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Balancing Lives Against Lucre

Risk analysis is no soulless monster of science. It's a valuable way to make choices that help the most people at the least cost.

February 25, 2004|James K. Hammitt and Milton C. Weinstein | James K. Hammitt is the director of the Harvard Center for Risk Analysis. Milton C. Weinstein is the director of the Harvard Program on Economic Evaluation of Medical Technology.

A risk that kills thousands of Americans every year surely seems like something the government should regulate. But what if that risk also comes with a benefit, providing people with a service that improves their lives?

Take the case of cellphones and driving. Drivers using cellphones cause 2,600 deaths and 330,000 injuries in the United States a year, according to our estimates. But Americans are deeply attached to their cellphones and are willing to spend billions of dollars for the convenience and business and social contact that cellphones provide when they are driving. A ban would save lives but deprive people of a benefit they badly want.

The decision is not as obvious as it seems. If you were in charge, what would you do?

In recent years, the Clinton and Bush administrations have put more of these decisions to the test of risk analysis, a decades-old process that attempts to consider comprehensively the complexities inherent in risk. This means studying the nature of the hazard, where we're exposed to it, how much of it we're exposed to and the severity of the consequences (death or something less) -- as well as the benefits and costs of various risk-reduction strategies. Risk analysts try to weigh all these factors, determining how many lives would be saved and how much health would be protected, at what cost, for each given strategy.

After all, money and time are limited, even when it comes to saving lives. And a million dollars spent protecting against one risk might save more lives if spent protecting against another.

Here's a simple example of how risk analysis can work. Some women who get Pap smears are told that their results are uncertain and that they should get follow-up tests every year. Totaled across all the women tested, annual follow-ups cost about $800,000 per year of life saved, according to our analysis. On the other hand, if those women got follow-up tests every two years, the reduction in cervical cancer rates would be almost the same -- while the cost per year of life saved would decline to about $200,000. That means that the healthcare system would save tens of millions of dollars per year that could be used to screen more women or to provide other health benefits.

The implications of risk analysis to policymakers are obvious. Yet to its critics, it is profanity. They say quantifying the value of human lives in dollar terms is an unacceptably cold and mechanistic metric for decision making, that it forces us to decide whether some lives are worth more or less and whether there is, in fact, a limit to what society should spend to reduce fatality risks.

Such valuation indeed seems unpleasant, but in fact we do it all the time in our courts, at our insurance companies and in our own lives. As individuals, we frequently make choices about how much to spend on our own health and safety. Should we buy a new smoke detector? New tires? More comprehensive health insurance? A more expensive but safer car?

We make these decisions based on an intuitive balancing of how much benefit we'll get against how much it will cost and how much we can afford.

In fact, the way risk analysis often sets the value for a life saved is by asking people what they'd be willing to pay to reduce their risk of death by a certain amount, or in some cases by looking at people's spending, to see what consumers actually do pay for various things in their lives that reduce risk. The valuation numbers directly reflect individuals' own choices.

The goal of risk analysis is, in fact, ultimately equitable. Debates about risk are often emotionally heated and charged with competing values. Risk analysis adds a cooler, fact-based perspective, favoring no ideology, no political or corporate agenda. It argues against certain regulations but supports others.

What can be fairer than to use the neutral tools of decision science and risk analysis to sort through a complex world of threats to human and environmental health so we can identify the choices that will do the most people the most good at the least cost?

Let's go back to cellphones.

We estimate that a ban on nonemergency use by drivers would save $43 billion in reduced deaths, injuries and property damage. But by calculating cellphone bills and estimating how much time a month cellphone customers are driving while phoning, we estimate that people are willing to pay about the same amount -- $43 billion per year -- to use their mobile phones while they drive. The benefits and costs of a ban are about the same.

Admittedly, these numbers are only estimates. Risk analysis makes assumptions (for example, no one is precisely sure just how many hours a month cellphone users are at the wheel) that can lead to uncertainties in the results. The numbers above are central estimates, the most likely values that fall within a wide range. But a risk analysis that is open about its assumptions and uncertainties can still offer powerful insights.

Our ancestors lived in a simpler world in which the threats were lions and hunger and the dark. The obvious first choice of what to do about such threats was usually the right one. But we no longer enjoy the luxury of that simplicity. Our modern world, with all its benefits, comes with a bewildering web of threats, and the instinctive response might not be the best.

Thinking logically about the perils we face and carefully analyzing our choices for dealing with them provide an important way to identify solutions that maximize public health and safety.

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