment. If one has to deal with the issues across different settings you can bring that data together. When you think about outcomes how are you going to get information about outcomes without knowing who you are talking about? You at least have some sort of pseudo identifier that does that for you. These are kind of pretty significant issues. Certainly all payers get identifiable data. Claims, that is the nature of claims when they talk about bringing claims together.
Those are very important issues. Certainly we would always want to maintain a high-level of privacy on the part of the patients. In terms of the practicalities, in terms of a distributive model, we do that in PQRI and our registries in that we have, the model we have there is basically that each of the registries calculates the clinical quality measures based upon the data that they get from the physicians.
We have 74 registries but as you can imagine that means that all of these registries have to work exactly the same. They have to use the same methods of calculating otherwise you are going to end up things that you cannot bring together. If your numerators and denominators, you have to be satisfied that those are calculated exactly the same way and that your denominators are select and so forth. You do not have that then you do not have any kind of data that is comparable. Having that standardization in place I think is wonderful from conceptual standpoint in terms of its practicality in the near term, I am somewhat uncertain about that.
In our CMS 30 day mortality measures, these are risk standardized 30 day all cause mortality and readmission measures for AMI, heart failure, and pneumonia. They are NQF endorsed and implemented for the RHQDAPU program. This is based upon Medicare claims alone. It is limited in that sense although large portions of hospitals’ heart attack, heart failure, and pneumonia patients are Medicare beneficiaries.
We are looking for ways to bring in other data. For example, the Veterans Administration has contacted us and asked could we bring their data in and it would be part of the overall thing. We have been contacted by some representatives of health plans and asked could we bring in private sector data for this. Again, to do that you basically have to bring the data together, you have got to run your risk adjustment and your model, and come up with your results. That is something that we are exploring.
You may be familiar with our 30 day mortality readmission measures but they were developed by a Yale/Harvard team of “statistical experts.” Harlan Krumholtz and Sharon-Lise Normand have been active on that. The measures again are NQF endorsed and have gotten a lot of attention because they have been published for a couple of years on the mortality side. This last summer we posted the 30 day readmission measures. The USA Today picked up on this and linked the data to their newspaper data server so people could search not only on our site but through this USA Today site.
Why 30 days? Well it is a common time period that people use to look at outcomes. It is not inpatient so it gets them out of the hospital for 30 days from the start of the admission. We in fact, and with NQF endorsement, are holding those hospitals responsible for what happens to them even when they get out of the hospital and even the readmission issue. Although of course there are a lot more parties involved in it than the hospital themselves.
Again risk adjustment, and I will show you how we display these but we have now moved to calculating the performance rates based on three years’ worth of data so that we are better able to show the differentiation among hospital performance but based upon data rather than modifying such things as confidence intervals and so forth. We use an interval estimate that is a 95 percent level of confidence.
This shows you a distribution of AMI and heart failure rates. The way we display them is this. We first of all show a diagram of something like this for each of the hospitals. That center vertical line is the US national rate. So if the US national rate for readmission for heart failure is 25 percent which I think it is something like that, if at the 95 percent confidence interval there, there interval estimate crosses the US national rate then we categorize it as no different. If it is to one side or another it is even worse or better.
When we started displaying these we displayed them as buckets. When you have only a years’ worth of data you do not have many in those buckets where you can say with a high degree of confidence that are in fact different than the US national rate. That was the way we did it the first year was buckets.
The second year we put the individual information more like this in terms of where they would show what their point estimate is. So you will see for example a heart failure ranges from about seven or eight percent up to – this is the mortality, up to about seventeen percent. So now we show exactly what the rate is but a point to recognize is whether you say it is different than the US national average is based upon this 95 percent confidence interval.
There are a lot of things that you have seen. I know with the Dartmouth Atlas and so forth about the geographic variations so we plotted out the geographic variations on these different measures as well. Distribution of AMI mortality you see here. We published something on this which basically pointed out there was not specific correlation between the AM 30 day readmission versus the 30 day mortality. In other words, it is not necessarily that one is better than the other, they are better on both. There was no specific correlation.
Here you will see the mortality for heart failure. Then we have our readmission. These are a little tighter in their distribution but still a significant variation in – look at the heart failure and you see that the average of the US national rate is 25 percent with a variation here of going a little bit under 20 to over 32 percent.
I was at a party and I mentioned to somebody that they might be surprised to know that heart failure patients, 25 percent of Medicare patients with heart failure are readmitted within 30 days. He said, no, that does not surprise me at all. They are sick. So you think that this grabs perhaps doctors in health care professions like you know it does seem like we just had him in the hospital and back in 30 days. You could have different points of view on this and when you start getting into these kinds of issues about do you belong in the hospital or don’t you belong in the hospital and you sort of point this out I think people can legitimately have different reactions.
From a beneficiary standpoint, I guess we have to think about that too. What do they think? They probably think if I want to go into the hospital, I want to go into the hospital. I do not want somebody telling me that the hospital does not want to do that because it has been less than 30 days and I am going to be on a website or something. There are a lot of different perspectives as Joachim was talking about.
Here is the distribution of readmission. I do not have the Dartmouth Atlas overlaying this but I know that there is as it has been frequently pointed out that Minnesota is a particularly advantageous place from the point of view of efficiency. Well, if you look at AMI by readmission, it seems to be darker and then if you go down to South Florida it does not seem so dark.
I have not correlated these with any other atlas. I think it would be interesting to try to do that but the AMI readmission rates do not necessarily correlate with the mortality and they do not necessarily correlate with other things either. Here is the heart failure readmission and here is the pneumonia readmission.
So in any event with the 30 day readmission rates the AMI is at 19.9 percent, heart failure 24.5, and pneumonia 18.2. the goal of course is not zero but we view it as overall the readmission rates are too high. Hopefully, this would prompt lowering the curve or lowering the rate of readmission and all so narrowing the distribution.
We have other hospital level measures like this that we have developed and that have achieved NQF endorsement and would be available for implementation in the future to us.
PCI 30 day all cause risk standardized mortality and also for lower extremity bypass. There is interest - I think in MedPAC a few years ago recommended building out measures in this arena.
I want to talk a little bit about moving to episodes and then I will wind up here. Joachim was talking about the episode group or you start with some kind of initiation and then you come to an end. The hospitalization itself is I think – has a lot of advantages and does give you that bright line. It is the thing that you have got to be at a certain level of illness to end up as an inpatient in the hospital. If look at the hospitalization at the endpoint you can then go out for some period of time and look at all of the care that takes place and think of all of the service and all of the people involved with it. It is an important starting point and possibly endpoint the AHRQ measures on ambulatory sensitive conditions are designed to measure whether care – which is likely to result in not having to go into the hospital is being rendered.
Of course, when you again as I mentioned for care not associated with hospitalization is the challenge of defining when the episode of care started or ended but of course we would be interested in that as well. Again, I think it is just a bigger challenge unless one deals with the ambulatory sensitive conditions. Beneficiaries not receiving care, I always like to remember those because these are patients that presumably have health care coverage but they do not see anybody so they do not have any claims and they do not have any health record and so forth. They still may have high blood pressure or any number of things. We probably need to spend a little bit of time on that segment of the population.
If we use hospitalization as a starting point, I want to point out some of the other things that we are working on that do not necessarily get a lot of attention. That specifically is the post acute care demonstration that was required in the Deficit Reduction Act. The idea here is in – when we talk about data sources we go to claims or charts or so forth. The post acute care time period is somewhat unique in that we routinely collect in the SNFs(?)(B-1:43) and in the long-term care, every patient that is in a nursing home has to have an assessment on a regular basis and that data is submitted to CMS. It is that data source that drives the calculation or clinical quality measures that we put up on Nursing Home Compare and so forth.
With that the problem with it is the instruments are different in the different settings. We have the SNFs which use the MDS, the skilled nursing facilities, the short-term benefit that Medicare pays for after which the long-term Medicare does not pay for. In any event that MDS instrument does have regular assessment in a variety of things.
We have in the home health a thing called the OASIS which does the same thing for home health patients. Then we have inpatient rehab facilities as well. The problem with that is you cannot compare across these settings, you cannot compare the costs if you do not have the same kind of assessment. In this demonstration they required us to develop a single instrument that could be used in all of those settings that would start at hospital discharge. Then it would follow that patient through that period of time. Then what the demonstration is about is to look at the various assessments in terms of functional status and other things that are included in that assessment and then figure out the costs and compare them to that.
Interestingly, the way the payment system in the post acute world works is it is based upon that assessment. That assessment drives the payment groupings that are made. It is an interesting area that could possibly tell us something about the future.
Now this instrument that is used in this demonstration is called the care instrument. If you think about your data sources and you think about episodes of care and you think about episodes of care that start at hospital discharge, what would be better than an assessment that is individually made of the patient starting at hospital discharge and carrying it through those post acute settings over a standardized period of time. You will get not only things like adverse outcomes but you get functional status which is a key ingredient of what kind of services people need or do not need and if we carried that through.
We spent quite a bit of time thinking about this in some of the previous HIT work that was done with the AHIC was the recommendations were made for a standardized dataset which had in mind this care tool. As we go forward possibly electronic health records could be – the inpatient record could include these items in there. If that was the case then that would be the start of the assessment which could be carried on further. This would also think about coordination of care. It is a big issue that people have. How can we coordinate care? You cannot coordinate care if you cannot share information. If you have it in electronic form and you have a standardized set then they share it in the post acute setting and so forth. It could deal with all kinds of issues like medication reconciliation and so forth. You can do that and at the same time you can couple the costs with it. You know what the costs are and you can add the overall costs. Then you can go on to such issues as okay, who is responsible? To what extent are we going to hold the hospitals or are we going to hold the professionals?
One other thing that we have done, the care transition’s QIO theme in the 9th scope of work deals specifically with the issue of re-hospitalizations, both looking at conditions and geographic region. In kind of an interesting way of approaching this in terms of attribution is that we attribute the impact of an individual, professional, or provider based upon proportion of transitions for the beneficiaries in that geographic region. So just to go over that again, you have patients. They live in Washington, D.C. They are Medicare beneficiaries but they do not necessarily get their care at Providence Hospital or GW. They may go over to Johns Hopkins for example. The doctors, where are the doctors located? What we have done in this is we have linked up the beneficiaries with the providers of care. We weight basically their impact on the care transitions based upon what extent that their care is representative of transitions that the beneficiaries experienced.
In any event we get into these attribution issues but it is something that we are working on through this and we will have the output of the scope of work and measures and so forth. The intention here is to promote improved quality of care within the setting, this for example heart failure, those things that prepare the patient for going home knowing and understanding medicine and so forth, coaching, following up with them afterwards. It promotes quality of care within the setting, improves coordination processes, and community involvement as well.
In conclusion, there is certainly active work being done I think to help develop a value-based purchasing framework at CMS. I think a whole lot of things potentially to draw on. I think in general, our preference would be to the extent to which we could use them, outcome measures because of a variety of benefits of that.
We have a lot of work to do in terms of getting measures in the positions setting and we always are going to have the challenge and the physician setting of the small numbers which leads I think us to want to at least tackle first the group. This is my opinion. Everything that I say here is my opinion. I am not speaking for the Agency or the US Government or anything else. It is my idea.
Anyway, the idea of considering the group or other level of attribution and I was kind of talking in that post acute setting you would see that when you get in the hospital and things happen. You could try to weigh what degree of involvement different parties have but you could perhaps have an aggregated cost and an aggregated outcome at that point. Perhaps the attribution issue would be significant but the measurement would be made less difficult I think.
That is basically a whirlwind through a lot of things that we are working on and I would be happy to discuss it further and to get your ideas.
DR. CARR: Thank you very much. That was spectacular. Do you have some time? Can you answer a few questions? I know we ran up against the time with Dr. Roski also. Maybe if you could come up to the table. Harry, I think you had the first question.
MR. REYNOLDS: Michael thanks again. The question I have – well first, you have got a lot of good and focused work going on and we appreciate it. You talked to us in a Meaningful Use Hearing. We heard yesterday from lots of different people that everybody is looking at – you referenced some of them today that you are picking up from other people. With Medicare being the largest payer, Medicare moving forward at this speed, meaningful use being on the table, why aren’t those measures just being the ones that are selected? I know it does not cover the whole population. You do not deal with every set of – and if something comes out as meaningful use is CMS going to adjust or –
DR. RAPP: You are saying why don’t we use measures that we are using in other settings for the meaningful use clinical quality measures?
MR. REYNOLDS: No, what I am saying is that you just listed how CMS sees value and quality.
DR. RAPP: Well I went over a lot of things that we are doing that we might -
MR. REYNOLDS: I guess all I am trying – as we recommend for the entire ecosystem some suggestions and some considerations and so on, the fact that all of these things are going on when we come up with one idea on how to do meaningful use or there are sets of measures on how to do meaningful use, one of the concerns that we heard yesterday is that payers be together at least in some way. Just trying to understand as you see the rest of this going on how do you see CMS playing in that positionally, functionally? If the measures that come out are different do you pull back some of yours, kind of that statement of positioning of that.
DR. RAPP: So first of all I cannot speak to the future. I can speak to the past and the present. In terms of what is going to be supposed by the Secretary in terms of the clinical quality measures that would be required for meaningful use or for the other measures that is up to a lot of internal discussion and clearance and sign off by the Secretary and so on and so forth. So you really do not, even though I have some ideas of things that would be discussed one does not really know until it is out. If I knew I could not tell you and I do not know because nobody knows until the action of the agency takes place.
Going back to the subject of electronic health records which I think is really the subject here and the reporting of clinical quality measures from electronic health records and using electronic health records, we have been interested in that for some time. We reflected most specifically in the Physician Quality Reporting Initiative in that from the very beginning even though the only way we could implement it in six months was to have claims-based measures. We indicated that we were interested in the future of moving to electronic health records and submission. We have followed up on that by developing electronic health record specifications and seeking to work with the standards organization and so forth so that we do not get out ahead of them and that we are in sync and so forth. It provides somewhat of a foundation from which wherever the Agency decides to go in the future with regard to electronic health records at least that is somewhat informative I think at a minimum.
We have proposed under PQRI that in 2010, we quality those electronic health record products that have sought to obtain such qualification and testing it and if it works out then we would allow electronic health record submission of clinical quality measures for PQRI in 2010. So again, that kind of thing can inform a lot of work in the future.
In the hospital arena, we did the same thing in that we sought to have the electronic specifications for a set of hospital measures developed and those have just been posted on the HITSP website I think recently for public comment. That provides again a foundation. There is a lot more work going on as well. I think that is about as specific as I can be but it is not like high-tech legislation is of course something that is brand new and providing a lot of incentive to move in that direction. We have been interested in moving in that direction all along.
What the final framework would be – there are issues that we have talked about here in terms of distributive models and so forth. There is a lot that has to take place. There will be regulations proposed that will be subject to comment and no doubt the regulations will probably change somewhat based upon that comment and also the input that has come from the advisory committees.
DR. CARR: Dr. Roski I know you are time constrained. If there were a question could you answer it or do you need to go? Was there a question for Dr. Roski? No?
Let me let you make your timetable then. Larry it is back to you.
DR. GREEN: More questions for Dr. Rapp, one about episodes. The question is either your thinking or whomever you choose to represent or not represent, that is all I can do. You used the word grouper and then you also discussed the difficulties in deciding when they begin and end. There is an intersection this committee, well not the whole committee has heard the last couple of years relating to episodes about the challenges of defining but there is a core intellectual distinction between an episode that becomes a reliable definition when a computer reruns the same program again and drops the things in the same bucket. Then there is the definition of episode that clinically meaningful. We are interested in meaningful measures here and what is your thinking about whether or not CMS gravitates toward clinically meaningful episodes versus a statistical aberration that can be used?
DR. RAPP: Well I think that we want everything we do to be clinically meaningful. We take advantage of the work that is done in the private sector and brought to our attention. We rely on endorsement of the National Quality Forum rather than going off on tangents of our own. But with regard to the episode groupers, I am not the one in charge of trying to implement those in the Agency but I do know of the challenges that they have presented in terms of trying to define these episodes. I think that they have to do with you are looking at when does an episode of a heart attack start? If you are not going to start that at the hospital where would it start or other more less dramatic acute care events. An episode of asthma, asthma is a chronic illness.
I think those present significant differences but in addition then what costs are you going to throw in there? Are you going to throw in just the cost that that doctor is specifically responsible for? Are you going to put in that they came to me with a sore throat and pretty soon they ended up in the hospital and I am the only doctor that they saw but they ended up having pneumonia and all sorts of things and I am all of the sudden responsible for that.
I think the attribution is just as big of an issue as when this episodes starts or does not start. That is why I think that those things will be highly-challenging. Those are being used right now mainly and really only for these confidential feedback reports. Congress has not authorized us to put up things like that on a website for public reporting and so forth.
By contrast as I mentioned, things like readmission rates and those kinds of measures that we have gotten through NQF were prepared and we can go forward with those.
DR. GREEN: I do not recall us hearing any testimony or learning anything in the last couple of years about the attribution issues in the episodes but in terms of when they start and begin we have heard testimony and seen examples where you ask the clinician, well this is a newer episode and when did it start and when did it end and they will tell you. It is very reliable for asthma, heart attacks, and all sorts of stuff. I just want to get that on the table.
The other question is –-
DR. RAPP: So you are advocating I guess in favor of those?
DR. GREEN: Well I think episodes seem to me to represent the insertion of time into care.
DR. RAPP: Right, but you need to have that episode start – does it need to start – the only issue I have which is I am not sure again, I am not an expert on the episode groupers just from what I have heard there is a lot of overlap on these things. It is not necessarily as uniform in terms of that but be that as it may, we are interested in the time issue and in interest in struggling with this issue it does just seem to me that it is easier to start with something like hospitalization and go for a period of time thereafter.
First of all you are dealing with the most expensive kind of care. If you are in the hospital you have already spent quite a bit of money, post acute care. There are all kinds of variations that take place here. People go into the hospital, they go the nursing home, they go back in the hospital, they do this, there are a variety of things that happen or the RTI wrote a report on that.
I do not really disagree with you. I just have not seen how we can effectively implement those readily.
DR. GREEN: My other question was about home care in transition. This goes back to yesterday afternoon again, about trying to understand our underlying assumptions about the constructive care, the model in which we are operating. So all of the home care slides that you had are really about home health care providers as I read them, right? That is of course not the way most home care is provided. Most home care is provided nonprofessionals and family members and friends and neighbors and most of it is organized in other ways without professional, certified home care providers.
Then it goes to the transition issue too. Both in your presentation and in many others it is if we are assuming that transitions will incur in boxes. There is Box A, there is Box B, there is Box C, and there is Box D and let me tell you, the only person that is going to cross those boxes is that patient. If we are lucky the patient may manage to cross them. There is no assumption that there will be an integrating of some sort. This flies in the face of what we are seeing from our work in the National Health Information Network and stuff about the portability of digitized data and that sort of stuff.
We have heard stories of doctors rounding in rural Wisconsin while sitting in Beijing with a $29 camera and Skype and a laptop. Are we – well I started to say the word condemned that is a little pejorative isn’t it? Are we stuck with the notion that we have to have measures of transitions that presume that the care providers in the different settings are just going to do their box and there is going to be a transition measure that has to be invented for each one of them or is it possible to plan for a future in which – see this relates back to the episodes, where the whole episode of care gets integrated and connected?
DR. RAPP: That is really what I was talking about with the care and assessment instrument. It is not limited when you talk about patients going home we consider that a transition too, home without having involvement with the home health agency. Those measures are for home health agencies admittedly.
DR. GREEN: Is the assumption that the doctor that took care of them in the hospital will not see them at home or will not know about -
DR. RAPP: Well no, the doctor is part of the network as well.
DR. GREEN: Do you get my point? I mean we are going to start certifying hospitalist doctors whose responsibility ends when they walk out the door. When we moved towards patient-centered discussions we heard no one testify that patients would not like to see their care coordinator to cross settings by someone they know, who they are not a stranger. Are we headed towards these measures? These measures can be so powerful. I mean Harry’s question was really about when an 800 pound gorilla says I am going to measure this that is gravity as far as I am concerned. We can discuss all sorts of things but that is gravity. Will Medicare move towards transitions as if – well, they are clean boxes, we have got them defined, this is where we are going to look at them or how to cross the boxes?
DR. RAPP: Well I think that the point that you are making is to if I understand what you are saying, is to focus on the patient and look at it as a patient perspective and not look at it strictly speaking from the provider setting. Just by way of explanation and not in defense is what happens is when Congress passes laws they have paper reporting progress for doctors, for hospitals, for home health agencies that is the way that they pass the authority for us to do things. That does not mean that we should not look at it from a patient perspective. That is the advantage of an assessment instrument such as a care instrument.
Another thing I should mention in the Physician Quality Reporting Initiative one of the things that we are interested in is that the doctors participate in it since it is a voluntary thing so we can keep track of that. I also ran some data recently to look at it from the patient perspective. Do not look at the measures in terms of doctors and how many of those that reported but look at it from a beneficiaries – how many beneficiaries did those measures apply to? How many reports did we get with respect to the beneficiaries? We have some information like that that we will probably be sharing.
I would certainly agree with you that the perspective is the patient. You can decide that when a patient with pneumonia came in the hospital they got a flu shot but we are interested more in what did the population of the patients’ get?
So I think you need to look from measurement, one needs to look at it from a population level. I agree with you 100 percent. When you deal with accountability though you necessarily have to deal with the different participants in that system of care since that is what we are trying to measure, the care. We want to know what the ultimate outcome for the beneficiaries was. How they were impacted? Are the patients getting their flu shots? Are they getting this kind of care or that? What is the mortality rate for heart attack overall but then we want to dice it a little bit more and say okay, what is the role of this particular provider in the health care system and how well are they performing?
DR. CARR: Thank you, Bill.
DR. SCANLON: This is linked to Harry’s question about Medicare and meaningful use and I guess kind of linked to what Larry was saying with how can the gorilla be most useful? I guess I see two models in what CMS has done in the past in terms of possibilities. One is MDS OASIS model. They actually started not with the idea of what do we want – reporting done but they actually started with the idea of what should a provider know about individuals and start to provide good care. The MDS assessment goes back to 1987 long before it became an issue of payment policy or nursing home compare or any other kind of quality. What it has is that CMS or Medicare receives the information and then it has got all kinds of uses that can be made versus I guess the other model I would think of as the measurement approach. We decide to hear some measures that we want and we ask for the relevant provider to give it to us but then tomorrow we ask for another measure.
We keep doing this process and I guess I feel like over time we would be better off with the first model in terms of getting basic information about an individual that is relevant to the provider that they are seeing at that moment and then having sort of a data capacity that we can ultimately build measures on for the future. If Medicare were going in that direction say, this is where we would want to go then it would be a powerful force. It would be very meaningful use of EHRs because they I think are the tool that allows this to happen with very minimal cost to the provider.
DR. RAPP: I think that if what you are kind of laying out and I mentioned the care instrument, currently hospitals are required to do discharge plans but they are not required to do an assessment discharge. The first assessment is when they get to the nursing home if that is what it is. If you did the assessment of hospital discharge and it was available to the physicians and to the nursing homes or home health agencies, ESRD facilities, whoever it is then you would track that same basic standardized information across time.
I agree with you. Then you would get to the doctor as well.
DR SCANLON: Well we actually need something at admission and we need something from the encounter with physicians.
DR. RAPP: I think the assessment of discharge does not mean that you do not get information about what happened in the hospital. It is merely – it is the time point that the information is provided.
DR. TANG: Thank you for a comprehensive review of all of the stuff that is going on.
You mentioned PQRI in 2010; CMS will accept directly if I heard you right, the data that physician practices are reporting on?
DR. RAPP: I said that we had proposed to do that. The rule has not been finalized. It is in the comment period right now. It will be finalized about the first of November depending on whatever the Agency does. I cannot tell you what the final result will be but what we proposed is for a set of 10 measures, that we would accept those directly from EHRs for vendors that had demonstrated that their product will do that.
There was a set of vendors that self-nominated in early 2009 so it is only that limited set for 2010 assuming that the testing works. Just like the registries we wanted to make sure that the registries could submit the data in a proper format and so forth. Then we could take it and make sense of it.
DR. TANG: So you would get it directly from the end user or you would get it from the company who had queried the end user?
DR. RAPP: One or the other or both.
DR. TANG: So you are getting the raw rates of numerator and denominator rather than the G-codes.
DR. RAPP: The specifications are based on clinical parameters not – like it would be the value of a hemoglobin A1c. It would not be CPT such and such.
DR. TANG: So does that demonstrate the capability to receive that kind of information directly from EHRs for testing through their intermediaries for quality measures in the future, well maybe concretely, practically for meaningful use in 2011. Does that mean that you, CMS could receive the kinds of measures that were in the grid?
DR. RAPP: Well, PQRI is a lot different than the high-tech and what has to; it is a matter of scale for one thing. PQRI doctors primarily submit through claims or they do registries. This is just a little, I look at this as a small project that some EHR vendor products may be able to be accepted. It is not the kind of comprehensive infrastructure that is necessary to deal with the whole country.
In the high-tech legislation there is only one way to you can send it in. You cannot say well, I will skip the – you have to use, according to the statute, use the electronic health record. In PQRI you can submit it by claims or anything else.
DR. TANG: So let’s say for the vendors that you have tested or certified or qualified -
DR. RAPP: We have not completed the testing yet - that may end up testing that works -
DR. TANG: That could potentially scale – I mean what am I missing? That could scale as long as you could test all of the certified vendors in fact. You could call it the meaningful uses. Using a certified vendor we could create criteria that they would fill the capability of transmitting to you. I am just trying to see if that is –
DR. RAPP: I think I will leave it to you to draw your own conclusions. I just want to describe what we have done and what we have proposed. Obviously, that is a possible building block on other similar activities. I do not want to mislead you or suggest to you that would be the way that the Agency would see going forward.
DR. TANG: So am I correct that that would be a pathway that if we could scale and all of these other factors, if all of the vendors could be qualified by the same way your PQRI is constructed that is conceivable?
DR. RAPP: Again, I would rather you draw your own conclusions from it. I do not want to be interpreted as forecasting the future.
DR. TANG: I just want to know if I am on the right track.
DR. MIDDLETON: Thanks very much for really detailed and comprehensive and very insightful overview. I only have one question I guess. I sort of struggle a little bit with our current approach to snapshots of quality. Transitions of care and episodes of care certainly reflect a different dimension if you will. I am beginning to think of the temporal side of clinical decision making. The clinician who is looking at the diabetic before him will say well geez, what is the velocity of this disease? What is the vector of this disease if you will because that actually is as important that diabetes log and all of the synthesis that comes together?
I am wondering how can we introduce this idea of the velocity of disease into measurement and can we supplement a snapshot or even bounded episodes of care assessments where a broader notion of a real lifetime perspective on the velocity of care? After all, all disease begins at birth. When does the episode begin? Well, somehow, somewhere along the way. I wonder if there is a longer view, if you have thoughts about measuring this notion of the velocity of care. I think that the transitions could actually be expanded to cover a lot of it if you were inclusive of your definition of transition or broaden the notion of an episode.
DR. RAPP: I do not think there is any limit to the timeframe. So far with our 30 day readmission and mortality we are at 30 days but you do not have to limit it to 30. You could go to 60, 120 or beyond. We can measure it at the population level. I think that is the first thing. What we can do at the population level is a lot easier than what we can do when we try to hold somebody accountable for that. The nature of value-based purchasing is you want to pay for better quality. We want to have better quality and that we could just measure whether we have got it. What are the outcomes that the patients are experiencing? We could figure out ways to do that.
The next step though from a policy standpoint that seems to be of interest is to somehow pay doctors, hospitals, and others differentially based on their quality. That is the challenge and that is why you have, I brought up the attribution issue that is pretty key. To what extent you have to weigh it, to what extent are they responsible for it. I have heard talk in Pennsylvania I believe implementing the AHRQ Ambulatory Sensitive Measures but toning it down and saying that you cannot be completely responsible doing it at the plan level. There are all kinds of issues but I think that attribution and the accountability are major policy issues that go beyond just trying to get a sense of what is going on at a particular geographic region.
DR. MIDDLETON: One quick follow up because you did not say yes or no. The flip side of this is not only the doctor facing side or the organization or the payer side but the flip side of this is the consumer facing part. What is a roadmap if you will for quality care for my mom to understand? What are the guardrails in which she can feel I am having safe care versus somehow I am out of bounds. I need to see my doctor or see another doctor. What are your thoughts on sort of the roadmap for quality from a very consumer point of view?
DR. RAPP: Personal views, I think that the patient definitely has to be involved in this equation. Being a physician myself I know that most medical care comes because the patient decides that they are going to go see somebody and they present whatever problem they present which could be big or little. Then the way that the health care system works is next thing the doctors will go see this person and go see that person.
I read an article recently about somebody coming into the emergency department room with herpes shingles of the eye and the doctor went in and I do not know if you read this but it was fascinating. I know what is wrong with me. I have got shingles. I need an antiviral and some steroids and boom I will get that pain medicine and I will get better. He goes into the emergency department and the emergency physician says, I agree with you 100 percent that is exactly what is wrong with you but you know it could be something else. Maybe we should have an ophthalmologist see you and the neurologist see you. So the doctor patient said, well okay, why not? So pretty soon the neurologist comes in and the ophthalmologist agrees with the diagnosis that is right. The neurologist says, well why don’t you get an MRI? They get the MRI read and say maybe it says something in the cavernous sinus. We should get a CAT scan. They get a CAT scan. Well, the CAT scan is normal, maybe we should repeat the MRI. The next day the final reading comes back well, that initial MRI was negative anyway.
For those of us that have been in health care I think that we can understand how those things happen. We talked about preferences and values and so forth but what is it in the system there that would counter that? If the patient says well, I do not want something terrible to happen. I do not want to have a stroke or whatever. The emergency physician says well, there is no benefit to me missing a diagnosis and I can be sure if I have got my coverage from these consultants that no matter what is wrong with him the neurologist agrees with me and the ophthalmologist says I am solid. The patient said –
These are the kinds of conundrums that I think exist that if you do not have the patient involved and the only levers that you try to work are the doctors and the hospitals and so forth I think that from my own view you are missing something and it will not ever get where we want to go.
DR. FITZMAURICE: You have a large portfolio of related quality measure programs and demonstration. I really appreciate you coming here and telling us about them. It is almost just overwhelming.
My question is what have you learned from your quality measure programs that helped to inform the value-based purchasing and to guide the data collection. What causes the hospital or physician group to improve its quality of care? Is it the confidential reporting? Is it the public reporting, is it not paying extra for never events? What causes change and what have you learned that guides your data collection?
DR. RAPP: Well I think the public reporting has a very significant impact. Hospitals will do whatever they can to try to improve that, both the process measures, the mortality they are kind of probably – they complain we are not telling them exactly what to do. Well, it is not our job probably to tell them exactly what to do. We can just tell them that their rates are different in terms of outcome.
Process measures, I think that we have learned that they get rapidly topped out. People figure out how to do them but that does not necessarily have that much to do with the overall outcome because there are too many other variable involved.
For physicians we have not gotten into the public reporting. Everything is confidential so far particularly at the individual level. I know that doctors are very concerned about it and I do believe that is an issue. I think there is a lot of reason to be but as a physician you have got your individual license and reputation and once that is gone you do not have anything anymore. I think on the physician side we would like to get the public report quality data but we, it would seem to me that one would want to start at the group level so you do not adversely impact the individual’s reputation and also the numbers.
I think public reporting is a very important driver. I do think that there has been a tremendous change in the views of the physicians and others as to whether that this is something that should take place and more accepting of it.
As far as how you can tie the money to it I think there is a lot more willingness to publically report information than there is actually to tie the money to it. Most of the proposals that you see in terms of saving money relate to well people do not report data and they get a disincentive or there are a bunch of neutrals. What we have not really figured out is that if you get these quality measures to have improved performance and so forth will that actually bring down the cost of health care. We have not figured out that one yet.
DR. CARR: Thank you very much. It was very much appreciated. We are going to break now for lunch and we will resume at 1:30.
Agenda Item: Meaningful measures of integration, population health and health status
DR. CARR: I would like to thank you for indulging us in our delay and invite you to step forward to help us understand better meaningful measures of integration, population health and health status.
DR. HARRIS: Thanks for having me today. I am not really sure who called me. I kind of pondered what value I could bring to you all. I have thought that perhaps there are a couple of things that those of us who are in the Healthy People business might have to offer. I hope so. I think in the end what we have to offer is a partnership over the next several years as we learn together about how to measure the life and the health status of Americans so that we can join in understanding how public health, population health, and clinical outcomes might be viewed together.
With that thought in mind, I am today going to talk with you today about the processes, some of the processes involved in Healthy People. A little bit about the conceptual framework that has been used and is being used for 2020. Then I am going to talk with you about the work of our group representing the health communication and health information technology objectives development part of Healthy People. Then a little bit about our conceptual framework because we are I think of a number of the topic area in Healthy People some of the most directly related to the kinds of things that you all are considering. Although, there are other groups that I would encourage you to discuss, or have these kinds of discussions with including the Access Group which is chaired by Tricia Trinite at AHRQ.
I am going to start by telling you a little bit about Healthy People. I assume you have heard about Healthy People. You may not know exactly what it does but I am going to talk with you about it from the advantage point of another effort to try to capture the essence of health at a national level and a sort of set of lofty terms but then get down to the rigor of developing measures, objectives that are measurable. It is that loftiness but grounded in rigor that I believe can offer you all some lessons learned from what we have been trying to do in Healthy People 2020.
First of all I want to say Healthy People is in its fourth decade so it has legs. Each ten years is really an opportunity to rethink what the priorities are, what the goals are, and obviously what the objectives will be for the next decade. It is something for you all to consider when you think about how overwhelming your own mission is to come up with meaningful measures. You do not have to get it right the first time because it is an iterative process. We are just doing the best that we can on each of the stages of our development.
Health People 2020, I am going to give you a little bit of insight about how it is going to be different from the other decades because I think that may be the most useful for you all. If you have questions about the past I will be happy to answer them.
Like the rest of 2020, the goals or the mission is pretty much the same. Instead of looking at health or health care at a micro system level it is really trying to look at it as national, nationwide kinds of objectives. That is meaningful in that it is not a federal set of goals. It is an effort to bring from the grassroots, the best ideas in the country about what the mission, what the goal, what the framework, and then ultimately what the effect should be. So they are national objectives not federal objectives and that is the engagement of the stakeholders. We have a forum just like you all do to help bring in public comment. We also have a pretty aggressive effort to bring public comment to the table.
Here is the timeline for 2020. As you see we are just about to launch the public stakeholder period after all of the objectives that have been reviewed by the federal interagency working group have been cleared. Next week these almost 2000 objectives will be launched out for public review. After that period we will have another opportunity to get public comment about those that we have developed and do one last round before it is cleared through the HHS process. It will be released next year, probably next December, maybe December 31st of 2010 to launch Healthy People 2020.
The 2020 Program is unique in all of the different versions of Healthy People in that it is not limiting the sets of objectives to conditions. That was not an easy thing to come about. For the first time, Healthy People is taking what we lovingly call an ecological perspective. That perspective is reflected in the context in which health occurs and where health takes place. That is not just in the clinic but you will see that the health services are one of a number of settings in which health happens or does not happen.
The determinants that have been recorded for Healthy People to date, and this is still a little bit up for grabs, there are some opportunities to redefine this a little bit. For the purposes of our discussion this is where we are in our deliberations. These determinants are health services, biology and genetics, individual behavior, social environment, and physical environment. All of these have in some way some impact in the health outcomes. The goals here as they are as of today, and I think they are pretty stable because they have had a lot of input, is really primarily about obtaining high-quality, longer lives in which people can get healthy and stay healthy.
I offer that to you as a goal that you all might want to consider too. I heard this morning, one of the reasons I wanted to come is to kind of get what is your language, what are your assumptions? Of course, as appropriate there is a lot about illness, conditions, and how do you do the best job you can to improve the quality of the way those conditions are managed?
Healthy People is really about preventing those conditions from happening in the first place. So you will see some different assumptions and different kinds of processes that are measured for achieving those sets of goals. In our particular objectives in health communication and health IT, our lofty goal is really to move us more toward a learning system. We view communication as a dynamic in which there is a series of interactions in which feedback is an important part of those interactions whether they are at the interpersonal level or at the system level, organizational, or state or federal level. We have we hope a patient-centered view but more specifically an interactional view of health in the discussion that we are going to have today, and with health delivery.
I am just going to tell you a little bit about the objectives that we in our group have developed and how they fit into this ecological model. Before I do that I will just give you a glimpse into the way we work in Healthy People. Each one of the topic areas whether it is heart disease or access or health communication and health information technology have working groups. Ours is made up of three members of – three of us make up the leadership of this working group, CDC and our office and Disease Prevention and Health Promotion which I lead with our team and health communication and the Office of the National Coordinator. We have tried to create an integrated view of health communication and health IT. The idea is that the processes, the interactions in a health care delivery system or any of these contexts are supported by the tools that the health IT offers. That is kind of our orientation going into this.
I am going to go quickly through the different kinds of – this is the list of individual behavior systems and the other kind of determinants in order to get you a little insight into the objectives that we have chosen to reflect important health communication and HIT objectives. I am going to tell you a little bit about their measurement.
Measurement across the board for Healthy People is pretty much survey data. I do not know if we have a lot to offer you on that. I am hoping that what we have to learn with you together is more of the conceptual basis of what we are doing.
Some of these have already been mentioned this morning. Health literacy is really an important element for us to measure. We have measured it for Healthy People 2010. That measure is no longer available so we are fishing for other measures for ways that we can measure improving health literacy. We would love to do that both from the population basis perspective but also from the systems basis like what are the systems doing to try and make it easier for people to understand the health and navigate the system?
A second objective that we associate with supporting individual behavior is the increase, the use of electronic personal health management tools and Paul you and your group helped us develop this perspective. For one thing, you all helped us really see that it is not about the technology. In other words, personal health records in some language but it really cannot be about the technology. We were really pleased in our office to learn that the people at ONC see it that way too even though they are technology focused. It is really about the interactions and about how the tools can support those interactions. As you will see we are very much interested in how this impacts the end use or the patient or the consumer, the citizen.
The third one is about the quality of health websites. As you know lots of people are going to the web for health information. We think that getting accurate, transparent, easy to use, accessible health information from the web is a meaningful way that people can get health information. Having access to the internet is another important part of that access.
Social environment, that is just friends and family whether it is real geographical areas or it is in virtual social networking, we know that if you are isolated your health status suffers. The flip of that is also true that if you have someone who you feel supports you in your health it makes a dramatic difference. We want to measure the degree to which people have social support and are being helped on that with HINTS which is the Health Interview National Trends Survey from NCI.
On the physical environment there are lots of objectives that are I think more relevant from a number of other topic areas. Ours has to do with improving, increasing the quality of risk communication. That is a big deal at the CDC. Right now the H1N1 flu, how do you get the word out that fits everywhere you really need to get your shot? It is not a small, trivial kind of effort. We are hoping that we can improve the best practices around our ability to get those messages to the public.
In the area of biology and genetics, we are looking at an objective that really has to do with personalizing health information. That has to do with describing health information as you would prescribe medicine in a clinic. So the information prescription idea is one where we are hoping people will – that professionals will increase their willingness to prescribe reliable health information and guidance for their patients. We will be tracking that though the PEW Internet and Society Survey.
Biology and genetics, our contribution to that set of priorities is that we will hope to increase the personalized health guidance and some of that has been mentioned here. Personalized population health is a direction that we would like to go. We had a hearing of our own on that and it was very helpful for us to see the direction that we need to go and really want to track how people want to feel, how personalized their information is including getting the genetic profile and marking their progress toward health care and having health care defined and informed by some ways by that information.
Health services, this may be the one that you all are most interested in and obviously we have a number of objectives that relate to this. Improving patient provider communication is one that is very important to us. It is a placeholder for a lot of issues that we share with you all that is it is hidden here a little bit but we want to look at that in terms of how patients can be a part of the team. Not that any time there is separation between the patient and the provider we want to try to eliminate those walls. We are hoping to create some measures that get at that individuals perception of whether they feel like they are a part of the decision making process of their team or is there even a team.
We also would like to know are they feeling like they are part of the coordinated care around them. We are thinking it is not just enough to have coordinated care but the patient should feel like they are a part of that process as well. It is our aspiration to be able to measure that.
The second final objectives are objectives that are coming out of the Office of the National Coordinator although we have worked on all of them together specifically these two and the personal health record one.
The increase the use of health IT to improve individual population health and the final one increase of advanced connectivity to improve individual and population health are two objectives that will be operationalized according to meaningful use that will be determined by the rulings that are being generated by CMS and OMC today.
Those are kind of the top level view of the objectives. We think those are many of the important objectives that help us think about what together could create a learning system. I am going to tell you in a couple minutes and then I am going to close and welcome your feedback.
One of the takeaways I would like for you to have is that when we think of communication we do not think of it only as public affairs or social marketing although that is often an important part of the communication process. We have looked at communication more as I mentioned before as a series of interactions between systems. It is the in between systems where decisions are made and where change happens. To know, to really be able to use this as a unit of analysis and to be able to capture the interactions at different levels helps us to see what is the quality of the feedback that people are giving. Why are they giving feedback whether it is provider to provider, on a team, or provider to patient? Perhaps patient to patient when they are in a group visit and they go out into the community and provide support for themselves in a social network. We are really interested in this unit of analysis with feedback as kind of the important mechanism where learning happens.
I want to offer you one particular model. Some of you may be familiar with the Care model. We have seen this as a really promising direction to help inform us in the way that we think about productive interactions. As you will see at the bottom of the chart for those who are not familiar, productive interactions from Ed Wagner’s perspective is really where we all want to get. If we can according to the Care model continually have these productive interactions with between an informed, activated patient and prepare a proactive team then we really have something to work with. In our view, we really have a learning system that if you can improve the quality of the learning, then you really are we believe, at the heart of the kind of system that can make the kind of adjustments and adaptations to the challenges on a continual basis. That is why we think that the health communication and the health IT perspective we bring to the party may offer you all something to work with us on as you contemplate the same kinds of issues. Here I am just going to lay out for you some of the assumptions we have about productive interactions and how they offer we believe the promise for a meaningful set of measures.
Now we are right in the middle of our effort to finalize the measurement of our objective. These are not cut in stone. We really do expect during the public comment period that there will be some useful perhaps additions to these objectives. We hope some efforts to help us measure them. We would really, really like to have to compliment our survey-based data some clinical data, that can together illustrate a bigger picture of how things are going at the national level in terms of health status of Americans as well as how are the processes that are either helping or making that creating some challenges for that to happen. How are they working?
We would really like to join with you all and continue conversations. If you think that is an appropriate way that we could learn together – as you see this last sentence, it was so clumsy and I thought, I should really change this sentence but it really reflects where we are. It is just sort of a jumble of terms we want to make sure that these terms are in there. That it is really about the interpersonal trust that happens in interpersonal relationships. It is also the trust that happens at the larger system level. Trust is really important even though it is not necessarily part of health information technology.
We see the concepts from those personal interactions as really critical as well as the more administrative care coordination teamwork and just data sharing interactions. They need to have that human quality. Some of the criteria that we all have come to understand as being vital to our own well being to be incorporated into those.
As I said it is sort of lofty. A little bit extract but our bottom line is we have to have the measures so we are looking right now to those of you who are also looking at measures, that is why I brought three fellows and an intern so that we can learn about the language and the perspectives that you are taking. I welcome further discussions about this and I really appreciate you inviting me here.
DR. CARR: Thanks, that was great, very clear and refreshing. I have a question. In the measures that we have been talking about this morning or yesterday and today, we have it linked to an accountable party, a physician, a group, a hospital. Who do you see as the accountable party when you see improvement or lack of improvement? Who do you turn to?
DR. HARRIS: We struggle with that on health literacy as a starting place because the measure that we had for health literacy before was really from a population perspective where nobody was accountable in our way of measuring it. We would really like to have measures in which providers have some accountability for changing the way they provide services such that their protocols, their processes are designed to help people really navigate the system.
We are trying to have it both ways a little bit. If we could get the measures to do that that is what we would do. Some of the responsibility is on the citizen for becoming more literate and I am using this as an example, in my opinion, a lot of this is just making the system more accountable so that the design, whether it is interactions, websites, or the processes themselves.
DR. CARR: Just to follow up on that. So you assess this based on surveys. Then if something got better, do you know why it got better?
DR. HARRIS: Well that is why we would like to program – exactly.
The social determinants approach is one big step towards getting there that we can kind of identify what in general may be more or less affecting the difference but you know with survey data you really cannot do that.
DR. CARR: Let me go around the room. Mike Fitzmaurice –
DR. FITZMAURICE: Linda that was a great summary of what you have been working on for the past two or three years maybe a half of a lifetime. I am wondering, there are measures being developed. We have had quality measures from CMS today. We are experienced with meaningful use measures. I wonder if some of those measures will fit into what you are trying to measure so that you kind of do double duty or do piggybacking. I am thinking particularly of the number of health services, health IT and communication objective and measures there.
They might be simple like do you have problem list? Do you have a medication list? Do you have a personal health record? Things that are the stepping stones to achieving what you want.
DR. HARRIS: Absolutely, when we look at the list of meaningful use and we talked with the other Quality Subcommittee, as it looks like it may be coming about, particularly the population health and interacting with families and patients. These are the areas that are ripe for better understanding the common ground, sweet spot between population health and health service delivery, between personal health and population health. These are the kinds of things that we have really though a lot about.
The personal health management I think is really going to be an important one because it could be a lot of different things. We have not defined that yet. It is an exciting time to help define it. One of the reasons that we have not settled on anything yet is because it could be a social networking effort. It does not have to be a record. If it is not a record it can be sort of anything. We are hoping that – we are working with PEW on that. The PEW Internet and Society folks are really close to the ground on that. They see the social life of information as very real. We are going to be looking at that with them.
DR CARR: Larry.
DR. GREEN: A brief editorial and then I have got two very specific questions. I think Linda’s presentation really helped us a lot more than I realized that it was going to around this measure independent of conditions. We really largely track ourselves and our conversations around thinking about a disease. I am so sick about talking about diabetes. We have this template model that we keep using and it is disease-oriented. She helps us start thinking about measures that are independent of conditions and I think this is really important to us. It is fueled into practicality for me by work I know about over the last or six or seven years where you try to get small practices to address unhealthy behaviors and the pre-determinates of premature mortality, the grid you show, where we know that it is doable because it has been done. You can touch it, you can see it and you have these hookups between what goes on in the community, what goes on in the practice with assessments linked through website generated stuff that comes in for a visit that gets there ahead of time that leads to responses and identification of risk leads to recommendations.
That is a prescription for health as opposed to a prescription for a drug or whatever. Then there can be feedback groups that occur asynchronously and through community agencies. You got into that talking about your feedback. So that sets up my first question is what is your thinking about measures of feedback that a person gets about their health? How would you know that the person was getting feedback? How could you detect it? How would you know that it happened in some way or another?
DR. HARRIS: Well you know there is an interesting sort of theme about episodes. I notice that episodes are very provider-focused in the discussion that I heard this morning. I understand the attempt to be objective and that that is important. There is actually quite a bit of research to suggest that people think episodically in terms of patterns of their interactions. In other words, they can recognize an argument. They can recognize joking. They can recognize the beginning and the ending of their sense of whether they got better or not. People can actually recognize reliably, predictably their own episodes. I would suggest that that is another way to go, to think about not just whether you got feedback but whether this was a quality interaction from a patient’s perspective or episode or however you want to think about that but the patterns of interactions that I think make for a useful unit of analysis and what I am saying is that people can pretty reliably give us what that episode means for them. We can ask them, did you get good feedback from your provider overall rather than one – the way it is phrased now is during your last visit. I think people are more capable than that. I think they can give us more robust answers than that.
DR. GREEN: Thank you but let’s drill down into this just a bit. Let’s for the sake of this question assume that health is won and lost in the community not in the health care system, that unhealthy behaviors kill us before our time. To change behavior requires constant feedback and reinforcement. That is the type of feedback that I am wondering about you are thinking about how you would measure whether or not individuals are getting let’s call it reinforcement, for moving in the correct direction according to the Care model for the chronic disease or for promoting their health. How would you notice what they were getting?
DR. HARRIS: One way you would know is by measuring the kind of personal health management tools people have. If a personal health record is designed with feedback in it that tells you at least people who have access to the kinds of personal health management tools that will provide the kind of feedback that they need versus tools that can pacify patients. So access to those kinds of tools is one way to measure it.
DR. GREEN: There is a list of those tools?
DR. HARRIS: There are personal health records that are being developed and include those kinds of tools. They are not just a record, it is for example, the use of cell phones to provide the kind of reminders that providers can outsource to those who are developing or supporting those personal health records.
DR. GREEN: Actually this is analogous to what we heard from Medicare about this. Where is the functional assessment and the status of the patient down at the nursing home after discharge or before they leave the hospital? This is analogous, that sort of proposition that could have items on it that should be able to be detected, yet this is much easier. You said something, you made a comment, you said but that measure is no longer available. What is that about?
DR. HARRIS: The Department of Education was measuring health literacy because they were interested in literacy so because health literacy changes so little they are only going to measure it every decade. That is not good enough for us we have to have – which is kind of sad.
But Larry you know I think we have – about your question about the feedback, this is the kind of thing I think we need to learn together on. I think that Wagner is very interested in this. Others are interested in this. I think the point of connection that we make between Healthy People and what you all were doing, you all could maybe identify them as well as I could, where do we learn together to really capture the essence of what we are trying to get at?
DR. GREEN: I will finish I promise Justine. I would like to create a memory in our collective minds for further discussion about meaningful measures here by creating a specific example. Long ago and far away when we wanted nutritional measures that were meaningful and we went to the field, we had the sort of discussion yesterday afternoon that dragged out over a year and a half, we got all sorts of consultative help and we found more than 7000 measures, nutritional measures. Skip a lot of intervening territory, cut to the chase, at the end of the day this question – in a typical day how many servings of fruits and vegetables do you eat? It started as part of Alice Ammerman’s Start the Conversation Questionnaire down in North Carolina just to get into a discussion of diet. It turns out you can use that sucker to screen entire practice populations. It can be answered for every one over the age of two. Once you screen them you can actually scale it, you can predict who has unhealthy diets and who does not. You can use it as a follow up measure and you can scale it up to your whole population and know whether the population is generally moving toward a healthier diet or not, one question, a five point scale.
I want to put that on the table as an illustration of what I view as a really meaningful measure related to health. It flunks a lot of the criteria that we were talking about yesterday afternoon in terms of its development and how we got there. If you talk to people, just try to eat better, if you talk to people in the health care delivery system who is trying to work with them they love this sucker. It means something to them. I will be quite now I promise.
DR. CARR: We always welcome your input. It is very thought provoking.
Truly this was a great thing to end up on because I think it brings us back to prevention and balances the equation.
DR. TANG: I just have one question sort of involved to what Larry said. As you mentioned, you have 2000 measure out for public comment. Is there a thought about condensing that some?
DR. HARRIS: I am really torn about to be the perfect fed or to tell you the truth. I think the truth is everybody wants that. Nobody has stepped up to the plate to do it. So I think it is really going to be an important thing for people to do. I am hoping that will happen.
DR. TANG: To accept that these are survey-based which is I think what you said and to take advantage of the tools and the kind of connectiveness with everyone. It seems like if you did have a survey tool that had 20 or 50, one more people would even take it once and you could convince people to take it multiple times because then you could present things that could appeal to them and that they could track. It might be susceptible to advice on changing behavior and then watch the change. It almost seems self defeating to every stakeholder’s purpose to have 2000 since no one, absolutely no one will benefit in a sense. I am sure you have had this discussion but maybe what can we do to help?
DR. HARRIS: Well if you want to take that on.
DR. TANG: It is not to reduce it but now that you have new tools where you could consider even having self-administered it would only be contemplated if it were really digested.
DR. HARRIS: But the challenge is to prioritize. It is to come up with the 10 most important measure. That is what we have not gotten anybody to step up to the plate to do. I mean if you can do that then you are right, we have the tools. It is the courage or the sense of authority to actually come up to prioritize out of 2000 and thousands of stakeholders who are clinging to each set of objectives.
DR. TANG: Well sometimes people change. In the meaningful use world we just think back on the NPP process. I mean you can pick a number of processes but there are still come contemporary health issues that – so maybe one compromise is you have got a decade. Divide it up into four two and a half year cycles and then at least you are starting with 500 and then keep whittling it down.
DR. HARRIS: Well you know I really think that – my bottom line is that there is a lot of opportunity for cross fertilization among the advisory committees to the Secretary. There is no reason why you all should not sit down with Jonathan Fielding who is chairing the Healthy People and have this stock kind of discussion. If you all do not do it I am really not sure, not you personally, but the people who are advising the Secretary are in the position to take on these kinds of issues and sometimes somebody from outside your own tribe can make that happen by just suggesting it and taking a little bit of a heat that you do not really experience so much because it is not your stakeholder group. That is really what I am suggesting to you all as a result of my coming here and spending a day with you. There is no reason why this should be siloed kind of exercises.
DR. EISENBERG: Hi, this is Floyd Eisenberg and I have joined the call. Can I make a comment? I think that one of the things that might help this effort is at National Quality Forum we do have a set of priorities set by the National Priorities Partnership and part of our next step is to have Tom Valic(?) and Karen Adams working with the NCP goals plans to sit down with Healthy People 2020 to help coordinate how we can work across the six priorities and I guess your 2000 measures, maybe there are more goals than measures so to figure out how to work this through and to coordinate. I think that will help.
DR. HARRIS: That is right there has been some efforts and I did not mean to be dismissive of the efforts to do this. It is who is going to adopt which set of efforts to prioritize; IOM has offered some as well.
DR. CARR: Floyd thank you. I am glad you are online. Are you ready?
DR. EISENBERG: Yes, I do not have a whole lot to present and I apologize that I do not have slides but I can give a bit of an overview of what we are doing at the NQF in order to move towards the retooling and to move forward on some of these areas that were discussed. Is it okay to begin?
DR. CARR: Please, yes.
DR. EISENBERG: The National Priorities Partnership, I think Helen Burstin presented some of the goals yesterday. They are really patient and family engagement, population health which includes preventive healthy living, and community index measurement, safety care coordination, end of life care, and overviews. There are groups being brought together over the next several months to year to call for measures in these areas. Some of the Healthy People 2020 may fit right into this. In the process of our call for measures what we are trying to do at this point is to encourage use of available electronic data. Some of this I think may need some research. For instance, how to measure social networking that shows engagement and education of families. How does the PHR use it? Having it with certain functions is one thing but how do we know the components are used for education or whatever we are looking for and to use what. Some of that is what was discussed yesterday as the quality data set and looking for the electronic information does address some of these issues. We are trying how to best coordinate that into the measures from the electronic data stream. At the moment what we are doing is we took the 17 measures that are endorsed that map directly to the policy committee areas for measurement and an additional somewhere around 53 measures that were requested through CMS to have them retooled and we are in progress for the contracting of having that done so that we can see all of them address the appropriate information in electronic data. We expect that will be done, the retooling by March. So they will be available for 2011.
We are also looking forward to adding a clinical decision support element to the quality dataset and a coordination of care element around plans of care so that we are identifying the appropriate information to measure for the future.
I do not have a lot more to discuss at this point. I was a late addition to the panel. I am not as quick as Blackford to create a set of slides as yesterday. I am free to discuss what you like to learn about.
DR. CARR: Can you say a bit more about the quality dataset? A little more detail about what is in it or what is your vision to be in it?
DR. EISENBERG: Sure, the quality dataset framework starts with the data element which is a concept that I am looking for something about a disease or a condition. I am looking for communication with the patient or I am looking for communication actually. We add to that communication, with whom as I use that example, and that makes it a data type. So communication to a patient, communication from a patient, each is a different data type. What communication I am looking for is represented by – it might be I just need to know I communicated. It might be I need to communicate about a specific subject and that subject represented by a set of codes that says, this defines the subject that I am looking for but communication with this patient on this subject.
What we have done is we have a set of terms around communication, so communication to a patient to and from another clinical care provider. We have almost any concept that you could think of for medication. Medications are prescribed, they are administered, they are dispensed, they are declined for laboratory studies and then they are ordered, they are performed, they are resulted and if resulted a value. All of the information about a medication such as the attributes such as dose and frequency come along with that information.
I apologize. I could have shown you a whole list of, the whole set of data types. What we did try to do is address existing areas in the medical records with all of those types and also new areas that we would look for such as functional status, patient – I am sorry I am thinking satisfaction there was another word we use for that, care experience.
What we have done is look for where in an electronic model of information that information would be found. A lot of that work has occurred in HITSB identifying for each of those elements where that kind of information would be shared if it was sent from one EHR to another in a message or in a document. So in a CCD or in an HR7 message what information represents that data type? That then becomes the translation of what is in the EHR to the information needed for quality or clinical care. Does that help?
DR. CARR: Yes, and actually this gets back to what Bill Scanlon was saying about having a repository of data elements but then with those elements and you know where they are then you can query how often something happened or that it happened or what the result was.
DR. EISENBERG: Right and that is exactly what we are looking for is so now that we have the framework now it is the issue of implementing it so we have multiple data elements that can be reused either for clinical care or assessing the care that was delivered through measurement or through data mining and also for clinical decisions support to determine if a next step is necessary and if so what.
This is in a sense a database of elements to be used for that. Understanding this will in time grow and needs to be maintained and that is part of the structure that we are trying to set up now.
DR. CARR: But does this also become the blueprint for the vendors in terms of –
DR. EISENBERG: It does. It becomes the blueprint – now we do hear from vendors, and I would be interested in the Committee’s comment on that, that they are concerned that if the data elements or this is prescribed exactly how they represent everything in each of their products they all look the same and they will all be commodities. They feel that they can provide better innovation if they are given some leeway to improve the flow within their own product as long as they know what part of that flow maps to and connects to the information that is required for that data element.
We have created a concept more as – and I will use the Rosetta Stone concept that through the using of data elements helps work with any EHR and however they represented it, the same information so that it can be used.
So what I am interested in is does that make sense or does the Committee feel there needs to be more prescription to what actually sits in the EHR?
DR. CARR: They do not know.
DR. EISENBERG: Actually we do not either in NQF. I do want to disclose that I did work for a vendor it was actually a year ago, so I do understand that perspective of one to innovate. I think there is some need there. I think there is probably a balance and that will be sorted out in time but at least having the standard types of elements and the standard list of them and the ability to access them will help move all of this forward which ever direction that takes.
DR. CARR: Bill.
DR. SCANLON: Let me make a rash comment since I am not a clinician and someone that is not directly involved with it. This notion that this standardization is holding back sort of innovation is kind of like saying innovation in word processing programs is held back by the fact that the spell checker works against English. That is the standard. There are so many other dimensions that you can think about for innovation and distinguish your products that I just think that argument needs to be ignored very quickly.
DR. CARR: Mike Fitzmaurice.
DR. FITZMAURICE: Bill probably said it better than I could. I was going to suggest that they compete on the ease and the flow of work of getting the information into the recording mechanisms or into the electronic health record but it all has to be recorded as apples not apples and oranges.
DR. EISENBERG: I actually appreciate both of you. I think when they – often vendors or the ones that I have spoken with and my impression is they listen to the discussion and they assume that the discussion is telling them they have to have a standard interface and a standard flow and all have the exact same questions in the same order as all of the others. I think the efficiency of workflow is what vendors can compete on and can innovate on. The data itself needs to be standardized.
DR. TANG: I guess I am still having trouble even understanding what they are objecting to.
DR. EISENBERG: Sometimes I have similar concerns Paul. I guess we would have to have the vendors in the room to –
DR. TANG: I guess I am very much with what Bill said. Maybe the world just has to move forward without them.
DR. EISENBERG: I will not argue that. I did have one say to me if they wanted to create their problem list dynamically from all observations, the value of these observations, rather than have a separate list so every time a physician or a nurse or whomever wanted to see a problem list that was created and available for view. They want that ability. I am not sure if that works, well I cannot kind of understand that concept too well.
DR. TANG: I think it is fine for a list of states that made up the scenario that they can suggest to the physician in this case to put something on the problem list. The problem does belong to the health care professional. There is still going to be and is needed a problem list. It just really sounds like it is taking a lot of effort to just not do it and I think we ought to just move on and say it has got to be done.
DR EISENBERG: Actually that is the direction that we have taken is just move ahead with the dataset and knowing that that is needed and not delaying because of concerns about innovation.
DR. CARR: I think that concludes it. Floyd thank you again for your flexibility and for you insights. We appreciate it very much.
DR. HARRIS: It ties together one of the things that we were talking about and that is I would love to hear you all reflect on this for a second. One of the standards of the objectives that we have is about quality health sites. It also refers to a standardized interface; it does not have to be a website, to improve health literacy. Should that be designed into, instead of that being a requirement, should that be a part of the standardization of the tools that we are making available for patients or maybe providers or maybe intermediaries?
That is just the kind of discussion I think that would be fruitful for us to engage in together. It is certainly one of our important priorities and I do not know that it has been a part of your discussion this morning.
DR. TANG: We had the discussion on disparities and so the disparities that we can measure and that certainly can include language and health literacy. Eventually we have to take a lot of time right now, and that is sort of what we asked the earlier panel, with respect on trying to measure and measure precisely with more granularity. That should prompt us to now figure out how to act on those things and deliver. As an example, there is a meaningful use requirement that says patient specific educational materials. That could be pretty broad or it could become more stringent over time. I am not forecasting the future I am just saying that you can imagine that to be patient specific it would have to be in the language of the patient. Maybe it has to be adjusted to the health literacy, it maybe culturally sensitive, a number of things.
Those are I think the important ways that vendors can help innovate what we do more tailored to an individual.
Agenda Item: Summary, Discussion & Next Steps
DR. CARR: Okay, I think that we have about 20 minutes before we break to organize or sort of categorize thoughts. Fortunately we have Susan here who is working on this but why don’t we start with that? So Paul why don’t you take the lead?
DR. TANG: I think the hearing has been productive in the sense that we have learned a lot of information about the current activities. I think what we expressed in the beginning of this morning was that it is not clear and it is probably accurate to say that there is not any overarching strategy or overarching framework to move these measures into what we think of as a new era. The new era is all of the sudden there is a richer set of data that will become available. There is a richer set of tools to make it displayed to people who could be influenced by it. One of the points that I think Carolyn brought up is it would be really nice if this was bidirectional, that we could use some of the data that is analyzed in mind and put back in front of the people who are effecting every day decisions.
In my mind, in her call for a killer app, I think that is almost a killer app and I think Larry said something similar. That kind of information would influence the very next person I saw. I think there is a real opportunity. I am not sure it was necessarily expressed by the folks in the trenches right now but maybe that is where we can contribute. That is what are the overarching goals, vision, and whether there needs to be a framework and whether there needs to be some kind of coordinating or hearing kind of group that helps guide development of measures that are more meaningful to the providers, the patients, and consumers not only for consumption for the way it is now. When it is so late, which is usually one to two years late, it is almost not useful to anybody but put to use by certain data consumers.
DR. SCANLON: I guess I will react to that killer app in a second but I also think I have a different killer app that I worry about and I think Carolyn also included it in her list too which is in some respects the health care system and the fact that we have health reform on the horizon. Even without it we are spending $2,500,000,000,000 and we are really worried about where that is going and what we are getting for it. The question is what can we do about that? How do we leverage information to a make a difference there? I mean after all the IT that we are getting is being paid for to a great extent with public funds. There is that aspect of it.
I think there is a lot that is feasible. We should not be deterred sort of in any way. The killer app in terms of feedback – two weeks I made a mistake on the internet trying to order something with my VISA card and my phone rang within five minutes saying did you really try to do this? It was actually the wrong expiration date and the card got rejected and they wanted to know if somebody was using the card.
This is like within the capacity of current technology there is no issue that things can be done. The information – my version of this is that we extend the building blocks to the payers and they can give feedback so that if the Medicare program gets information from their claims about the services being provided there is no reason why within a day or within an hour information in an aggregated for cannot go back to the provider. I mean that is just a function of current IT capacity mechanics. It does not exist at CMS but can exist at CMS. That is the kind of thing that we need to think about. I really believe that the building of a database is key much more than the current measure because I feel like the current measure we are still working on incredibly hard to make them richer and that if we get hung up on what it takes to build them we are going to end up having even more complaints from vendors because they are going to be continuously saying, wait a minute, yesterday you told me this is what you wanted and now you are telling me this. There is a certain legitimacy to that but we have to overcome that by kind of being able to build this kind of Swiss army knife of data so to speak. I think all of these things are possible and we need to push forward on them.
This Committee has got a very valuable potential role in this because we are the HIPAA Committee. There is a potential linkage between these information flows that we may want and HIPAA. We are also sort of a very good representative of the privacy community. That intersection with us not even identifying the objective that intersection in terms of the meaning and what the risks are et cetera are can provide very important advice for the Secretary. I hope that we move forward in that and try to bring together not just what we think about here in the Quality Committee or the Populations Committee but also what our standards and our privacy sort of cuts across this Committee as well.
DR. TANG: I can piggyback a little bit on one of the threats which are our responsibility and our opportunity to give advice to the Secretary or at least HHS. As Linda mentioned as far as the fact with the Healthy People and of course we are a factor that is very related to the HIT Policy and Standards. I think a lot of us have talked about how meaningful use is becoming a very forceful tail that is wagging a much bigger dog that is part of the health reform and that timing means everything. Just like we have pushed the measure developers to a point, this is a real good opportunity to get some good measures out there.
I think we have a moment in time also with respect to the Meaningful Use in 2013 and beyond there. Still the 2011 is open for public comment in December. To the extent that we want some of this information on meaningful measures which we picked up from the meaningful use phrase to have an effect, it seems like we need to get our advice, our letter out – I mean it would be idealistic to say November but when is our next meeting after that, February that is actually too late because the public comment will be open.
DR. CARR: I think we should absolutely aim for November.
DR. TANG: That could be very potent. It will definitely go into the public on 2011. It will also be forwarded to the coming 2013 deliberations but that is how we would be coming in. I think that we have drawn certain conclusions. We have talked about it offline that could be very potent and important to this whole move in this direction. So that is the challenge to ourselves I think to take this.
DR. CARR: So are you saying that there would be value in taking the meaningful use proposal and intersect that with what we heard?
DR. TANG: That is one way HIT policy could take, maybe the other way is we can digest what we think are measures that can be meaningful with respect to measuring the health system and influencing it’s direction in health reform. The Policy Committee can wrap that or CMS can wrap that into the whole meaningful use construct.
DR. MIDDLETON: The idea of actually – the occasional interfacing of the FACAs was extremely interesting for a full host of reasons. It seems natural just from a management perspective to have those kinds of committees. You know talk to each other periodically. I am sure it would lead to higher quality and perhaps more interdigitating advice to the Secretary. There might be a recommendation regardless of the current effort; there should be a recommendation in general.
DR. TANG: I was going to pick up that and easily volunteer Justine to do backup.
DR. CARR: Okay, next steps. I know I for one kind of would like to reflect a bit more on this. I think that we have heard some important themes today. I think perhaps if we could each list ten important themes and kind of send them to all including Susan, I think that would be a helpful way of us saying what were the things that we all heard.
DR. TANG: And then from that if we could lump them into five categories then we could start saying something rather than –
DR. CARR: That was my – I tee up the lumping by splitting. I make the elements like Bill and then I roll it up.
DR. GREEN: Justine, do you have in your mind a title of the letter? If you throw a title forward our themes will follow.
DR. TANG: So that would be our recommendation for measures that would meaningfully impact health reform.
DR. SCANLON: How about achieving the measures because I think it is premature to say that we have the measures. I think what is critical is the process and how we are going to get to the measures.
DR. CARR: Does it impact health reform or reform health?
DR. TANG: So the title at one point has to say, reaffirming the status quo will actually get in the way of health reform. Actually I think I would delete that one because it was my no measure, no mission. If the payment is now going to be on measures then truly we have no measure, no mission, no measure, no money. That is how crucial what we measure –
DR. CARR: No outcome, no income.
I guess we will get to the themes but I know I for one was struck by the disparity in a sense of urgent action. I heard some great ideas today which over the decade to come make come to fruition. I also heard some very concise, incisive, ask one question and trigger a meaningful action. I think that in the moment concept is true. I think timeliness is really an undercurrent in all of this. Timeliness for the physician to see the results in the moment, timeliness for us to find the one thing that will take and make us 25 percent better as opposed to taking 25 years to make us 26 percent better.
When is our meeting? November 17th? I have it right here.
DR. TANG: So if we want something to submit into the public comment we have to have it approved –
DR. SCANLON: When are the rights going to be released? It is in December right?
DR. CARR: We can approve it from the Subcommittee and then – well our November meeting is the 19th and 20th of November.
DR. SCANLON: I guess the issue of approving it would have to be public notice if this was going to happen with Paul it would have to be open in a public meeting.
PARTICIPANTS: (remarks off microphone.)
DR. CARR: Well I think that, anyway we have had calls where we have had to work on – I think the products will be transparent but I think the alignment of our thinking, we will be talking about everything that was public record and in the transcript today. It is a question of assembling it.
I actually think that we need to get our concepts that are the most urgent concepts to be heard out by the 19th and that maybe we have a list and a brief executive summary. Perhaps we then want to have a more in depth letter or comment about taking it to another level. I think we definitely want to have a distinct message ready for November. I think that we can do this on conference call. I would say the top ten most important messages that you heard coming out of this. Maybe what you thought after what you heard and then if we can circulate them and then Cynthia if you could set up a call in the next say 10 days -
DR. SCANLON: One of the things that I think was apparent yesterday and Harry’s communication as well in the topic today, is there exists a leadership vacuum in getting this done. Maybe a way of putting that is governance and accountability around this. I think that there are a lot of people trying to do really good things. I know that is the case and doing thoughtful things and many of them are actually collaborating and working together. I mean yesterday we had two of the chairs of the NQF Initiative and Helen Burstin talking about – they were there and working together. This urgency and the timeline requires I think, a different sort of framework for leadership and governance that does not exist today.
DR. CARR: So we have got the 10 things, 10 thoughts. Let’s say in the next week and try to be specific with the measures. In seven days and I will start off an email to all so we can just respond to all.
I just want to express my thanks to everyone for their wonderful participation. Of course, thank you especially to Matt for working so hard on this and also to our able staff for tolerating our last minute changes in so many ways so thank you. I think we are done.
(Whereupon the meeting adjourned at 2:50 p.m.)