RE: UMMM hasn't this been done?

[Guest guest]

I wonder how their mathematical formulas will calculate fatigue (during

the shift by running all over the place), burnout (by continued running

all over the place) and replacement of staff due to fatigue and burnout

as well as the potential liability caused by human errors due to fatigue

and burnout.

This might work if we were running 8-hour shifts, but 24s? Sounds like a

recipe for potential disaster.

Barry Sharp, MSHP, CHES

Program Coordinator

Tobacco Prevention & Control

Texas Dept. of State Health Services

Barry.Sharp@...

________________________________

From: texasems-l [mailto:texasems-l ] On

Behalf Of

Sent: Tuesday, June 17, 2008 4:36 PM

To: texasems-l

Subject: UMMM hasn't this been done?

ScienceDaily (Jun. 17, 2008) - Every extra second it takes an ambulance

to get to its destination can mean life or death. But how, besides

driving faster, can ambulances get emergency services to people in need

as efficiently as possible, every day? It's a classic operations

research question that three Cornell researchers are tackling in

groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing

associate professor of operations research Shane , assistant

professor of operations research Huseyin Topaloglu and applied

mathematics Ph.D. student Mateo Restrepo to work on this problem. They

are seeking to perfect a computer program that estimates how best to

spread ambulances across a municipality to get maximum coverage at all

times.

The researchers are working on a computerized approach to take such

available information as historical trends of types and incidences of

calls, geographical layout and real-time locations of ambulances to

figure out where ambulance bases should be, and where ambulances should

be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said.

The easy part is knowing what an ideal system should look like. The hard

part is anticipating various outcomes in a limited period of time, like

the falling blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews

to various bases and sending them back to their assigned locations once

finished with a call.

Going back to base isn't necessarily the best option for maximum

efficiency, say the operations researchers. It might be better to

redeploy an idle ambulance to where coverage is lacking, even though no

calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're

ignoring what's going on in real time in the system, "

explained. The concept is easy enough, but the solution is tricky,

especially because of the enormous amount of uncertainty involved.

The field of operations research that deals with making decisions over

time in the face of uncertainty is called dynamic programming, in which

Topaloglu is an expert. The key is coming up with what's called a value

function, a mathematical construction that estimates the impact of a

current decision on the future evolution of the system. In this case,

it's the impact of current ambulance locations on the number of future

calls that are served on time.

" When you're trying to make a decision, you have to select the locations

of your ambulances so the performance predicted by the value function is

as good as possible, " Topaloglu explained. " But it turns out that

computing that function is very difficult, especially if you're talking

about the scale of the problem we're trying to solve. "

has more than 10 years of experience working on such problems,

using a technique called simulation optimization, which is modeling

different scenarios of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the

technology used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole

responsibility of the author. They do not necessarily reflect the

thoughts, feelings, or opinions of my employer, or any other group or

organization that I may be, am perceived to be, have been or will be

involved with in the future. They are my own comments, submitted freely

and they are worth exactly what you paid for them.

[Guest guest]

All systems use something, based in science or not, about how and where to place

ambulances.? The dreaded " SSM " title which is usually used to refer to a

flexible deployment model can always stand to be studied and researched more to

show its viability and to answer questions like Barry brings up.?

To answer one of Barry's questions...if an agency is using a totally flexible

deployment model and having their staff work on 24 hour shifts then they are

doomed to failure....just as bad as any agency that has units running 18+ calls

in 24 hours and continues to work them in a 24 hour format.? Get a copy of the

A/TC EMS study...and how they responded.? We shouldn't try and combine the two

separate issues...there are plenty of 24 hour; " station based " agencies that are

creating the same disaster because they knowingly expect their crews to work for

24 hours without any sleep...

Now, back to the " SSM " discussion...in the system I was in that did this very

well, and worked hard to balance employee needs with the needs of our customers,

we worked 11 hour shifts with the first 15 minutes and last 45 minutes dedicated

to getting in and out of service...so it worked out to a 10 hour shift...and

never having your sleep interrupted to go on a call, working hard on a busy day

knowing in less than 10 hours you would be on your way home, and working a

schedule I could bid upon that met my needs (I worked 1800 to 0500; W-Sat...)

was cake...3 days off a week...home every night (or day...for us vampires) was

really nice.?

I for one look forward to the results of this.? These are also the type of folks

who could look into the question we all have about 911 calls....why it is quiet

for hours then all of a sudden a whole host of calls come pouring in for " no

reason " ....I wish I was educated in " chaos theory " .?

Dudley

UMMM hasn't this been done?

ScienceDaily (Jun. 17, 2008) - Every extra second it takes an ambulance

to get to its destination can mean life or death. But how, besides

driving faster, can ambulances get emergency services to people in need

as efficiently as possible, every day? It's a classic operations

research question that three Cornell researchers are tackling in

groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing

associate professor of operations research Shane , assistant

professor of operations research Huseyin Topaloglu and applied

mathematics Ph.D. student Mateo Restrepo to work on this problem. They

are seeking to perfect a computer program that estimates how best to

spread ambulances across a municipality to get maximum coverage at all

times.

The researchers are working on a computerized approach to take such

available information as historical trends of types and incidences of

calls, geographical layout and real-time locations of ambulances to

figure out where ambulance bases should be, and where ambulances should

be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said.

The easy part is knowing what an ideal system should look like. The hard

part is anticipating various outcomes in a limited period of time, like

the falling blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews

to various bases and sending them back to their assigned locations once

finished with a call.

Going back to base isn't necessarily the best option for maximum

efficiency, say the operations researchers. It might be better to

redeploy an idle ambulance to where coverage is lacking, even though no

calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're

ignoring what's going on in real time in the system, "

explained. The concept is easy enough, but the solution is tricky,

especially because of the enormous amount of uncertainty involved.

The field of operations research that deals with making decisions over

time in the face of uncertainty is called dynamic programming, in which

Topaloglu is an expert. The key is coming up with what's called a value

function, a mathematical construction that estimates the impact of a

current decision on the future evolution of the system. In this case,

it's the impact of current ambulance locations on the number of future

calls that are served on time.

" When you're trying to make a decision, you have to select the locations

of your ambulances so the performance predicted by the value function is

as good as possible, " Topaloglu explained. " But it turns out that

computing that function is very difficult, especially if you're talking

about the scale of the problem we're trying to solve. "

has more than 10 years of experience working on such problems,

using a technique called simulation optimization, which is modeling

different scenarios of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the

technology used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole

responsibility of the author. They do not necessarily reflect the

thoughts, feelings, or opinions of my employer, or any other group or

organization that I may be, am perceived to be, have been or will be

involved with in the future. They are my own comments, submitted freely

and they are worth exactly what you paid for them.

[Guest guest]

Does anybody remember " System Status Management " that was used in Tulsa and

Kansas City in the early to mid 1980s? & nbsp; I wish that I could get a grant to

" study " and " develop " something old and sell it as a new concept. & nbsp; If I did

that, I would be prosecuted for fraud.

& nbsp;Todd

Amarillo, Texas

From: & lt;spiband@... & gt;

Subject: UMMM hasn't this been done?

To: texasems-l

Date: Tuesday, June 17, 2008, 4:36 PM

ScienceDaily (Jun. 17, 2008) — Every extra second it takes an ambulance to get

to its destination can mean life or death. But how, besides driving faster, can

ambulances get emergency services to people in need as efficiently as possible,

every day? It's a classic operations research question that three Cornell

researchers are tackling in groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing associate

professor of operations research Shane , assistant professor of

operations research Huseyin Topaloglu and applied mathematics Ph.D. student

Mateo Restrepo to work on this problem. They are seeking to perfect a computer

program that estimates how best to spread ambulances across a municipality to

get maximum coverage at all times.

The researchers are working on a computerized approach to take such available

information as historical trends of types and incidences of calls, geographical

layout and real-time locations of ambulances to figure out where ambulance bases

should be, and where ambulances should be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said. The easy

part is knowing what an ideal system should look like. The hard part is

anticipating various outcomes in a limited period of time, like the falling

blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews to

various bases and sending them back to their assigned locations once finished

with a call.

Going back to base isn't necessarily the best option for maximum efficiency, say

the operations researchers. It might be better to redeploy an idle ambulance to

where coverage is lacking, even though no calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're ignoring

what's going on in real time in the system, " explained. The concept is

easy enough, but the solution is tricky, especially because of the enormous

amount of uncertainty involved.

The field of operations research that deals with making decisions over time in

the face of uncertainty is called dynamic programming, in which Topaloglu is an

expert. The key is coming up with what's called a value function, a mathematical

construction that estimates the impact of a current decision on the future

evolution of the system. In this case, it's the impact of current ambulance

locations on the number of future calls that are served on time.

" When you're trying to make a decision, you have to select the locations of your

ambulances so the performance predicted by the value function is as good as

possible, " Topaloglu explained. " But it turns out that computing that function

is very difficult, especially if you're talking about the scale of the problem

we're trying to solve. "

has more than 10 years of experience working on such problems, using a

technique called simulation optimization, which is modeling different scenarios

of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the technology

used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole responsibility of the

author. They do not necessarily reflect the thoughts, feelings, or opinions of

my employer, or any other group or organization that I may be, am perceived to

be, have been or will be involved with in the future. They are my own comments,

submitted freely and they are worth exactly what you paid for them.

[Guest guest]

,

Hey you are from my neck of the woods!! Spearman to be exact. Well any ways, we

had system status and it is really a poor way to guess where calls or the volume

may come from. I was part of that management team. The best bet is to use the

tier system which occasionally fails as well.

  Stan Brandt CCEMT-P,CISM,FPC

Director of EMS

This document may contain information covered under the Privacy Act, 5 USC

552(a), and/or the Health Insurance Portability and Accountability Act (PL

104-191) and its various implementing regulations and must be protected in

accordance with those provisions. Healthcare information is personal and

sensitive and must be treated accordingly. If this correspondence contains

healthcare information it is being provided to you after appropriate

authorization from the patient or under circumstances that don’t require patient

authorization. You, the recipient, are obligated to maintain it in a safe,

secure and confidential manner. Redisclosure without additional patient consent

or as permitted by law is prohibited. Unauthorized redisclosure or failure to

maintain confidentiality subjects you to application of appropriate sanction. If

you have received this correspondence in error, please notify the sender at once

and destroy any copies you have made.

UMMM hasn't this been done?

To: texasems-l

Date: Tuesday, June 17, 2008, 4:36 PM

ScienceDaily (Jun. 17, 2008) — Every extra second it takes an ambulance to get

to its destination can mean life or death. But how, besides driving faster, can

ambulances get emergency services to people in need as efficiently as possible,

every day? It's a classic operations research question that three Cornell

researchers are tackling in groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing associate

professor of operations research Shane , assistant professor of

operations research Huseyin Topaloglu and applied mathematics Ph.D. student

Mateo Restrepo to work on this problem. They are seeking to perfect a computer

program that estimates how best to spread ambulances across a municipality to

get maximum coverage at all times.

The researchers are working on a computerized approach to take such available

information as historical trends of types and incidences of calls, geographical

layout and real-time locations of ambulances to figure out where ambulance bases

should be, and where ambulances should be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said. The easy

part is knowing what an ideal system should look like. The hard part is

anticipating various outcomes in a limited period of time, like the falling

blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews to

various bases and sending them back to their assigned locations once finished

with a call.

Going back to base isn't necessarily the best option for maximum efficiency, say

the operations researchers. It might be better to redeploy an idle ambulance to

where coverage is lacking, even though no calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're ignoring

what's going on in real time in the system, " explained. The concept is

easy enough, but the solution is tricky, especially because of the enormous

amount of uncertainty involved.

The field of operations research that deals with making decisions over time in

the face of uncertainty is called dynamic programming, in which Topaloglu is an

expert. The key is coming up with what's called a value function, a mathematical

construction that estimates the impact of a current decision on the future

evolution of the system. In this case, it's the impact of current ambulance

locations on the number of future calls that are served on time.

" When you're trying to make a decision, you have to select the locations of your

ambulances so the performance predicted by the value function is as good as

possible, " Topaloglu explained. " But it turns out that computing that function

is very difficult, especially if you're talking about the scale of the problem

we're trying to solve. "

has more than 10 years of experience working on such problems, using a

technique called simulation optimization, which is modeling different scenarios

of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the technology

used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole responsibility of the

author. They do not necessarily reflect the thoughts, feelings, or opinions of

my employer, or any other group or organization that I may be, am perceived to

be, have been or will be involved with in the future. They are my own comments,

submitted freely and they are worth exactly what you paid for them.

[Guest guest]

Ugh computers will solve all our problems and by 2000 we will live in a

paperless society. Explains why I buy paper by the pallet load at my office!

LNM from Baku, AZ

- UMMM hasn't this been done?

ScienceDaily (Jun. 17, 2008) — Every extra second it takes an ambulance to get

to its destination can mean life or death. But how, besides driving faster, can

ambulances get emergency services to people in need as efficiently as possible,

every day? It's a classic operations research question that three Cornell

researchers are tackling in groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing associate

professor of operations research Shane , assistant professor of

operations research Huseyin Topaloglu and applied mathematics Ph.D. student

Mateo Restrepo to work on this problem. They are seeking to perfect a computer

program that estimates how best to spread ambulances across a municipality to

get maximum coverage at all times.

The researchers are working on a computerized approach to take such available

information as historical trends of types and incidences of calls, geographical

layout and real-time locations of ambulances to figure out where ambulance bases

should be, and where ambulances should be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said. The

easy part is knowing what an ideal system should look like. The hard part is

anticipating various outcomes in a limited period of time, like the falling

blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews to

various bases and sending them back to their assigned locations once finished

with a call.

Going back to base isn't necessarily the best option for maximum efficiency,

say the operations researchers. It might be better to redeploy an idle ambulance

to where coverage is lacking, even though no calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're ignoring

what's going on in real time in the system, " explained. The concept is

easy enough, but the solution is tricky, especially because of the enormous

amount of uncertainty involved.

The field of operations research that deals with making decisions over time in

the face of uncertainty is called dynamic programming, in which Topaloglu is an

expert. The key is coming up with what's called a value function, a mathematical

construction that estimates the impact of a current decision on the future

evolution of the system. In this case, it's the impact of current ambulance

locations on the number of future calls that are served on time.

" When you're trying to make a decision, you have to select the locations of

your ambulances so the performance predicted by the value function is as good as

possible, " Topaloglu explained. " But it turns out that computing that function

is very difficult, especially if you're talking about the scale of the problem

we're trying to solve. "

has more than 10 years of experience working on such problems, using

a technique called simulation optimization, which is modeling different

scenarios of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the technology

used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole responsibility of the

author. They do not necessarily reflect the thoughts, feelings, or opinions of

my employer, or any other group or organization that I may be, am perceived to

be, have been or will be involved with in the future. They are my own comments,

submitted freely and they are worth exactly what you paid for them.

[Guest guest]

,

That was exactly my thoughts when I read this. I didn't post it to get the

whole SSM fight going again because that has been done to death.

Dave

Todd wrote:

Does anybody remember " System Status Management " that was used in Tulsa and

Kansas City in the early to mid 1980s? I wish that I could get a grant to

" study " and " develop " something old and sell it as a new concept. If I did

that, I would be prosecuted for fraud.

Todd

Amarillo, Texas

Subject: UMMM hasn't this been done?

To: texasems-l

Date: Tuesday, June 17, 2008, 4:36 PM

ScienceDaily (Jun. 17, 2008) — Every extra second it takes an ambulance to get

to its destination can mean life or death. But how, besides driving faster, can

ambulances get emergency services to people in need as efficiently as possible,

every day? It's a classic operations research question that three Cornell

researchers are tackling in groundbreaking ways.

A National Science Foundation grant of almost $300,000 is allowing associate

professor of operations research Shane , assistant professor of

operations research Huseyin Topaloglu and applied mathematics Ph.D. student

Mateo Restrepo to work on this problem. They are seeking to perfect a computer

program that estimates how best to spread ambulances across a municipality to

get maximum coverage at all times.

The researchers are working on a computerized approach to take such available

information as historical trends of types and incidences of calls, geographical

layout and real-time locations of ambulances to figure out where ambulance bases

should be, and where ambulances should be sent once finished with a call.

The whole process is not unlike the puzzle game Tetris, Restrepo said. The easy

part is knowing what an ideal system should look like. The hard part is

anticipating various outcomes in a limited period of time, like the falling

blocks in the video game.

Using their program, the researchers are recommending that ambulance

organizations break the traditional setup of assigning ambulance crews to

various bases and sending them back to their assigned locations once finished

with a call.

Going back to base isn't necessarily the best option for maximum efficiency, say

the operations researchers. It might be better to redeploy an idle ambulance to

where coverage is lacking, even though no calls have yet been placed there.

" If everyone is constantly going back to the base assigned, they're ignoring

what's going on in real time in the system, " explained. The concept is

easy enough, but the solution is tricky, especially because of the enormous

amount of uncertainty involved.

The field of operations research that deals with making decisions over time in

the face of uncertainty is called dynamic programming, in which Topaloglu is an

expert. The key is coming up with what's called a value function, a mathematical

construction that estimates the impact of a current decision on the future

evolution of the system. In this case, it's the impact of current ambulance

locations on the number of future calls that are served on time.

" When you're trying to make a decision, you have to select the locations of your

ambulances so the performance predicted by the value function is as good as

possible, " Topaloglu explained. " But it turns out that computing that function

is very difficult, especially if you're talking about the scale of the problem

we're trying to solve. "

has more than 10 years of experience working on such problems, using a

technique called simulation optimization, which is modeling different scenarios

of what could happen in any given industrial system.

He and a colleague have already commercialized an earlier generation of

emergency medical system planning, which now forms the basis for the technology

used by the New Zealand ambulance company Optima.

The comments contained in this correspondence are the sole responsibility of the

author. They do not necessarily reflect the thoughts, feelings, or opinions of

my employer, or any other group or organization that I may be, am perceived to

be, have been or will be involved with in the future. They are my own comments,

submitted freely and they are worth exactly what you paid for them.