The good news is 50,000 fewer deaths, along with health improvements and saving money. The bad new is that the rate of hospital-acquired conditions basically fell from one patient in every seven patients to one out of every eight. Sure, hospital-acquired conditions will never fall to zero. But it certainly looks to me as if at least tens thousands of lives were being lost each year because that rate had not been reduced, and that tens of thousands of additional could be saved be reducing the rate further.
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Robin Hanson has observed that:
1. Some medical interventions clearly prolong life.
2. On average, medical interventions do not prolong life.
He infers from this that the successful interventions must be offset by interventions that make things worse.
True, but there could be interventions that 1. do not prolong life but 2. do have a positive expected value.
Maybe that hip replacement doesn’t increase your expected life span when you take into account possibility of surgical death, etc, but that doesn’t mean the expected value of such a procedure isn’t still positive.
We can offer another charitable explanation. Good doctors know this, thus the “first, do no harm” guideline. So, only seek medical intervention when you are on death’s door. Since patients may have some asymmetric information, they may likewise seek medical interventions at points of unlikely recovery. Then doctors do something and post hoc death rates are high.
Are all observed increases in life expectancy definitively explained by other factors?
While closing hospitals could end deaths due to hospital acquired infections, no one should conclude that would decrease overall deaths.
If many more people concluded that then overall deaths likely would decrease.
Isn’t it a good thing that only 1/8 of the patients get a hospital-acquired condition, instead of 1/7?
Can’t a selection effect explain #2, and therefore undermine Hanson’s inference?
People who go to the doctor are . . . sick.