I hope this link stays active long enough for anyone interested to read it. It makes an interesting point about public policies that are "bad bets" that have a strong human factors component.
Consider this example: There are two people who are very sick and require medical care that costs $25,000 to treat. Person A has a 50% chance of getting better with treatment. Person B has a 5% chance of getting better with treatment. You can either:
1) give Person B the treatment
2) give Person A the treatment
3) split the money and half treat them both, which reduces their chance of improving by 90% (so it would be 5% and 0.5% respectively.
Most people would select option 2. It gives the best bang for the buck. But what if there is no Person A. We can either:
1) treat person B and have a 5% chance of having an effect
2) distribute the $25,000 in medical care to other people in general, who have an average chance of improving of 50%.
3) distribute the $25,000 to the entire population to spend however they want.
Now which one should we do? Option 2) in the second situation is identical to option 2) in the first example in its effect. So if you preferred option 2) in the first example, you can't choose option 1) in the second. But the problem faced in our health care system is that when we are faced with a real Person B on one hand and a vague, unseen population on the other, we find it very hard not to treat person B and hope for the best. And the when we have a lucky 5%-er, it makes the news and makes it even harder to choose option 2) the next time.
This is why our health care system is so wasteful. We keep funding the bad bets because we can't look at a sick person and say no.