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>>> That's not actually correct. <<<

Your narrative appears to support my simple explanation.

With respect to chaos, I don't think our overly-simplistic

explanations are expansively dissimilar.

>>> . . . you can't predict with any certainty whether a particular

element exists or has a given value. <<<

With extrapolation of chaos, it is theoretically possible to predict

those events and characteristics with absolute certainty; it only

requires values for an infinite number of variables which

practically, of course, is impossible.

>>> The problem with EMS is that the number of variables is much,

much too high to be able to compute. You would have to be able to

know far too many details . . . <<<

This is what I said.

>>> You can predict where higher call volumes are likely (population

centers, certain communities, etc.) or when higher call volumes are

likely - but the actual existence or location of any given call is,

for all intents and purposes, random. <<<

The chaos theory holds that these " random " events have order and can

be understood, given the values of an infinite number of variables.

If I can predict where higher call volumes are likely, I make the

prediction with the values of fewer variables. The more variables I

know, the more accurate my prediction.

Mike, thanks for the dialogue.

Kenny

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Kenny -

You make a classic mistake - confusing randomness with chaos.

When a system is random, the outcomes are not correlated in any fashion. That

is, if I roll a six-sided die 100 times, randomness allows for all 100 rolls to

come up " 1 " because the results of any subsequent roll aren't reliant on any

past roll.

When a system is chaotic, future events are directly dependent both on the

immediate past event and the entire combinatorial series of past events, a la

the Lorenz attractor. The next " motion " of the attractor is bound by the

current (last) vector and the prior motion of the series.

EMS is random. Although the calls dispatched may seem related and predictable,

it's simply not the case. The call from the patient suffering from a TIA isn't

related to the call for the patient who was just stung by a bee and is having an

allergic reaction any more than the numbers in the addresses are related, the

age of the patient's parents are related, or the astrological signs of the

paramedics on the trucks are related.

When we look at managing and placing public safety resources, we place them

where they are most likely to serve the greatest need. In many places that's a

simple process that's much aided by population densities (i.e. you get more

calls where there are more people) or special populations (you're more likely to

get a call at a nursing home because of the additional needs of those patients).

But even with all of that information, the actual calls are still random.

The Santa Fe Institute has a good explanation of this at

<http://www.santafe.edu/~gmk/MFGB/node2.html>. From that site:

" The game of Roulette is an interesting example that might illustrate the

distinction between random and chaotic systems: If we study the statistics of

the outcome of repeated games, then we can see that the sequence of numbers is

completely random. That led Einstein to remark: ``The only way to win money in

Roulette is to steal it from the bank.'' On the other hand we know the mechanics

of the ball and the wheel very well and if we could somehow measure the initial

conditions for the ball/wheel system, we might be able to make a short term

predict ion of the outcome. "

What we've done with EMS is fooled ourselves into believing that our short term

accuracy somehow relates to our long-term prospects. In reality, it's just a

random string of 1's on our dice rolls...

Mike :)

>

> Subject: Chaotic rebuttal

> To: texasems-l

> Date: Wednesday, June 18, 2008, 9:24 PM

> >>> That's not actually correct. <<<

>

> Your narrative appears to support my simple explanation.

>

> With respect to chaos, I don't think our

> overly-simplistic

> explanations are expansively dissimilar.

>

>

> >>> . . . you can't predict with any certainty

> whether a particular

> element exists or has a given value. <<<

>

> With extrapolation of chaos, it is theoretically possible

> to predict

> those events and characteristics with absolute certainty;

> it only

> requires values for an infinite number of variables which

> practically, of course, is impossible.

>

>

> >>> The problem with EMS is that the number of

> variables is much,

> much too high to be able to compute. You would have to be

> able to

> know far too many details . . . <<<

>

> This is what I said.

>

>

> >>> You can predict where higher call volumes are

> likely (population

> centers, certain communities, etc.) or when higher call

> volumes are

> likely - but the actual existence or location of any given

> call is,

> for all intents and purposes, random. <<<

>

> The chaos theory holds that these " random " events

> have order and can

> be understood, given the values of an infinite number of

> variables.

> If I can predict where higher call volumes are likely, I

> make the

> prediction with the values of fewer variables. The more

> variables I

> know, the more accurate my prediction.

>

> Mike, thanks for the dialogue.

>

> Kenny

>

>

> ------------------------------------

>

>

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>>> You make a classic mistake - confusing randomness with chaos. <<<

Thanks, but I know the difference between randomness and chaos.

>>> EMS is random. <<<

I am not disagreeing (or supporting) your position. What I am

suggesting is that my experience demonstrates that events I formerly

believed to be completely random turned out not be random at all. I

make room for the possibility that the distribution of ambulance

responses may not be as completely random as many people believe.

I once believed (because I was taught) getting cardiac arrest

patients intubated was critical to their short-term survival. Data

that is more recent suggests otherwise.

I am always willing to reconsider my position (regardless

of " correct " I think I am).

Thanks for the website. It is very interesting.

Kenny

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