**Transcript of Cyberseminar**

**HERC Cost Effectiveness Analysis Course**

**How Can Cost Effectiveness Analysis Be Made More Relevant to U.S. Health Care?**

**Presenter Paul G. Barnett Ph.D**

**December 5, 2012**

**How Can Cost Effectiveness Analysis Be Made More Relevant to U.S. Health Care?**

**December 5, 2012**

Paul G. Barnett:  I added one slide to the talk, this first slide about excess cost in healthcare and so this is not in the handout that went to everyone, but I thought just to kind of motivate why do we care about cost effectiveness?  So the Institute of Medicine came out with an estimate that about 765 billion dollars a year in the healthcare system are wasted and this is something like three or four percent of the gross domestic product is lost in healthcare inefficiency.  We think that cost-effectiveness analysis has a lot to offer in terms of trying to reduce these excessive costs.  Certainly to help us identify unnecessary services, but also inefficiencies or ways in which we're spending money in which we're not really getting the value that we'd hoped for.  So that's not a trivial amount of expense.  We hear about certainly a lot more money than this being talked about as we worry about driving over the fiscal cliff the end of this month.  Keep in mind these are annual costs and what we've been talking about in Washington are ten- year costs, so these are hardly trivial when it comes to the total value of goods and services in the U.S. economy.

So let's just review what we'll hope to cover today is just to review some of the basics of cost-effectiveness analysis that we've already covered in this course and then talk about how is cost-effectiveness analysis being used in this and other countries.  What are barriers to implementing it or using it to make healthcare decisions and how can we overcome those barriers and then talk a little bit about in the world where comparative effectiveness everyone acknowledges that that's an important thing to consider.  How do we use the tools of cost effectiveness and maybe even if people are not willing to look at cost-effectiveness analysis.  So that's just sort of an overview of what we're hoping to accomplish.

So first to start with just that review of what is cost-effectiveness analysis and we've talked about it being a method of comparing treatments or screening or care.  One of the alternatives is standard care and the idea is that we would measure all costs, using the societal perspective, so regardless of who incurs them, and identify all outcomes and express them in terms of Quality Adjusted Life Years.  We use long-term, really life-time horizon to assess the costs and benefits of the intervention compared to standard care and then we'd apply a discount rate to reflect that lower value that occurs with delay.

Then test for dominance, that is, we find out if one of the alternatives is more effective and less costly and then that alternative would dominate and, in fact, there are some weaker dominating conditions like if they're equal cost or one is more effective or if they're equally effective and one is less costly, but if there is no dominance, then we look at the Incremental Cost-Effectiveness Ratio, which some people call the ICER and that is simply the differences between the experimental intervention and the standard intervention in terms of cost divided by their differences in QALYs.  In other words, what are we paying for to gain a QALY?

   The decision maker can compare this ICER to a critical threshold of what they consider to be cost-effective.  Dollars for QALY in the U.S. healthcare system we observe that people seem to use critical thresholds of 50- to $100,000 per QALY and that things that are very much more expensive in this are not so likely to be adopted and things that are less expensive in this are.  In fact, it's been proposed by some that the threshold really is maybe the mean per capita gross domestic product that that really is what could be used to find that critical threshold.  World Health Organization suggests that.  

Then the question is: where can cost-effectiveness analysis be applied?  How can it influence the healthcare system?  It could influence individual decisions of both physician and patient, but also more system-wide decisions about what services do we cover, what drugs do we include on the formulary and practice guidelines.  What is the optimal care for a given condition?

Now in other countries cost-effectiveness analysis is employed and Canada has an agency for drugs and technologies that has for more than two decades evaluated health technologies and there are also provincial organizations that study cost-effectiveness.  In the United Kingdom they have an institute of clinical effectiveness, NICE, that provides advice to the National Health Service.  

And other countries require—new drugs when they are being proposed to be used in their healthcare systems that they have some information about evidence of cost-effectiveness.  Germany has an institute on quality and efficiency that's not so new now and France also does pharmaceutical reviews and it is somewhat unique in every few years updating those, based on changes in prices or new information about effectiveness.

So in most developed countries health plans consider cost effectiveness in one way or another and use them for coverage decisions like new drugs and technologies.  They don't always follow unambiguously the cost-effectiveness findings and they're not that very many cases of outright rejection based on cost-effectiveness considerations.  

Now that said, we have to confess that the last time I looked at this literature we found that there were no formal evaluations of how cost-effectiveness analysis affects healthcare decision making.  There's a lot of anecdotal stuff about it, but nobody has really done a formal evaluation in any country.

Now in the United States we have a different history.  Medicare proposed using cost-effectiveness criteria in 1989.  There was a regulation that its proposal led to a decade of really contentious debate and it was not adopted, it was finally withdrawn.  The Medicare Coverage Advisory Commission doesn't consider cost or value in its decision making.  

More recently the Patient Protection & Affordable Care Act, also called Obamacare, in the popular lexicon of late, created an institute to assess outcomes, effectiveness and appropriateness, but had specific language in the legislation that said that dollars per QALY threshold should not be used by this institute, PCORI, and that dollars per QALY should not be used in the coverage decisions that are being made by Health and Human Services.  There was actually a kind of a big step back made at that time in terms of use of cost-effectiveness analysis.

Now it didn't say dollars per QALY were ruled out, just a dollars per QALY threshold shouldn't be applied, but Joe Selby, who's the head of PCORI has said that the PCORI will not do that kind of cost-effectiveness research.

Now another cost-effectiveness experiment was with the Oregon Medicaid program and people may be aware that they attempted to prioritize and restrict the more expensive and low benefit treatments.  So it's kind of a cost-effectiveness analysis to set the coverage decisions.  There was a lot of controversy over it at the time, but it is interesting—kind of the popular wisdom is that the Oregon Medicaid experiment failed, but, in fact, the Oregon Medicaid continues to set priorities for Medicaid services that are actually used by the managed care plans that provide Medicaid coverage in that state and in fact they're pretty much following and using the critical thresholds that their panel that sets those priorities has developed.  So that's pretty interesting, so while popular opinion is it that the Oregon Medicaid experiment failed, in fact, there's some suggestion that it's actually had some impact at least on the managed care part of the Medicaid in Oregon.

Now there have been a number of surveys and analyses about use of cost effectiveness.  This study that I've cited here by Alan Garber and his colleagues asked managed care plans, "Are you using cost-effectiveness analysis?"  Most of them said, "Oh, yes, we consider cost," but fewer than half said they actually used formal cost-effectiveness analysis in making their coverage choices.

So what we want to do now is just have a little time for you to give us some thoughts about what you think—why has there been this resistance, using cost-effectiveness analysis in the U.S. healthcare system?  We're going to try to use the question and answer panel for you to put in your suggestions here.  So you would type it as if you were asking a question, right, Heidi?

Heidi:  Exactly.  That Q and A screen is located on the dashboard that's on the right-hand side of your screen.  If it did collapse against the side of your monitor, just click that orange arrow at the upper right-hand corner of your screen to open that up and just type in whatever you are thinking in that Q and A screen and it will come out and Jean will read those over the line here.

Paul G. Barnett:  I'm sorry that I neglected to introduce my colleague, Jean Yoon who is also a health economist at the Health Economics Resource Center, so, Jean, appreciate your help here in giving us—

Jean Yoon:   So we have a few responses.  Some people have typed in—people aren't exactly sure what it is, tradition, money and political issues?  Politically unpalatable, too difficult to understand, perceptions of using CEA to limit available care. Somebody else wrote in, "Universally applying"—sorry.  "Universally applying tools that may not be unique to an individual.  People are concerned about care being rationed.  Too many stakeholders' opposition.  Difficult to do as correctly as many would demand, once you state you are doing one.  I wonder if the complexity of the QALY and the society perspective are too overwhelming for non-economists to digest?"  Somebody else wrote in: "Cost is not the same as value."  Somebody else wrote: "The question about putting costs on life and how to measure quality of life potentially negative consequences for high cost patients, such as people with disabilities or complex conditions."  There's a bunch more, if you want me to continue reading?

Paul G. Barnett:  Yes.  I think those are all very interesting and really do get at the heart of the issue.  I think the interesting thing that was in the debate leading up to the Affordable Care Act, Governor Palin was the one who said that—worried that—of course, originally she was speaking about the Palliative Care Consults, that they were calling them "Death Panels", and she expressed specifically concern that her disabled child might be subject to some sort of pressure from a Death Panel.  Of course, I think there was a big misunderstanding on her part about what it was that was being talked about, but she subsequently meant to say that she meant it to be about coverage decisions.  So I think that is an interesting—that whole question about how does it treat the disabled and I think that is a very important one or people who don't have very many QALYs.  Anything else there, Jean, you think that is novel that you might not—

Jean Yoon:  Several people have pointed out that there's a tension between what's preferred for the population versus care for individual patients.  What applies to the average person may not apply to a very sick person.

Paul G. Barnett:  I've been able to find at least 16 different surveys of decision makers’ attitudes about health economic studies and so people have identified many of the concerns that are represented in these studies.  One I didn't hear so much was—somebody did mention the idea that they may not understand QALYs, but also people are concerned about the long-term modeling, that models are not so well accepted and just a general lack of understanding about cost-effectiveness analysis.  But even decision makers who do understand cost-effectiveness analysis are worried that it's not relevant to their particular setting or their time horizon.  They have a more short-term time horizon or they want a perspective from their own view as a payer rather than the societal perspective.

Then another criticism has been that the cost-effectiveness analysis lacks information on the budgetary impact.  So cost-effectiveness analysis may tell you that say it's only $10,000 per QALY if you adopt this intervention, but it doesn't tell you how many QALYs you're obligated to buy if you choose it.

Then there's also been a concern about—in some studies that there's a sponsorship bias.  So, for example, we mentioned the pharmaceutical evaluations that are done by many countries, those are sponsored by the company who's promoting the drug in question, so there's a question about whether those are truly objective cost-effectiveness analysis.

Then I think there are some unique American issues about distrust of government and corporations and our unwillingness to concede that resources are really limited, that we really do have to make choices.  Somehow we think as long as care continues to offer some benefit to the patient or some even small probability of benefit that we ought to be able to provide it regardless of cost and I think that is an interesting problem too.

So there are a number of things that we, as researchers, who are trying to use this method, can do to make our results more useful or more acceptable to the decision makers.  The International Society on Pharmacoeconomics and Outcomes Research, ISPOR, sorry to have an undefined acronym there, has actually made some recommendations on what we can do to improve acceptance of cost-effectiveness analysis.  Basically just being more transparent at what we do, describing the relevant population and its size and that allows us to project the budget impact.  Of course, whose budgets will be affected, that's also very important to the decision maker.  It's important to know whether it's the health plan or the patient who's going to bear which share of the cost.  This is all about the disaggregation of both costs and outcomes.  What their timing is, which sub-groups might be affected and then the last bullet there is this whole idea that we'd be very transparent about what are our assumptions, what data did we use, what sensitivity analyses we conducted and to be able to say what parameters have the biggest impact, that is, what assumptions that we're making might be driving the results?

Other ways to improve acceptance are to make sure that the cost-effectiveness analysis is relevant to the decision maker and I think this is actually a very important thing for us to think about.  A lot of the help desk requests, the consulting service requests, that we get at HERC are about kind of novel interventions that are not really on the horizon yet, something that someone may have developed and they would like to show that it's cost-effective.  I think, we, as economists often get sucked into those evaluations when actually there's a lot of coverage decisions, a lot of expensive things that are on the cusp of being adopted in the healthcare system and that's where we really ought to direct our attention, really is try to think about what are the high impact decisions where our research is most likely to have an effect and, in fact, in other countries the cost-effectiveness analysis are actually commissioned by the decision makers, the decision makers go to the health economists and say, "Hey, there's this drug that we've got to decide about, tell us whether it's worth adopting."  In that sort of situation, the decision makers are anxious for results.  I think the emphasis now in health services research and development service to be a partner with VA operations is really an opportunity for us to take this same approach.

Then, of course, our studies are going to be more useful if they're timely.  I think it's really important to think about if something is already adopted, the cost-effectiveness results may be too late.  It's very hard to de-implement something once it gets adopted.  Whereas if we prevent adoption of something by saying right at the outset that it's not worth doing, that's important.  I think an example—perhaps a good example, I don't know—is like the breast cancer screening recommendations in young women, after many people became screened, and screening became emphasized by so many, once the Preventative Health Services Task Force began to say, "Well, you know, younger women this is not so valuable, not so cost effective," in essence, they didn't use quite those words, there was a lot of resistance to it because it was a kind of withdrawal of an existing plan or existing practice.

So how do we be more timely?  I think one answer is to conduct some preliminary studies or build your model or do your work in an area where you know there's new interventions that are coming down the pike, so that we're really pre-positioned to respond to requests in a timely manner.

Now in the United States, coverage is based on effectiveness, not so much cost-effectiveness, but there's kind of a backdoor way in which cost-effectiveness enters this because—and this slide really could be attributable somewhat to what Alan Garber has written, just observing that—when coverage decisions are made, they don't look at cost-effectiveness, but they want to be sure that the effectiveness has a big effect and that the evidence is strong.  So those are saying something about the incremental benefit.  If treatment is expensive then the decision makers really want to see a much larger effect.  So they are doing a kind of back-of-the-envelope, if you will, cost-effectiveness analysis.  They know that it's a big expense and so they want to be sure it's really going to work and cause a big impact.

There are more examples of use of cost-effectiveness by the Preventive Services Task force when it makes its recommendations for screening, although oftentimes it does it in kind of the same mode of talking about if it's very expensive then there has to be good benefit and not too many risks.

The American Managed Care Pharmacy has it formulary guidelines and so Peter Neumann's paper of 2004 talks about ways in which cost-effectiveness analysis are being used by these decision makers already.

I'm going to talk a little bit about comparative effectiveness research so that PCORI, the Affordable Care Act Funded Institute, is really about doing comparative effectiveness research and comparative effectiveness research saying, "We'll study alternative treatments and really compare it to standard care, not the new treatment compared to placebo, but compared to the best available standard care and find out if it's really worth doing or at least if it's more effective."  So comparative effectiveness is sort of I think been promoted as an alternative to cost-effectiveness, being seen as too controversial.  

So the interesting thing, there are some limits to comparative effectiveness research.  What do we do if the most effective treatment has more side effects or has a higher risk, how do we balance the harms with the benefits that a treatment causes?  So comparative effectiveness doesn't really have an answer to that and also how do we estimate the long-term benefit of something that we do in the short term?  So what's the long-term value of say identifying screening someone for a disease, comparative effectiveness could tell us which is the best screening method, but it doesn't tell us exactly what the value of that is.

Louise Russell has written a very interesting paper about how even if you don't want to do cost-effectiveness and you believe in comparative effectiveness, you may end up using some of the methods that we employ in cost-effectiveness analysis.  

One is the whole question of how do you balance benefits with risk?  How do you trade off the potential for harm with the gain that you get from a treatment and so she says that well, if we convert to QALYs, then at least we can find out what's the net benefit and which is the most effective once you've considered harm.

Then if we have to extrapolate on short-term effectiveness, we can use the same decision models that are used in cost-effectiveness analysis to estimate long-term benefits.  So I think her work is really interesting, just proposing that even if you don't want to use cost-effectiveness analysis, it offers some useful tools to the world where we only consider comparative effectiveness.

Alan Garber has written that one criticism of comparative effectiveness it's as if you went into a restaurant and you had a menu of choices, but you never knew what the price was until the bill arrived.  So you have to make choices informed by cost really if you're going to be a good consumer.   

It's interesting the Institute of Medicine set some priorities for comparative effectiveness, this was in the first part of the Obama administration the economic stimulus bill mandated that part of the research we would do that was stimulus-funded research that was on comparative effectiveness asked the IOM to come up with some priorities and the IOM said these very words that "cost-effectiveness analysis is useful for comparative effectiveness” and in fact if you look at the 100 top priorities, which is what they were challenged to come up with, the word cost appears explicitly in 13 of the 100 priorities.  So even though they were kind of directed to not consider cost-effectiveness, but comparative effectiveness, they couldn't avoid mentioning it in so many cases.

It is also interesting that cost-effectiveness—I think the most experience with applying cost-effectiveness in the healthcare system is in the United Kingdom, where the National Institute on Clinical Effectiveness has made its recommendations.  It's very interesting to see the history there that in some cases even when treatment is not regarded as cost-effective, that is, if it's higher than what would be considered cost-effective by a threshold that it's say $200,000 a QALY sometimes the treatments will still be adopted and this really has to do with the special needs populations, when there's a life threatening condition or when it involves the health of children or disabled or some group that has special priority, as it were, and we, in VA, we might also think about this if we apply cost-effectiveness analysis more thoroughly to our decisions that we might treat conditions that are the result of a service-connected injury or illness.  So it seems unlikely to me that VA would ever put a very strict criteria on say a treatment for post-traumatic stress disorder, based on the cost-effectiveness considerations.  That's somehow the special population that's it's our mission to serve.

So part of the way in which the NICE responded to this issue saying basically there's other information that you need besides just the cost-effectiveness ratio.  They have a citizen's council that provides them with advice and kind of mitigates or somehow helps attenuate the effect of the cost-effectiveness analysis, that basically incorporate that public input.  I think that what this is really about is this whole idea that all QALYs are equal and that is one of the assumptions underpinning cost-effectiveness analysis and it appears that if we can provide QALYs to those who are under endowed, those people who have not much life expectancy or have a serious disability, they don't have many QALYs now, we'd rather give them an extra QALY, all things being equal, than someone who had already had a lot of good health and expected lifetime.  So that NICE citizen's council I think is a way to kind of incorporate that into the decision making process.  

There is a paper that Martha Golds—she's the author of the Public Health Service guidelines to doing cost-effectiveness in health and medicine that is really the underpinning of this course.  She did a work with some individuals who were recruited from the jury pool in New York state and basically asked them to rank a bunch of different healthcare interventions, did some training and then asked them to rank them again after providing these jurors with information on cost-effectiveness and she showed that it did influence their decisions about what sort of healthcare ought to be covered, so that these jurors basically represent a sample of Americans—could get the idea of what is cost-effectiveness analysis and understand and think that it was relevant to designing a health plan.  So I think that's a very interesting experiment and it certainly is a challenge to us to think about how we would make cost-effectiveness analysis just not something that only the experts understand, but become more well appreciated in the popular understanding.

I think there is a unique role for us in the Department of Veterans Affairs about how we employ cost-effectiveness analysis.  For one thing, we have pretty much a global budget, so for us, if we can use more cost-effectiveness analysis in making healthcare choices, all we can do is increase the number of QALYs that Veterans are going to gain, given our global budget.

We are, in essence, tied to this health system, there is this potential for collaboration and I think it's already being realized between decision makers and researchers and we do have this identified constituency that is who are members and these members I think could be and really must be involved as we try to apply cost-effectiveness analysis in the Veterans Health Administration.  

I just thought here for a minute about some of the potential research partners, those operations partners who would be interested in cost-effectiveness analysis or already working with it.  The Pharmacy Benefits Managements folks are doing some work in this area, but clearly I think they would be very open to having assistance in helping evaluate new drugs that come to them for review.

National Center for Health Promotion & Disease Prevention does a lot of work on screening and prevention.  They're definitely thinking in these terms.  Again, the Office of Public Health, Specialty Care Services, Chief Business Office, I think this is an interesting one about the choice of whether we make or buy services really could be fashioned as a cost-effectiveness decision, where we ought to consider also the cost that the Veteran incurs in traveling to the VA versus traveling perhaps to the closest community hospital or perhaps further away to a particular selected contractor that really could be boiled down to a—put in a cost-effectiveness frame.  So I think these are opportunities for us.  There are many more potential research partners.

So I'd just like to kind of recap, review what is the take-home message is: that if we want to choose a topic to do research on cost-effectiveness analysis, it's going to be important to involve the decision maker at the outset and whether—consider if our finding is going to be relevant to policy and so really it boils down to: Is this expensive treatment?  Also is the treatment targeted for one of the exceptional groups that is people that we think are under-endowed with QALYs that maybe cost-effectiveness analysis would not be so relevant?  So I think those are good things to think about as you choose a topic is who's interested and who would apply my findings if I develop them and is this something that is a high priority then because it's going to be expensive in cost and then also is it a study that's likely to be only part of the choice.  

I'm not sure how we would get involved in some of the more controversial areas like—I'll give the example of doing cost-effectiveness on PTSD, there are some other examples that we could think of where cost-effectiveness would be difficult to apply.  For instance, where the Oregon Medicaid foundered was on its recommendation about soft tissue transplants as not being very cost-effective.  Well, there was a very identified constituency that needed those transplants and that that made it very tough for them to hold to that priority.

Once we've chosen our topic is how do we prepare and report it and one of the three papers that was in JAMA that came out from this Public Health Service panel actually talks about how do you report cost-effectiveness analysis?  We want to be transparent, we want to provide disaggregated costs and outcomes, so we can look at not only sub-groups, but also how does it affect different stakeholders: the payer and the patient, the costs that they incur?

I think now that we're realizing that budget impact analysis is really an essential adjunct to cost-effectiveness analysis, we need to describe how many people are going to be affected by the coverage decision or the guideline that's in question?  What's the effect on the payer and their short-term cost?  Basically this whole question: If you make this choice to cover this service or this drug or adopt this guideline, what's the bottom line?  What's the impact on the budget?

Here are some papers that were cited in the talk.  I think all of these are very interesting food for thought.  Do we have any questions or discussion?

Jean Yoon:  There's one question and one comment.  So one comment is that there was a report that was released by AHRQ, the Agency for Healthcare Research and Quality in October of 2012, which may have formally assessed the economic evidence on policy makers in healthcare.  So the person provided the link, which we can e-mail out to everybody.

Paul G. Barnett:  That's great.  So this is about cost-effectiveness analysis?

Jean Yoon:  Yeah.  It looks like the title is: Assessing the Impact of Economic Evidence and it was just released a couple of months ago.  This is available on the AHRQ Web site.

Heidi:  I will include that link in the archive notice that we send out tomorrow, so everyone will have that in their e-mail tomorrow.  

Jean Yoon:  There are a couple more questions that came in.  Somebody asked about the QALY threshold that you mentioned.

Paul G. Barnett:  The idea is if one of the interventions that we're considering is more costly and more effective, we have to decide whether the value of that benefit is sufficient to justify the cost.  So now we have it measured in dollars per quality adjusted life year, so how much is society willing to pay for quality adjusted life year?  In the United States we used to say $50,000 per QALY and that was based on what the end-stage renal disease program cost Medicare and at some point, somebody said, "Well, this is about as much as anybody would be willing to spend," but that number has increased over the years and more recently the World Health Organization has said it's about what your per capita GDP is.  They observe that that seems to be what society is willing to pay for a QALY.  So if you're in sub-Saharan Africa maybe you're only going to spend $1,000 $2,000 for QALY on healthcare interventions.  Whereas in Western Europe, you're more likely to spend 20,000 Euros or whatever, 25,000 Euros.  

That's the basis of it and actually what the cost-effectiveness analysts—usually dodge the question by reporting their results as a cost-effectiveness acceptability curve.  Did we cover that in the course?  I can't remember right now, but the idea is to offer the decision maker information about what the cost-effectiveness is at a variety of thresholds, so they can use their own particular threshold and make their choice and know what the implications are.

Jean Yoon:  There's another question about cost-effectiveness for screening projects.  "Can the outcome of cost-effectiveness analysis about screening be the number of patients we screened?"

Paul G. Barnett:  It could be, so strictly speaking cost-effectiveness could be denominated in any sort of unit, not necessarily QALYs.  If we're really being correct or accurate in speech, we should have called it the cost utility analysis when we talk about dollars per QALY is a cost utility analysis, which is a kind of cost-effectiveness analysis.  So you can see in the literature that people will report things like dollars per person who quit smoking cigarettes or dollars per heart attack prevented or—it could be denominated in terms of any outcome.  The problem is that we don't know what the threshold is, how much should society be willing to pay for one smoker quit or one heart attack prevented—we don't have any way and even if we did have a threshold for that, how would we compare an intervention for say smoking cessation to one for cholesterol reduction?  So the fact that they're all denominated in QALYs, allows us to compare all the possible interventions across the whole scope of the healthcare system.  So that's the big advantage of that.  

So the interesting question even if I have dollars per smoker who's quit smoking cigarettes, immediately I turn to the literature and I see that people estimate that quitting smoking is worth about one to three QALYs, depending on the study, depending on the age of the patients who quit, and their co-morbidities.  So that immediately begins to say how much we're willing to spend per quit, so you can see how the denominating things in QALYs is helpful.

Jean Yoon:  Somebody else asked, "Are you recommending that we start this process at the local level, in other words try it on a particular VA hospital for a selected topic like approaches to lung cancer?"

Paul G. Barnett:  Well, no.  I think it's going to be harder to do on a local level really.  I actually think the way to approach it is to think about what are the decisions that are being made not in any particular clinic with any particular patient, but rather start at the decision about what will the health plan cover.

I asked Peter Neumann about this, who is—if you're not familiar with his work, he's a great person to read up on and read some of his papers.  He keeps a registry of cost-effectiveness ratios at Tufts University that is available to you, so if you ever have a question about what—any particular intervention—has there been any cost-effectiveness study of it, you can look it up in there, Tufts Registry.  In any case, I say, "Where do we start?  What's the place that is the best place to start, where we're actually probably going to draw the least political heat," and he said, "Well, you know, it seems like where it's a statistical life that's at risk as opposed to the particular person who needs a particular service."  So what he meant by that—especially in the area of like screening, where your probability if you get screened, you're going to decrease your probability of getting a condition or getting treatment, but those are the places that are really most amenable to a cost-effectiveness analysis and objectively that is where cost-effectiveness analysis I think has had the biggest impact on U.S. healthcare that we really do—I think the people who formulate screening guidelines do think about this and realize that, "Gee, if it's going to cost a million dollars per QALY, if we screen everybody for some condition down to age 20 and it's going to cost us a million dollars per QALY, that's not a very good use of healthcare resources.  

Then the other kind of decision I think where we can be really helpful is when there's some expensive new technology that's on the horizon and I give you an example, one that we're struggling with right now is VA is being asked to look into using low dose CT to screen smokers for pulmonary nodules, to see if they might have lung cancer.  This would be phenomenally expensive if we adopt it and so cost-effectiveness analysis could be pretty informative.

Jean Yoon:  Somebody else asked: "How do you educate the U.S. public about healthcare costs?"

Paul G. Barnett:  Well, I think the public is pretty aware of cost itself.  I think where we're stuck is that there's not generalized acknowledgment of how we deal with the cost.  How do we stem the cost?  The idea that we actually are not making good use of the healthcare dollars that taxpayers give Medicare, VA, and Medicaid and that the premium payers give to the health plans, so that money is not all being used as well as it could be.  So I think the place to start is with the whole question of ineffective services.  We've talked a little about this in prior seminars, but there are actually lists of things, targets for de-implementation NICE, the National Institute on Clinical Effectiveness in the UK has its list, it's Do Not Use list and the Institute for Healthcare Improvement has its list, earlier this year in the Annals of Internal Medicine there were 37 diagnostic tests that shouldn't be done.  So I think that's one place to start, it's just to look at some of the totally inappropriate services that people are aware that those are being done and then the other place I think is choosing wisely—what do we call it?  I guess it's kind of a movement or anyway an effort to educate patients about what the implications of their healthcare choices are.  

I actually think that if we did a very thorough job of informing patients about what the payoff is and what the cost is of the care they're going to undergo, that they will actually make very similar decisions as a coverage commission might make.  So in other words if someone knows that—well, so we talked about this low-dose lung cancer screening, if they understand that their chances if they enter a low-dose lung cancer screening project, the chances are 30 percent that they will have a positive result from the screening, but 19 out of 20 of those positive results will be a false positive and they'll get a lot of workup for something that won't turn out to be lung cancer.  I think that informing patients of that is probably going to cause a lot of people not to opt for this.  We don't necessarily need to have the Coverage Commission say, "This is not cost-effective," if we have the patient who is well informed and choosing wisely, then the patients are not going to opt for things that are essentially very expensive, even just in terms of their time or the procedures they have to endure and won't result in much payoff.  It's patient by patient, but there's probably other ways, too, to do this.

I think it's a great topic, those are my thoughts, but I think it's a bit of a challenge for us, being where we are in VA, we don't want to seem like we're the proponents of rationing.  So we want to be the proponents of efficiency and value, but not of rationing.

Jean Yoon:  Congress is certainly considering cuts to Medicare right now because of the fiscal cliff and everything like that, so I think people are aware of the high cost of healthcare in this country.

Paul G. Barnett:  Well, cuts to Medicare were already put into ACA, put in the Affordable Care Act?

Jean Yoon:  Right.

Paul G. Barnett:  The question is: are we going to cut the unnecessary stuff or are we just going to do it in some sort of proportional cut to everything, regardless of its value that's the disturbing worry.

Jean Yoon:  Somebody else asked: "How has cost-effectiveness analysis related to cost savings model, example: considering preventive care?"

Paul G. Barnett:  We're thinking about changes in cost over changes in QALYs, but the thing we want to do is to measure all costs from the societal perspective.  So I think what the questioner is getting at there is that sometimes a particular intervention prevents subsequent healthcare costs and so that is—and if you have a really exceptional intervention that could even save cost in the long run that there would actually be cost saving, but I got to say that that is often the hope, but rarely realized.  Most things we do we add to the healthcare system, they may offset some of their cost down the road, but usually they add cost and we really are in this area where there is not dominance.  So they're hoping that they're going to have the situation of dominance that is that one of the interventions is going to be more effective and less costly because it's offset its cost by reducing cost in the healthcare system down the road.  I just think that if you go look at the Tufts Registry of cost-effectiveness analysis and you'll just see how few of them actually involve dominance.  There's I'm sure less than ten percent, most things that we do to improve the quality of healthcare cost extra resources.

Jean Yoon:  There's another question in here about QALY weights: "What QALY weights are used for VA cost-effectiveness studies?  Do you include or exclude productivity costs?"

Paul G. Barnett:  This is something that is discussed in one of the chapters of the Gold book, that is the Preventive Services Task Force on cost-effectiveness in health and medicine.  So the hope is that we have done a good job of measuring the quality or the utility and that we incorporate any loss in productivity in that measurement of QALYs and that we don't use lost productivity, say lost time from work, in our cost-effectiveness results.  One of the problems with doing that is if we're say dealing with an intervention of people over 65, we don't value their time at all because it's not lost productivity.  So that's why we really measure it in terms of utility values and not consider that lost productivity.  There is some discussion, some people think that we ought to incorporate that into the cost-effectiveness, but I would say that's not the standard method, the standard method is to measure utility and we have a guidebook on how you go about measuring utilities.  There are three commonly used, off-the-shelf measures, [inaudible] or EQ-5-B, the Health Utilities Index and the Quality of Well Being Scale that are basically pencil and paper or you can use a computer or whatever to gather—ask people some standardized questions. EQ-5-B just ask five questions that ends up in assigning them a utility value.  The more direct measurement methods, standard gamble and time tradeoff, are harder to administer and are not commonly done in studies, but people do do that too.  There is a pretty complete guidebook on how to measure utilities that we have on the HERC Web site.  

Jean Yoon:  There is another question, asking about for preventive interventions, we want to track the effects of interventions over the lifetime, however, administrators face budget planning over shorter durations, should we present data on return on investments for shorter durations to increase relevance for decision makers?

Paul G. Barnett:  This is a real problematic one because—right.  Here's the classic example, why doesn't HMO fund smoking cessation services?  Well, that's just going to prevent cancer 20 years from now, that return on investment is not very great, the person may even leave our health plan by then.  What the guidelines say is we want to be concerned about lifetime costs and benefits and that we do care about preventive services that may have a benefit that's not realized until years in the future.  Obviously, if you have a decision maker with a very short-term timeframe, it's hard for them to see that there is going to be a short-term return on investment.  So return on investment is an idea from kind of the business literature about what's the payback.  It doesn't fit so well for the healthcare decision making, although people have tried to use it that way.  I don't know.  Jean, do you have any thoughts about that?  I know that Patsi's talked a little on that, this return on investment stuff.

Jean Yoon:  Yeah.  I haven't done any work on return investment, so I don't know much about—

Paul G. Barnett:  My predilection is to say that's not so commonly used in healthcare.  There probably is a way that you can use that language.  I mean in essence the dollars per QALY is a return on investment, isn't it?  If you assign a dollar to the QALY, then you can come up with a return on investment, but this whole question about the decision makers really interested in knowing how is this going to affect the bottom line this year is the budget impact analysis and that's why we suggest that a budget impact analysis really needs to be part of most economic evaluations.

Jean Yoon:  This person has a comment and then a question.  The comment is:  "I think that physicians in health provider organizations know of cost-effective care, but for financial incentives, they will continue to drive the healthcare costs up."  So I think what she's referring to is pay for service.

Paul G. Barnett:  Fee for service.

Jean Yoon:  Pay for service.  "The solution is really healthcare consumer education."  The question is: "How do we deal with institutions pressuring healthcare providers to provide unnecessary services?"

Paul G. Barnett:  Right.  What are the things that drive this overuse?  We think to a certain degree we're somewhat insulated by in VA, but maybe not as well insulated as we think.  What are the factors?  One is there are financial incentives such as if someone's a fee-for-service provider or even if they could be self-referring, right?  There's some examples of that, where they're actually referring to their own diagnostic lab or their own scanner or whatever.  There's also been offered as a reason for overuse is the fear of malpractice that you have to practice to the community standard.  Medicare has dealt with this by using prospective payment, right?  Going back to 1981 with paying hospitals on the basis of the discharge, not necessarily what services are provided during the stay.  It's gradually expanded perspective payment to cover outpatient services so that it doesn't matter what facility charges are incurred, you're going to get a flat rate based on the procedure that's provided and then we have capitation payments, they're just payments per covered life or per case-mix adjusted covered life, so these are all ways that we get around that, trying to avoid the incentives to over-utilize.  Then the other way I think that we get around it is to begin to judge provider performance based on efficiency and that's just a whole 'nother talk, but there are now a number of measures of provider efficiency where providers can be compared to their peers in terms of their use of services for a given population.  I think if those are linked to some of these quality measures and also measures of specific inappropriate things that we ought to reduce that that becomes a very powerful tool to make the healthcare system more efficient.

Jean Yoon:  Okay.  Then there's another question: "For your studies, do you use a utility function for the QALY derived from the VA population or from where do you get your utility function?"

Paul G. Barnett:  For the clinical trials—and you have some clinical trials you're doing, right, Jean?  So what are you doing in your trials to measure utilities?

Jean Yoon:  We're measuring QALYs from things like the EQ-5-D from these patients and then we apply these population weights from the population responses that we get from the patients in the study.

Paul G. Barnett:  So you're actually asking the questions of the VA patients?

Jean Yoon:  Right.

Paul G. Barnett:  But to translate them into utilities there's some sort of scoring algorithm and that is not based on VA patients.  I think EQ-5-D now has U.S. weights, they're based on U.S. responses, but, yes.  So there aren't really any utility weights that are based on VA population.  So basically it's an EQ-5-D there are five questions and I can't remember—like are there 100 possible ways, permutations, that could be answered, something like that?

Jean Yoon:  Yeah.  There may be like five responses for five different questions.

Paul G. Barnett:  Right.  Depending on your response, that contributes to the score, which is going to run from zero to one, zero representing death, one perfect health.  So those weights that are assigned to the responders, those are not developed on a VA population, but the responses themselves are from people who are participating in the VA study.

Jean Yoon:  I think you've basically answered all the other questions that were still in the queue.

Paul G. Barnett:  It's exactly the hour, six seconds left by my watch.  I'm out of energy for doing this too, so it all happened perfectly,

Heidi:  You timed it out very well there, Paul.  

Paul G. Barnett:  Well, I'm sorry we don't get to see the interested or disinterested looks and get more feedback from this, but I think those are a lot of good questions and stimulates good food for thought.  

Heidi:  Fantastic!  This was the last session in the course, is that right?

Paul G. Barnett:  It is, that's my understanding.

Heidi:  I believe that's what I have here.  So for our audience, this will conclude the cost-effectiveness course, but we will be starting up the HERC Econometrics Course in September 2013 and we will be getting registration information out to everyone probably about four to six weeks before we get started there or you can always check the HSR&D cyber seminar catalog and we will get those added out there as soon as we have the information.

Paul G. Barnett:  We have cyber seminars coming up too in the interim.

Heidi:  Yes.  We have a monthly cyber seminar.  I believe you guys took this month off.

Paul G. Barnett:  Yeah.

Heidi:  But we will be getting started back up in January and we have a session scheduled on January 16th and Chuan Fen-Liu will be presenting.  I don't have a topic yet, but as soon as we have that we will also be getting that registration information out to everyone.

Paul G. Barnett:  Fen is a senior economist at the Seattle HSR&D program. I'm sure whatever she talks about will be very interesting.  There's also one we have scheduled—I'm not sure is it for April?  Where Gary Koontz is going to be talking about the modeling guidelines, isn't that April?  I think that may be very interesting to people.

Heidi:  It might be, but I haven't had a chance to fill out my catalog that far out yet, but I will get there within the next few days.

Paul G. Barnett:  So the Society for Pharmaco Economics and Outcomes Research and the Society for Medical Decision Making got together and developed guidelines for building decision models and they have just released those and Gary Koontz will be talking about those I think it's our April seminar.  It's in the HERC bulletin in any case, the time and place.

Heidi:  Fantastic.  Sounds great.  Well, Paul, Jean, thank you very much for presenting and helping out for today's session.  We really appreciate the time that you put in to that.  For our audience, thank you very much for joining us for the Cost-effectiveness Analysis course.  We hope to see you at a future HSR&D cyber seminar.  Thank you. 

**[End of Recording]**

Page 1 of 14

Page 14 of 14