Cost-benefit analysis can kill. The failure to distinguish statistics from arithmetic can kill. In the current debate over mammograms, the number of women projected to be at risk of death due to cost-benefit analysis is about 47,000.
That is the approximate number the United States Preventive Services Task Force projected to die if its recommendations on scaling back mammograms had been accepted. It is their number, if you do the arithmetic, which they apparently did not.
Their statistics say that the life of “only” 1 woman in 1,900 will be saved if mammograms start at age 40 instead of age 50. In other words, a 40-year-old woman’s “risk” of dying from breast cancer in the next ten years is only 1 in 1,900. That seems like no risk at all: 1 divided by 1,900 equals .000526. About half a woman per thousand. Minuscule, right?
Now, how many women in America would be affected?
The most recent (July 2008) census figures say there are about 304 million Americans, of which 50.7 percent are female. That’s about 154 million females. Roughly 80 million of them are under forty and about another 20 million between 40 and 50. Of the 80 million under 40, each one, under the proposed guidelines, would not get a mammogram until age 50. If “only” 1 in 1,900 die as a result, that would be .000526 times 80 million, which equals about 42,000.
In short, moving the mammogram age from 40 to 50 would result in the deaths of 42,000 women now 40 or under, according to the statistics of the United States Preventive Services Task Force. Of the 20 million between 40 and 50, it could mean the deaths of as many as 10,500 women, though the figure may be somewhat lower because half are more than halfway through the critical period. There might be as few as half – say, 5,000 deaths. Adding 42,000 and 5,000, we get a ballpark figure of 47,000 currently alive American females who would die needlessly under the proposed task force restriction on mammograms. Of course, as more are born, the absolute numbers would go up.
What is at issue is called “framing.” The Preventive Services Task Force chose the probability of risk frame: only 1 in 1,900. But the arithmetic frame reveals the more important truth.
Framing, in this case as in so many others, is a matter of life and death. Take the framing in The New York Times (November 18, 2009) in the front-page news analysis by Kevin Sack and in the op-ed by Robert Aronowitz. Sack frames the mammogram debate as the “science of medicine” versus “medical consumerism.” Aronowitz calls it “wishful thinking” that early mammograms could help and speaks of “the very small numbers of lives potentially saved.”
You can see why cost-benefit analysis can kill. Its use isn’t science. Real scientists do arithmetic as well as statistics. Medical science is about real people, not percentages or statistics, especially when large numbers of real people are involved and small differences in risk can produce large numbers of deaths.
The Preventive Services Task Force also uses the “harm” frame. The task force observes that more mammograms mean more false positives and claims that false positives do “harm.” But no science is presented showing that the “harm” done is greater than the deaths of 47,000 women.
What is the “harm?” Anxiety and unnecessary biopsies from false positives are listed as the “harms.” My wife had such a false positive. The anxiety came for economic reasons: she had to wait for a biopsy because no one who could perform one was present when the mammogram was done, due to economic restrictions. The biopsy, when it came, was simple: a needle inserted to withdraw fluid, like taking a blood sample. No harm. If the biopsy had been done immediately, there would have been no need for anxiety. But the task force does not recommend immediate biopsies as a way to eliminate such “harm.”
Aronowitz also claims that the figures show that mammograms haven’t helped prevent breast cancer. He observes that rate of 28 breast cancer deaths per 100,000 people has not changed substantially since the 1950’s, despite more mammography and better treatments. But that could mean, and probably does mean, that there has been an increase in breast cancer offset by earlier detection and better treatment, saving tens of thousands of lives, but not affecting the overall rate. But he did not consider the possibility that the occurrence of breast cancer might have increased, while the rate of deaths did not change because of earlier detection due to mammograms.
I suspect that the real “harm” intended is economic harm – the costs of the “unnecessary” mammograms and biopsies. But the task force gives no figures weighing the economic costs versus the human “cost” of the deaths of 47,000 women. Now, in cost-benefit analysis, a commonly cited figure for the value of an American life is $6.5 million. And 47,000 times 6.5 million is $305,500,000,000. That is, 305 billion five hundred million dollars. Of course, that would be spread over the next forty years, but it’s not clear that such a cost-benefit analysis would make this less than the cost of mammograms and biopsies, all moral issues and human costs aside. Unfortunately, the Preventive Services Task Force doesn’t do the calculation, so my figures may be off. The exact figures are not the point. The point is to go beyond rates to numbers.
In the present debate over health care, economics has become the main issue, but the Preventive Services Task Force hides it by framing. “Cost-benefit analysis” has been reframed as “risk-benefit analysis,” as if the task force were not concerned with “cost” to insurance companies and taxpayers, but rather with “risk” to women. But “risk-benefit analysis” is just cost-benefit analysis, which in turn is what corporations use to maximize profit in the short term. Both cost-benefit analysis and the Preventive Services Task Force were introduced as government institutions by the Reagan administration. They were right-wing moves – part of the strategy to privatize government.
As the Obama administration shifted the health care debate from morality to economics, cost-benefit analysis entered in the form of “evidence-based medicine,” where the “evidence” comes from statistics. This is seen as a major way to reduce the cost of health care. This is where “risk-benefit analysis” is cost-benefit analysis publicly and proudly discussed.
Is such an application of cost-benefit analysis always immoral? Hardly. It can be very useful. But it has to be looked at carefully, as the mammogram example shows. In the mammogram example, low-probability events can have major effects!
When is a case of “evidence-based medicine” that uses cost-benefit analysis an instance of low-probability events that can have major effects – effects serious enough to far outweigh the cost-benefit analysis? This is a serious and difficult question.
It is also a question of concern in the Obama White House. There are three high-powered experts there committed to such questions. One is Ezekial Emanuel, Rahm Emanuel’s brother, who is perhaps the best-known advocate of evidence-based medicine. He is an adviser to Peter Orszag, budget director, who sees medicine as an economic problem. The third is Cass Sunstein, Obama’s administrator of the White House Office of Information and Regulatory Affairs, also known as the cost-benefit czar. Sunstein is known for specializing in low-probability events that have major effects. Political observers should watch how such issues are handled by the administration as they arise.
The official administration reaction is so far against the Preventive Services Task Force recommendation. Health and Human Services Secretary Sebelius has rejected it and said to make no change.
Hooray for Kathleen Sebelius! Tens of thousands of women owe her their lives.
The political fallout has been instructive. Steve Pearlstein, business columnist for The Washington Post (November 20, 2009) attacked Sebelius
as not wanting to save money, but rather promoting waste. This is pretty much what The New York Times position (both front-page analysis and op-ed) seems to be. Most voices on the right have ignored Sebelius’ official response and instead attributed the Reagan-era Preventive Services Task Force’s recommendations to official Obama health care policy, calling it “rationing” health care, while ignoring the fact that most rationing of health care is actually done by insurance companies. As expected, the most radical conservatives have seen this not only as an Obama move, but have likened it to mythical “death panels.”
I stand with Sebelius, and I take it to be the official Obama administration view. When arithmetic is added to statistics, this is a clear case of a low-probability event with major life-and-death consequences for tens of thousands of people. The overly simplistic framings – either accepting or rejecting the cost-benefit analysis without looking further – are dangerous. Just accepting the task force’s recommendation is dangerous to the women of this country, now and in the future. Calling it “rationing” and using it to argue against the health care bills in Congress is dangerous to us all.
As we sit down to Thanksgiving dinner, let us thank Kathleen Sebelius.