In segments #1 and 2, you learned why to do CEAs, and how to compare net costs to health
outcomes. In Segment #3, you learned about DALYs and QALYs, the uber-health metrics.
In this segment, #4, on CEA Results Tables, we examine CEA findings
and how to present them.
Now, let's talk about how to present findings from a CEA.
We'll start with a standard CEA results table for just two intervention options. We have
no therapy and drug A. In this case, we say that the evidence suggests that for a person
with this unspecified disease, the net cost with no therapy is $10,000, perhaps representing
a 20% risk of being hospitalized at a cost of $50,000 when it happens.
There are four DALYs associated with this disease. That means that the person with this
disease will lose a total of 4 DALYs representing both premature mortality and morbidity, compared
with a person without the disease. Drug A increases the net costs. Maybe the
drug itself costs $ 4,000. But it may reduce the risk of hospitalization. So the net cost
is $12,000. And the DALYs decrease from 4 to 3.5. Maybe there are both small morbidity
benefits and a slightly extended lifespan.
In this table we calculate the differences in costs, DALYs, and the ICER.
Under delta cost, we see that the difference in net cost is $12,000 minus $10,000, or $2,000.
So drug A costs $2,000 more than no therapy. The difference in DALYS is 0.5, simply 4 minus
3.5. This means we can calculate an ICER, a net
cost per daily averted. It works out to $4,000. Depending where you are working and which
standards you use for cost effectiveness, that might be considered either very cost
effective or cost effective. People always ask what's a good ICER? and
that depends. Currently WHO specifies an ICER below the local annual GDP per capita as very
cost-effective and below 3 times the local annual GDP per capita as just cost-effective.
A more sophisticated approach is to look at all of the options and pick the set of interventions
that are truly the most cost effective. That may eliminate some that are cost effective
by WHO standards because they're just not as cost effective as the other choices you've
got.
You might wonder, what happens if you have a negative ICER? Well in this example, we've
added drug B. And look, drug B is more expensive; maybe it's a new drug. The net cost is $17,000.
That might be okay, except, if you look at the DALYs, they went down from no therapy
to drug A but went up to drug B. In other words, drug B doesn't work as well as drug
There are more DALYs negative DALYs averted -- and a higher cost, which is bad.
And so you might think, "Well that's an ICER of negative $20,000." But that would not be
correct because once you have a negative ICER value you don't actually show it. It doesn't
have any technical meaning unlike a positive ICER, which represents the cost of gaining
health. A negative ICER changes values in odd and non-intuitive ways as you alter cost
or DALY inputs. Until you go through that exercise yourself you'll have to take my word
for it.
Negative ICERs shouldn't be reported.
So what do we do instead? We use the word Dominated. Drug B is both more expensive and
less effective. So drug A dominates B, or drug B is dominated by drug A, it's cheaper and better.
There's no need to compare the added costs to the added benefits.
Now let's look at a table with more comparisons. We've kept drugs A and B and added drugs C
and D. In this example drug C has a higher net cost but it also works a lot better. Drug
D has a still higher cost, but it doesn't work as well.
So what we have here is two strategies, A and C. Both have positive ICERs, $4,000 for
A versus no therapy and $6,000 for C versus what? What do we compare C to? Normally in
an incremental CEA we compare to the prior option. But B is dominated, so irrelevant.
Instead we skip to the closest viable option. We compare C to A.
Notice how we're not comparing each option to the cheapest option, at the top of the
table. The way I like to explain incremental CE ratios to my students is by reference to
my children's desire for a fancy sports car for our family. They want me to spend $100,000
for a car. I tell them, "Yeah that sounds like a good car and a lot of fun, but I have
a Volkswagen and it works fine and it costs $25,000." And for me the comparison isn't
the $100,000 car versus no car, it's $100,000 vs. the VW. It's all incremental. The same
strategy and technique applies here.
So, if you're going from no therapy to A, that's $4,000. Remember, you don't compare
to B because it's dominated. Drug C is $6,000 per daily averted compared to A and D again
is dominated. Now what if you find that drug A actually
is impossible. You can't do drug A for some reason, maybe it's under some restrictive
patent. Then you can compare C to no therapy, and drug A wouldn't even appear in the table,
because it's not a viable option.
That's all for CEA results tables. All of the results are referred to as base case with
the best estimates for input values. However, we know there's uncertainty, because we never
know each input value with complete precision the value may have a 95% confidence interval
in the source study or imperfect applicability to the modeled study population. That's why
we head next to sensitivity analyses.