Blink_ The Power of Thinking Without Thinking - Malcolm Gladwell [53]
5. When Less Is More
Why is the Cook County experiment so important? Because we take it, as a given, that the more information decision makers have, the better off they are. If the specialist we are seeing says she needs to do more tests or examine us in more detail, few of us think that’s a bad idea. In Millennium Challenge, Blue Team took it for granted that because they had more information at their fingertips than Red Team did, they had a considerable advantage. This was the second pillar of Blue Team’s aura of invincibility. They were more logical and systematic than Van Riper, and they knew more. But what does the Goldman algorithm say? Quite the opposite: that all that extra information isn’t actually an advantage at all; that, in fact, you need to know very little to find the underlying signature of a complex phenomenon. All you need is the evidence of the ECG, blood pressure, fluid in the lungs, and unstable angina.
That’s a radical statement. Take, for instance, the hypothetical case of a man who comes into the ER complaining of intermittent left-side chest pain that occasionally comes when he walks up the stairs and that lasts from five minutes to three hours. His chest exam, heart exam, and ECG are normal, and his systolic blood pressure is 165, meaning it doesn’t qualify as an urgent factor. But he’s in his sixties. He’s a hard-charging executive. He’s under constant pressure. He smokes. He doesn’t exercise. He’s had high blood pressure for years. He’s overweight. He had heart surgery two years ago. He’s sweating. It certainly seems like he ought to be admitted to the coronary care unit right away. But the algorithm says he shouldn’t be. All those extra factors certainly matter in the long term. The patient’s condition and diet and lifestyle put him at serious risk of developing heart disease over the next few years. It may even be that those factors play a very subtle and complex role in increasing the odds of something happening to him in the next seventy-two hours. What Goldman’s algorithm indicates, though, is that the role of those other factors is so small in determining what is happening to the man right now that an accurate diagnosis can be made without them. In fact — and this is a key point in explaining the breakdown of Blue Team that day in the Gulf — that extra information is more than useless. It’s harmful. It confuses the issues. What screws up doctors when they are trying to predict heart attacks is that they take too much information into account.
The problem of too much information also comes up in studies of why doctors sometimes make the mistake of missing a heart attack entirely — of failing to recognize when someone is on the brink of or in the midst of a major cardiac complication. Physicians, it turns out, are more likely to make this kind of mistake with women and minorities. Why is that? Gender and race are not irrelevant considerations when it comes to heart problems; blacks have a different overall risk profile than whites, and women tend to have heart attacks much later in life than men. The problem arises when the additional information of gender and race is factored into a decision about an individual patient. It serves only to overwhelm the physician still further. Doctors would do better in these cases if they knew less about their patients — if, that is, they had no idea whether the people they were diagnosing were white or black, male or female.
It is no surprise that it