Payer Decisions Regarding Reimbursement - Naomi Aronson


Uploaded by GenomeTV on 16.12.2011

Transcript:
Naomi Aronson: I’m giving the perspective today from the
Blue Cross Blue Shield Technology Evaluation Center. I am the director, executive director
of Tech and director of our AHRQ evidence-based practice center. And I am disclosing that
I am a seller, the employee of Blue Cross and Blue Shield Association.
I’ll briefly describe our center, talk about how we evaluate evidence, and touch briefly
on value affordability. In other words, who are we, what do we do, and what do we worry
about -- value and affordability. But we’ll only have a little time for that.
So, there are 39 Blue Cross and Blue Shield plans. They are independent plans making their
own coverage decisions but united by a series of principles and standards. There are 99
million beneficiaries, so almost one in three in the U.S. carries a Blue Cross and Blue
Shield card. And we have in support of evidence as the basis for decision making, health plan
decision making with the support of the Technology Evaluation Center since 1985. Principles of
Tech are rigorous evaluation of clinical evidence. We use systematic review methodology. And
the ultimate question always is does this technology improve health. And so, with diagnostics
in general, not just genomics in particular, questions do revolve around clinical utility
because that is the crux of improvement in health.
Our tech assessments are -- can be accessed online at bcbsa.com/tech. We consider that
our contribution to public understanding of evidence and [unintelligible] leadership in
evidence-based medicine. That work is done under the clinical and scientific authority
of an independent medical advisory panel, primarily clinician and clinician researchers
nationally known, including an appointee of the American Academy of Medical Genetics.
We also, and this is not publicly available, but we provide for our plans who have to make
day-by-day constant decisions around contract administration and benefits for what interventions
are medically necessary, a medical policy reference manual. This is, again, supportive
of our plans. We do not dictate coverage decisions. We don’t make this publicly available because
we don’t cover anybody at the Association. We don’t make payment. We don’t make reimbursement
decisions. We don’t make coverage decisions. We provide the clinical and scientific analysis
to support these. But if you go to plans’ websites, you will see those policy manuals
displayed online and, to a large part, they are resourced from our compendium.
And we have been an evidence-based practice center since 1997, most recently designated
as the comprehensive comparative effectiveness review center in cancer and infectious disease.
I think it would be helpful to distinguish between these elements in the plan vocabulary.
Medical policy is based on scientific evidence, on evidence of clinical effectiveness. It
does not take into account costs and coverage. All of this analysis is conducted independent
of those decisions. I will also add that, for the most part, Blue plans are not for
profit. Of the 99 million individuals who are beneficiary of Blue plans, only 30 million
of them are in for-profit plans. The rest are in not-for-profit plans.
What is covered is determined by the contract between typically the account, the employer,
and the plan. That circumscribes the benefits. And what is paid is a matter of the contract
with the provider. So we are focused strictly on the clinical, not on the cost. We’ve
been very active in genomics. This is what we have done in the decade before 2007. And
in the two years after, you can see that the volume of genetic tests of interest and our
devotion of resources to them has exponentially increased. We considered this a high priority
for our work, for our systematic reviews, and devoting about 25 percent to a third of
our capacity in genomics because we see this is as an area which is calling for that kind
of analysis.
I remind you of the framework for evaluating evidence of the ACCE where we look at analytic
validity, clinical validity, clinical utility, but I also want to remind you that this is
not unique. This is the model of the continuum for diagnostic efficacy put forth by Fryback
and Thornbury in 1991. And it reminds us that it’s not about technical efficacy, that
is, pretty pictures are not enough in diagnostic imaging. It’s not even about the accuracy
of diagnosis. But it’s about can you ultimately improve health. And all of our questions are
can we improve outcomes -- quality of life, length of life, ability to function. This
is the ideal. This is the model of the randomized control trial, test versus no test, treat
accordingly, measure the outcomes, compare. But I will caution now and I’m going to
remind you, very little of the literature in diagnostic technology is about randomized
control trials. And this is not necessarily a lack or a gap. It is frequently not necessary.
Because one often has a reference standard, a model of the disease, a model of what intervention
into the disease means, that understanding performance is often sufficient to make inferences
about outcomes, but not always, in particular not when one is by the fact of a diagnostic
technology; for example, defining a new disease state or looking at a new spectrum of disease.
And I would suggest that this probably occurring more frequently in genomics than it might
in imaging. But I would not suggest that all genomic testing would require randomized control
trials.
So I want to give you some examples of assessments we have done on the continuum of types of
evidence available to us. And I’ll start with genetic testing for long QT syndrome
which illustrates a chain of indirect evidence going from what we know about performance
in a clinical state where there actually is no true gold standard or reference standard.
What the links in the evidence about what can be done in change of management, and the
inference is that outcome would be improved. In this setting, and of course this would
refer to individuals who have a relative who either have a mutation or unknown mutation
status but clinical diagnosis of disease or individuals who, by clinical criteria, their
status is suggestive but not clear. What is certainly ascertainable is that the genetic
test ascertains more cases than clinical criteria. There is no gold standard. This is a lethal
disease affecting a young population, highly unpredictable. There is the potential to change
management for use of beta blockers, a relatively benign intervention considering the risks.
And the conclusion was that use of the test, use of the management improves outcomes and
has the potential to avert potential catastrophic consequences if left unascertained and untreated.
So this is an example of inference through, you know, relatively -- I’m not going to
call it low-grade evidence. But it’s descriptive evidence, and it’s inferential through a
chain of what’s known.
I also point that we have new opportunities and predictive biomarkers for looking at evidence
with a retrospective -- prospective methodologic -- methodology proposed and used by Simon
et al., which allows us -- it’s not simple but allows, for example, the use of archived
tumor materials from existing randomized control trials to protectively, rigorously pursue
certain questions in predictive genomics. Issues, there are always issues. There are
issues of stewardship of the archives. There are issues of missing data. But again, potentially,
alternative designs, alternative approaches.
And then, at the other end of the continuum, I’m just going to post there genotyping
for warfarin dose, very complex set of intervening variables. Trials are -- RCTs are in progress.
And the question of such complexity that we think it does call for RCTs. So, again, the
spectrum of evidence from a chain of logic to RCT illustrating some of the points on
that spectrum.
Now I’m just going to touch in the 27 seconds I have left on value and affordability. To
emphasize once again, clinical effectiveness is the cornerstone of plan medical and coverage
policy. I think there’s a thought, idea out there that plans are doing things based
on cost, that they have some cost effectiveness criteria, but actually, contractually, plans
really don’t have that capability at all. They are mostly driven by the medical necessity
contractual provision. And it really makes virtually no provision for consideration of
cost. And in the last five or six years or so, there has been a provision basically put
in there through court settlements that permits consideration of cost when two interventions
have the same outcome and one costs more and the one that costs more isn’t medically
necessary. But real life is interventions really have the same outcome. And what we’re
typically faced with is what’s the increment of benefit versus the increment of cost. And
we have -- we have no levers with that. That is a societal issue. Morever, there is no
gold standard for what is a, you know, the value of equality. Again, that is a societal
issue. That is a political-cultural issue. That really is not existing as a public kind
of conversation in our society.
But I think it is clear that even when you have interventions of high value, there may
be limits to what is affordable. That is, a Mercedes-Benz on sale may be a good value,
but it’s certainly unaffordable to me. So, we really are on the threshold, particularly
as we look approaching and the implementation of health reform, how are we going to get
more individuals under that umbrella.
And some of you may have read -- I certainly did with interest -- the IOM report on the
essential health benefit. And it really calls for a very prudent approach where, if interventions
are added, then something needs to be subtracted, that you should take the total cost of the
benefit to be stable. Will that be adapted? Will Secretary Sebelius accept that? I would
say, you know, that’s speculative. I don’t know. Probably not. Politically -- politically,
probably problematic. But I think it reminds us that we are dealing with an effort, and
[unintelligible] has mentioned this, that when cost goes high, access goes down. And
how are we going to handle all of those things? We don’t have it in our power. I believe
that the moral compass and the leadership needs to come from the professions, from the
clinical scientists, from the clinical researchers. Health plans are really not in a very good
position to do anything about this. But people will suffer if nothing is done.
And this is just a -- this is from Peter Orszag, Congressional Budget Office, showing that
if health care spending continues on the course it has been, it has the potential entirely
consuming the gross domestic product. And obviously, that’s unsustainable. It’s
undesirable. So, I simply remind you of that, that as we talk of evidence, we really -- and
talk of clinical utility, we are hoping to put value into the system to improve care
and to do the best we can with the resources we have.
And then I’m happy for questions.
Female Speaker: Thank you.
[applause]
Female Speaker: Any questions? Yeah.
Male Speaker: So in terms of cost effectiveness criteria,
I guess you basically said you don’t do it, but when it goes to extremes, you do consider
it.
Naomi Aronson: No, no, I didn’t say that. We don’t have
cost effectiveness criteria. We have one provision in the medical necessity contract language
that says if you have two things that have exactly the same outcome, you don’t have
to pay for the one that’s more expensive. That is a rare event that you would have that
occurrence.
Male Speaker: So, just to rephrase then, if it’s a million
dollars for quality-adjusted life, you’re saying --
Naomi Aronson: No, no quality-adjusted life here. It’s
same outcome. I’ll give you -- I’ll give you -- the only example, actually, I can think
of is virtual colonoscopy versus endoscopy. Virtual colonoscopy is actually quite a bit
more expensive. And that is the one instance I can think of where plans have actually applied
this provision in five years of experience.
Male Speaker: I think it’s important recognize, Ken, that,
you know, again, this gets at the perspective issue that, you know, qualities and that sort
of thing are from a societal, national perspective. And that’s not the way health plans adjudicate.
So, again, I think this is -- to reinforce what Naomi is saying, there’s this misconception
that plans are all about the cost, but the reality is is that what they’re really looking
for are improvements in outcomes and that if you can demonstrate improvements in outcomes,
there will almost always be coverage. Now the coverage is variable in terms of its implementation
with early adopters and late adopters, but the bottom line is that is you’re improving
outcomes, we almost never consider cost in any of the entities that cover health care
in this country. And in fact, many of our biggest payers are specifically prohibited
from considering cost.
Female Speaker: I see the French horn section is up again.
[laughter]
Male Speaker: Coming in -- no. This time I think I’m coming
in on the right note. I wanted to ask you just a question. It’s very common among
geneticists to believe that what makes genetics different from other fields and what makes
it different in the insurance arena is that clinical effectiveness applies to the patient
in front of you, but in genetics it applies to the entire family. And I think there’s
always a concern that coverage plans feel that, you know, if someone, a brother or sister
is not covered by this particular plan, is covered by somebody else, it sort of doesn’t
count and therefore we’re not going to take family impact into consideration when considering
clinical effectiveness. Could you comment on that?
Naomi Aronson: Yeah. That is an implementation issue that
we recognize and really can’t control because it’s tied up in some of the contractual
language. But our position is at Tech that the science says in many cases that it’s
clinically important to test the relative. This has been a challenge for plans. I think
it is ultimately -- and I think they have come out in various positions as a practical
matter, but I think it is ultimately resolvable. I am reminded of HLA testing for unrelated
donors. Was it -- a real sort of shock. How do you manage this? That’s been worked out.
I think this will be worked out. I actually feel that, given that we are covering one
in three of the U.S., we ought to be in a position to give some leadership and find
a way to do it. But remember, we are operating under employer-driven contracts. And there’s
not an appreciation of this, but we are promoting as a --
Male Speaker: But in terms of the science, in terms of clinical
effectiveness, do you take into account that testing the patient may not be of direct benefit
to that patient but may be of tremendous benefit to the relative.
Naomi Aronson: I just told you we think it is very important
to take a leadership role to understand that the clinical use of these tests may be -- may
depend on testing an index case that will benefit a member but et cetera, and we are
trying to exert leadership there. That’s the clinically right thing to do. And I think
our medical staff understands this. But we are operating under contracts that ER from
another area may not recognize that. And that’s what they are circumscribed by, by what, for
example, the employer may have purchased, et cetera, or what may be in the regulated
insurance. So you are dealing with the overlay of contractual mechanisms that may not have
caught up to current practice. That’s why I used the example of HLA matching as something
that was, as I said, a little bit of shock to how things were done but was eventually
incorporated. Could it go faster? I wish it would.
Male Speaker: We can always hope.
Naomi Aronson: But you’re dealing with a legacy system.
Female Speaker: Okay. Mark?
Mark: And I’ll just add to that that I think we
have an opportunity here because this type of an approach fits within concepts at least,
theoretical concepts of accountable care organizations and the fact that the, you know, health care
systems have the responsibility beyond just one patient by one patient. And particularly,
with the innovations center and the opportunity to perhaps explore this, and maybe this is
something that Jeff will mention in his talk as well, not to put any pressure on you, Jeff,
but I think this is an area where we should be very proactive in terms of looking for
opportunities to really test this out and say this really fits under the concept of
accountable care.
Female Speaker: Great. Thank you. Thanks, Naomi.