Posted on 11/17/2009 11:56:26 AM PST by the invisib1e hand
So you see, women over age 50 are substantially less likely to receive an "intervention" -- that's how Dr. Emanuel refers to medical care -- than those in the 40 - 50 age bracket. Fewer intenventions means less money spent. The patients, like the customers of that trucking company, be damned.
Obama Attacking women, where is N.O.W.?
Have the figures upon which this chart is based been normalized - i.e., do they reflect the fact that there are fewer women over age 50 (e.g., because their age cohorts have diminished in number due to attrition)?
Do these figures also reflect that pre-menopausal woman perhaps seek medical attention more frequently than woman in their 60s and 70s?
And where is the rest of the curve, for woman in their 80s and 90s?
Regards,
Ohhhh.....I see now. The maximum bennies are for those in the 20-30yr old range.....who are typically still going to college, starting their careers and living off that 55yo Mom who won’t get much to keep her healthy...
Couldn’t agree more. Ezekial Emanuel is a boob. He may even be a boob who hates boobs because of this change in recommendation for mammograms.
But what about the number of women who die because they don't get early diagnosis, was presented as "only 0.7$" per 1,000. That was not translated into number of women who will die as a result of this cost-cutting change of medical policy. The number of women who would lose their lives because of this change, is 70.
Seventy women will die in every group of 1,000 American citizens who are women between ages 40 and 50. The total deaths therefore will be in the hundreds of thousands. This is an example of a "death panel." It has shown the blood cost of government-controlled medical care.
Congressman Billybob
what are the implications of these questions?
So, there are 20 million women in that age group who will no longer receive routine mammograms. Apply the Panel's o.7% death rate to that group. It means that 140,000 American women will die as a result of this policy change. If that isn't a “death panel,” I don't know what is.
John / Billybob
My questions imply that the graph - while factually correct - may nonetheless be misleading.
Can you answer my questions?
Regards,
However, I can surmise that, since the line is a probability, and that a probability is a ratio in which the denominator is the universe of possible events in question, that "normalization" for population sizes across the spectrum had to have occured.
I'd have to refer you to Dr. Emanuel or his co-author for more info.
Well, in fact I did answer your question. You asked what the implications of these [my ]questions were.
I answered:
My questions imply that the graph - while factually correct - may nonetheless be misleading.
In other words: I have difficulty deriving usable, real-world information from a graph in which the Y-axis is labelled merely "probability of receiving intervention." You can read virtually anything you want into such a lapidary label.
What does "probability of receiving intervention" actually mean?! Does it mean: "Probability that women REQUIRING or DEMANDING intervention actually GET that intervention?" Or does it mean: "Probability that a woman chosen randomly (i.e., regardless of any actual need) from the given age-cohort will receive medical attention?" Importantly: Does it take into account (in statistics: does it weight)) the fact that, in absoulte terms, the cohort of 70 to 80-year-olds is smaller than the cohort of 40 to 50-year-olds? Does it take into account that the NEEDS of an average individual in a given cohort might be greater/smaller than the needs of a randomly chosen individual from a different cohort?
Consider, for example, what it would be like if this graph were about MEN. The average man between 20 and 30 years of age hardly ever seeks medical treatment. The average man between 70 and 80 very frequently (in comparison) seeks such assistance - BUT THERE ARE A LOT FEWER OF THEM, since many of them have died off.
Further, I would expect the Y-axis to be marked with at least a "zero" and a "one."
In short: I am honestly unable to draw any practical conclusions from a graph without knowing whether it has been normalized (to reflect demographics). I bet, for example, that a 105-year-old woman has a much higher chance (probability) of receiving attention than anyone else, because she's likely in a nursing home, where she's been interviewed on "60 Minutes."
However, I can surmise that, since the line is a probability, and that a probability is a ratio in which the denominator is the universe of possible events in question, that "normalization" for population sizes across the spectrum had to have occured.
You are not surmising: You are ASSUMING.
Regards,
As I said, you can google up the paper from which it comes and satsify those spurious curiosities there.
There is no need for personal animosity. I was only calmly posing a few simple questions (like “Is the curve normalized?”)
Regards,
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