heart attack avoided or cost per life year saved. This approach works well, said Veenstra, and people are reasonably accepting of it. CEAs, however, do not easily allow for cross-intervention comparisons, for example, whether to spend $50,000 to prevent a heart attack or spend $50,000 to prevent breast cancer. Answering this question would require further considerations of how long a person would have lived, what that person’s quality of life would have been with a given intervention, as well as other downstream costs.
The gold standard in the field has become CUA because of this limitation of CEA analysis, said Veenstra. CUA typically measures outcomes through a metric called a quality-adjusted life year (QALY) and allows for comparisons across interventions. For example, if $50,000 spent to prevent a heart attack produces 10 QALYs, and $50,000 spent to prevent a breast cancer produces 20 QALYs, a decision can be informed by that information. “That is what we produce in health care,” said Veenstra. “We don’t make cars; we don’t make phones. We increase people’s length of life, and we improve their quality of life—at least that is our goal. And the QALY captures those.”
Another standard measure in health economics is the incremental cost-effectiveness ratio, which is defined as the difference in cost between two interventions divided by the difference in their effectiveness. This metric can fall into four different quadrants on what is called a cost-effectiveness plane (see Figure 3-1). The best result is when outcomes improve and costs go down. The worst is when outcomes become worse and costs increase. Most interventions in health care result in higher costs with improved outcomes, Veenstra said, which makes CUAs useful for comparing these interventions. For example, the cost per life year saved may be $10,000 for one intervention and $200,000 for another intervention. In this case, money may be more effectively spent on the first intervention.
In the United States, however, there is not a clear threshold on how much money society is willing to spend to save a life for 1 year, said Veenstra. “You might hear people [say] $50,000 per QALY. In reality, it is probably closer to $100,000 or more in this country.” Nevertheless, this approach provides a way to determine whether an intervention is reasonable.
Whether genome sequencing is cost-effective depends on the outcome that is being measured, Veenstra said. These outcomes could be measured in