you know given limited resources to think about that a little bit more? >> that's a good question. i'll give you my pitch on the diabetes prevention program. so here -- we have a population of 80 million people nationally that are prediabetic. we have a program that we know through ten years of clinical trial follow-ups that has accumulative reduction in incidence of diabetes of 34%. it works at a point in time, a ten-year follow-up study that shows over time we can reduce it. united health group and ymcas have put these into place in 25 states. we can reduce weight by 5% to 7%. we can reduce incidents of diabetes in a short period of time by 58. for older populations 71%. that program could be scaled nationally in the next 12 to 18 months for $80 million. not "b," "m." why in the world don't we do that out of the public health

fund? that's something that is an investment that we should do, build that one simple program in nationally, have it available so that small employers could use it medicare patients could be referred to it, and exchanges, plans in exchange could refer patients to this. now that's a simple example of something we should just be doing because we know it works. i guess my point of saying that is that, we have a whole variety of interventions that would target these programs that i've talked about that we have years of data to show that they work, transitional care models, diabetes prevention program. we need to flip the switch here and get into implementation mode, not pilot project mode. we're not going to pilot project ourselves into a solution here.

i mean, we need to sort of take things that we know that work, target them, to at-risk populations, and we could make an enormous difference. >> that was my point, it's not doing pa more pilots it's about getting package of services that works to people at highest risk and certain parts of the country. >> that would be great. i live in the obesity triangle. if you take the cdc, cdc data on obesity rates over time, looking at changes and diabetes preference, they're the same charts. we have things that we can do right now that would make a difference. you know we just need, as i said, flip the switch and focus on implementation and you can tell from what i'm saying i have pilot fatigue. sure, we need more information and we need to pilot other different projects but we have so much data on programs that we already know that work, that we should just implement and bill into how we do business in the exchanges. if you think about on the

exchange side something that we're not talking about is that, in the definition of essential health benefits, we have in-patient, outpatient usual services but a component of certification for plans to be and exchanges prevention and care coordination. what do we mean by that? what are we certifying and asking plans to do in exchanges on prevention and care coordination? geez, there's really simple things that would make a lot of sense that we would hope plans would do, like transitional care models and lifestyle programs like the dpp. >> dan callahan then the reactor panel. >> one issue not touched on, how do we -- i'll take ken's example of the 70-year-old with all of the things wrong. talk about coordinating care. how do you assess care with multiorgan failure or multidiseases at same time?

we're very good at individual cases but a team of physicians together and trying to coordinate them, how do they assess the overall work and interaction? >> i'll put my m.d. hat on for a minute. ken, i think this is a great example of why having team-based compare, and if you look at some of the health systems that do, i think, a pretty good job of that, whether it's marshfield clinic or guisinger, where you are building teams to deal with multiple problems and treating patients holistically, is probably the best way to go with this. think about, take medicaid, a good example, even a medicare when we do care coordination a lot of care coordination segments off of care coordination into different buckets. you'll have behavioral health

care contracted out, pharmacy contracted out, acute care. you know dealing with a patient that has all of those problems. so even coordinated care sometimes and medicaid is not coordinated at all, fractured. to the extent that you continue to drive this towards payment reforms that really move us towards team-based care, that really engage patients for the whole range of medical problems is probably i think our best bet. it's not fee for service medicare, that's not how that program works at all. >> thank you. we're now going to move on to a series of a short presentations from our reactor panel. these are nonnuclear reactors but nonetheless very energized and we'll get through their presentations i know energetically so we have time for a break and then a beefy amount of time for a discussion. we're going to start with melanie bella who is leading those efforts at care coordination for the dual

eligible population. melanie? >> good morning, thank you. ed and others for inviting me to be here today. i was trying to figure out why i was invited and i sort of hit me in the face in an obvious way, dual eligibles are the poster children for high users of technology and high cost. and bruce and diane and others i think will get into the statistics around the prevalence of chronic disease. but the fragmentation between the two programs just as ser baits the use of technology and high costs driving the system. so i want to spend a couple of minutes on that theme of what is actionable and talk about a couple of actionable things that we're trying to do at cms to try to get a handle of the opportunity to improve quality and costs for this population. and the first is all about data. and until we understand better

this population, the subsets of the population, what's driving their care needs, what the utilization patterns are, by very discrete subpopulations, we're not going to be as effective as we can be in developing new models to improve care coordination, to improve transitions, to improve the use of long-term care services. so there's a few things we're doing in that regard. one is, i'm pleased to say that cms now has an integrated data set, so medicare and medicaid. it's not 2011 unfortunately but we're getting there over time and it's really going to help drive i think our analysis as well as those of others in the room and other interested stakeholders. the second is, we'll soon be releasing state profiles, so it will be a state by state look at the demographics, utilization, the costs, again, for from an integrated data set perspective of the individual whose are duly eligible in the state.

it's not meant to compare state-to-state, because we're not controlling for the differences in the medicaid program but again it will be a useful tool to get out there. another thing we're doing that i think is very relevant to this discussion is looking at the simplest way to call it is a pathway analysis. it's very different if you start on medicaid and age into medicare versus start medicare and have some financial decline that makes you medicaid eligible. types of care coordination models whether someone's care improved by care transitions. all of those things highly dependent on what drove a person to be in the program, what their care needs are, who they trust to get information about those care needs, all very different, depending on which "m" you start with. we're doing a lot of work in that area lastly, those who

researchers, enhancements to the chronic condition warehouse, we have conditions for diagnoses for serious mental illness, alcohol use, for intellectual and development disabilities and if we again are going to truly understand prevalence of chronic disease by subpopulations we have tonight add to diagnoses in the ccw, particularly those that are going to reflect things that medicare maybe hasn't looked at as medicaid has in the past. so that's a critical part of the effort. as part of our efforts to work with states in the arena, we have been focuses on making sure states have access to medicare data for care coordination purposes and tried to streamline a process abiding by confidential rules allows states to access to data. we have 22 state as that have received or in the process of receiving parts a and b, 20 states in the process of receiving part d. when i talk about demonstrations from our perspective, it's critical that states are requesting these data to show us

that they have an understanding of their population and they can tailor their interventions and demonstrations to the needs of those populations and they're heterogeneous care pathways. next thing i mention quickly, along again the theme of actionable, are demonstrations. and i appreciate ken's comments about i think pilot fatigue. we're getting all sorts of feedback on our demonstrations. one is, they're too big, we're move too fast and others telling us, boy, it's about time, can't you go quicker. i would say that certainly i understand the pilot fatigue. for this population we have not tested, there is modest paid for integrated improved coordinated care particularly that that bridges the behavioral health, long-term services and supports acute and primary. however, there are important components, diabetes prevention, we expect to those things where they are relevant for those populations in the demonstrations.

we have a state-based demonstration opportunity right now and that involves two models, one a capitated model, one is a managed fee for model. we had 26 states interested in pursuing one or both models at this point. some states targeting 2013 implementation date and others targeting 2014 date. i want to emphasize we expect to see care models and care teams and care plans tailored to the different needs of the populations and we've not done as good a job of that in the past as we need to. the needs of someone who is going -- the prototypical 80-year-old medicare patient is very different than someone under 65 whose needs are long-term care driven or someone who is in an institution. and so understanding again all of these varieties is a great opportunity for us to test in this -- in these new situations. and then i'm very excited the

other demonstration that we're doing is for dual eligible beneficiaries in nursing facilities there are about a million of them at any given time, avoidable hospitalizations is a critical opportunity for improvement here. the churn between hospital and nursing home largely driven by the misaligned financing of the two programs is actionable improvement in both quality and cost. cms study showed that 26% of hospitalization for duals were potentially avoidable and today's dollar that's about $8 billion and it's very poor care for patients obviously. we have a demonstration going on targeted at beneficiaries in nursing homes. in closing, i couldn't be a bigger fan of trying to develop evidence based models of care coordination and look agent prevention an area we have not been able to focus on are the preduals. so the folks 45 to 64 before they're coming on to medicare, there's a huge opportunity for us to do care coordination or medical homes or care management to improve utilization and the preference and intensity of the disease when they get on

medicare and those on medicare there's a lot to be doing to prevent decline on to medicaid. so far the financing and the incentives between two programs haven't supported that work and i'm hopeful that once we kind of get through dealing with the 9 million folks on the program we can shift attention to preduals and doing a much better job of managing i'd say the progression of folks to dual eligibility status. with that, i will close and say thank you again for being part of the panel. >> thanks very much, melanie. we're going to turn to joe new house. it's often asserted that the u.s. is an outlier in outspending. how big of an outlier are we really if we are? >> thanks, susan. this discussion somewhat reminds me of -- russia mount home. how many have seen it? it's a classic japanese movie and basically presents four different views of the same

reality. i think that's some of what we're hearing here. i noticed in the green book that you were handed when you walked in, there's the usual slide which i'm not going to show you on page 7 of the u.s. spends a lot more than everybody else which susan alluded to. what's less well appreciated, though ken mentioned it in passing, my first slide, is that -- how do i advance the slides? >> right hand. >> the -- what i've done here is look at annual growth rates per person in real health care spending over time. so this is almost 50 years. and the asterisks -- the g-7 -- by germany, italy, japan, because there's strange things

about their numbers, not just that they're different. germany had reunification, italy doesn't start until 1988 and most of the japanese bulge is in 1960s, when their economy was growing 11% a year. if i look at the other four, the u.s. actually is the highest but not by a lot. certainly not by nothing like the levels. and then i'd like to go on to say when we participated in the medicare trustees 75-year review, which you may think is a waste of time, but we were doing our civic duty and in projecting 75 years or even 10, for that mat, it's the growth rates that matter. it's the growth rates that are doing it to federal, state, and personal budgets. i just did some calculation over the weekend of the kaiser data

on average family premium against median income, 2009-2010, that went from 22% to 28%. so the average family premium, not out of pocket, so the family premium is now for on the average family insurance policy 28% of median income, which is, i fine, somewhat staggering number. so the inference i draw from that the rate of cost growth is going to slow down. i can't tell you how, but it is. nothing grows to the sky, is the saying in financial markets, and it's true here. so the u.s. and other countries -- the other countries are also not so different, at least the uk, france, canada. here the data by time, ken alluded to these two, i've broken things into decades since the '40s. and what you see is you see some variation around that average, but there's usually something happened in those decades that

departed a lot from the average. medicare, med cade, managed care introduction in the '90s, the recession in the last decade, but what's remarkable, to me, and the reason i put this up is to give some perspective, that this issue of cost growth is a common across countries and, b, has been going on for a very long time. so what i take from that is that while the u.s. certainly spends a lot more than everybody else, that must be something that u.s. specific. but the growth issue must be something that's common to countries and to decades. i take ken's point that, what's -- things may have changed over time in terms of what's driving but the growth issue must be

something that's common to countries and to decades. i take ken's point that, what's -- things may have changed over time in terms of what's driving this, but i still think it's important to keep in mind that this is not -- whatever is happening here is not necessarily a result of things that are specific to the u.s., which we naturally tend to get wrapped up in. the second point i wanted to make, which also has been alluded to, we've actually gotten something out of all of this growth in spending, you know, again the usual line is, we spend a lot more than

everybody else and we trail in life expectancy. but if i look at the change in spending against the change in life expectancy, never mind morbidity, things like cataracts and hip replacement, it's a remarkable change since 1970, which looking around the room most of us are old enough to remember, you know my students can't tell the difference between 1970 and 1870 but i can certainly. so what's quite remarkable is that life expectancy is like a lot of other things, subject to diminishing returns, that is, it gets harder and harder to get an increment. and we grew seven years, which

is a major achievement, in my mind, as did other countries. again, this is going on everywhere. no one can say how much is attributable to medical care. well, this is kind of a busy slide, as projected up there. this is a graph from a study of several trials. it's in your handout. and in -- about what accounted for the change in coronary heart disease. and the darker bar on the left is what these authors attributed to treatment. these are in various countries, not just the u.s. and the lighter bar is how much they've attributed to risk

factors but the risk factor part includes the better control of hypertension and better control of cholesterol, as well as the fall in smoking, which are the three big things in light part there. but the dark part is the higher tech treatments. so the -- and the -- it's the decline according to heart disease, it's almost all of the decline -- the gain in life expectancy in these years. we actually did get something for all of this. now that said, i think you know, what joe and ken have put

forward about what to do makes a great deal of sense. and what melanie has said makes a great deal of sense. but i would leave you with the notion that this is a rather -- a pervasive and long standing issue about cost. something is going to make it slow down, because it cannot continue at historical rates. but how that will happen i am not wise enough to know. >> okay. great. thanks so much, joe. we're going to move now to jim fasules of the american college of cardiology. jim, your chance to explain to us why all of this spending on cardiovascular disease inventions has been entirely worth it. >> i hope so. i want to thank ed and i want to thank mary ella, you're probably as much responsible for me being here as anybody else.

i'm not sure that's good until after the comments, okay? i guess we picked cardiovascular disease as the example or the model of chronic disease here. let's me just say that i'll go into that but go into the data and take the opportunity to say what a disease-specific association can do that's actionable in what we've been talking. right off the bat, one thing we haven't talked about cardiovascular disease also has an effect on the economy. a net loss to productivity of anywhere from $300 billion to $400 billion a year in lost productivity. also, though, what dr. newhouse's slide the last decade

a 30% reduction in mortality from cardiovascular disease, probably from the treatment. i'm going to just say, in the data aspect, we have to kind of be careful what we pick, what population we looked at, one slide looked at stenting versus medical maximum management and that really is in elective case, we're not talking about doing stents in the acute m.i. case, that's proven to be effective. a little bit also about the stents, whether the drug alluding or bare metal if you look at outcome as mortality, there's probably not a big difference. if you want to look at outcome as whether you need to have another procedure, then there is a difference. so what i'm getting at is the data, and getting the data also to the physicians is very important. one of the things we've done over the last 35 years is develop guidelines that look at the science and try to translate science into what you should be doing. recently actually taking guidelines and develop what's called appropriate use criteria,

and we use those appropriate use criteria in five recommendations in choosing wisely which has been mentioned. you can actually set up some continuous quality improvement aspects with the physician. and by giving the physician their data on what they're actually doing and what they see how they're doing against the norms, and whether they're using the procedures, the investigations, the imaging appropriately, and you can actually get them to improve their care. we found that just giving a dashboard of how the physician ranks against their fellows in their practice in the community and the region and nationally as far as where they score, for instance, on nuclear studies for their appropriate use criteria will decrease their use 15% to 20%. getting down into the range that we think should be about 8% of what we would label as inappropriate use. now, of course, you can't tell a physician not to do something because it still, i think it's been mentioned, medicine's still

an art as much as it is science. but practicing the best science that you can getting the data to the physician so they can make a better decision. part of that also with the appropriate use criteria and choosing wisely is also interaction with the patient. getting them to understand and if it's been mentioned the shared decision making where you're discussing with them ahead of time options. so take coronary artery disease an elective situation you can maximum medical management, you can have cabbage or coronary bypass or a stents placed. giving them a tool for the physician to see what fits in and what the patient wants as well and helping make that decision. i think that's how we've been looking at how do we decrease

the curve. now i would say that, actually we've discussed the cholesterol and management of coronary artery risk disease, disease risk factors, and mentioned california. we've looks at the data on both coronary artery bypass and the stenting for coronary artery disease and gone down all the last five years in california. if you look at cms data, there's a 10% reduction from last year -- actually the year before to last year for both cabbages and stenting and reduction also in imaging of cardiac imaging and i think that speaks towards the addressing of the risk factors. i'm glad everyone's looking at obesity and mary ellen knows that i've worked on obesity when i was in practice in arkansas. it gets to be quite hard. we were fuel actually on the commission that set up bmi on kids in school. imagine when you -- how do it, no one else knew the bmi at home, but we had 33% obesity in school-aged kids and doing measurements, taking vending machines out of school, et cetera we leveled that. now we didn't impact the 48%

smoking prevalence or tobacco use, i guess it was dipping as it was smoking. the other thing is, when you do action on data and one program i'll mention is the door to balloon, which means from when a patient with acute m.i. hits the e.r., the door to the e.r. until they're blowing up the balloon in the artery to open up the vessel, we know that if you do that under 90 minutes you save heart muscle and as a result you don't have as much congestive heart failure, so you reduce the morbidity. now we went from about a 50%, 60% in the e.r. to 90% of all e.r.s hitting that and hospitals hitting that number, and that probably saves two to three days of hospitalization and also puts the patient back to work after three to five days as opposed to what we mentioned when eisenhower had his heart attack and admitted to fitzsimmons army hospital he sat in the hospital

with little heparin and prayer. they have a little room for where he was at the hospital there now. but where do the savings go? the cardiologists didn't get paid anymore. here's program that actually had savings and we still haven't figured out whether they were -- the hospital got them through drg or the insurer got them. whatever we do with the models we have to look at what joe said, there has to be some incentives built in so that if you are doing this extra stuff or paying for this data, and finally the other thing we have the registries that we can actually track outcomes. maybe when the electronic health record gets to where it should be, we can do it that way. but data, disease specific, procedure specific outcomes over longitudinal time and that really tells us, someone mentioned in the trials, they nd