I teach at a program that's a little bit different than yours.

Our our health and wellness program has a heavy internship orientation.

So our students spend seven months in a health care architecture firm as part of their curriculum.

So it's a little bit different from yours, but we all have the same goal, and that's to make you successful.

Health care architects in your career.

So what I'm going to talk about today is the one of the areas that I'm the most interested in.

And that's the design of emergency departments.

Just as a question here.

Has anybody in this room ever been a patient in an emergency department?

Raise your hand.

Yeah.

Okay.

All right.

Those that haven't you are very lucky.

But those that have you got some idea of what we're going to talk about.

So what I'm going to try to do and let me warn you, I'm going to move at a very fast pace.

I'm going to try to cover a wide range of topics.

You may not be able to catch everything I'm presenting here, but hopefully it will be an idea that sticks in your mind that when you're dealing with a similar issue, it'll help you.

But what I'm going to try to do is I'm going to give you an overview of how we generally approach planning problems for the emergency service, and the emergency service is really a prototype for other health care pieces.

So you can take what we're talking about with EDS, and you can see how it may apply to other areas.

We're going to talk I'm going to show you how we translate some of the facility concepts into operational issues, and how operational issues impact a facility.

Ideas.

I'm going to show you some case studies of examples.

Can and talk a little bit about events, scenario planning.

And then we're going to have some fun at the end I'm going to show you some wild and crazy student projects that we did, because this is a point in time in your career that you have the privilege of experimenting and doing crazy things, some of which may or may not work out.

But this is the time you want to be doing that.

So that's what we're going to do.

So to start off, when you look at a complex service like an emergency service or surgery or obstetrics etc., there are a number of factors that influence it, and they will affect the design.

So what I try to do in terms of looking at the facility side is work off of theory of Constraints, which is a very similar to lean theory.

And it basically says if you look at a complex system, what you want to do is you wonder, understand what's constraining the flow through that system and focus your energy on trying to relieve that constraint.

And if you're successful, then things should flow through at a more smooth rate, and then something else will bubble up to the top as the constraining variable.

So the idea is this is a continuous improvement process.

You see what's slowing down in our case in the emergency room.

What's slowing down the flow of emergency room patients.

What can we do to relieve that.

We relieve that.

And then something else will bubble up at the top.

So what I do from a facility's point of view is I kind of turn that idea a little bit on its head.

And I said, if we're doing our job right, facilities will not be the constraining variable on the flow of patients through the emergency room.

It'll be something else.

And in most cases, it's the accessibility to the doctor.

But to do that, we need to understand how the emergency room works at peak periods.

If we have the facilities to accommodate peak period demand, then we know that facilities are not going to be the constraining variable on how how well the emergency service works.

So that's the overall framework in which I approach an emergency room problem.

Just this is a very difficult diagram, but it starts to talk about the major pieces.

What I try to do is break the problem up into two major groups of issues.

Those that are outside the control of the emergency service.

Those are called exogenous.

From a systems analysis perspective, the things that affect the emergency room.

But the emergency room can't do anything about it.

So EDI volume, overall volume, the emergency room doesn't control that.

The emergency room has to respond to it.

It's outside of their control hospital.

Strategic planning strategies, other issues of that nature.

Those are what we call external variables.

And then if you flip down to the bottom, you've got the internal things.

That's how do we organize ourselves?

How do we respond to this?

How do we provide care.

Those two pieces then feed together to start to say, what's the key predictor of demand in emergency room?

What do you think that would be?

What would be the key predictor of demand in the emergency room from a facility's point of view, what's the key thing we want to know?

Is how many how many exam rooms?

If you know how many exam rooms, you can start to scale your project.

You know it takes about 750 departmental gross square feet per exam room.

So if you know how many exam rooms you need, you can start to say, all right, this emergency room needs to be about this size.

Then you can start to go in and do your detailed programing and get into design.

So what we want to focus on then is, is how we merge these things together and how we predict the number of exam rooms.

The problem with an emergency service, which is very similar to obstetrics or some of the other services, is a variability in demand.

So I'm going to talk about a few of the constants that we've seen in emergency room design and it's arrival patterns, staffing patterns, procedure times and then overall volume predictors.

So if we look at excuse me, if we look at overall demand, in terms of variability, there are three things in particular that are consistent amongst virtually every emergency room you deal with.

One is seasonality.

And so this is an example of a project I can't remember which project this was.

Oh Newton, Kansas okay.

We would take 5 to 10 years worth of historical monthly data.

And we would average average it out for each month and compare it to the overall average for the year.

So if the average volume for that month is the same as the overall average, it would be one.

So if it's 1.06, that means it's a 6% above the average.

And so we would take that for ten years worth of historical data and see.

And this is pretty typical for the Midwest.

Usually in the Midwest you see a summer peak and then a drop down, and then you might see a winter peak with respiratory issues.

We would assume typically in projecting the number of treatment rooms, that that would be a constant.

We would say whatever happens in the future, we're going to assume it follows that same pattern.

Just to give you some idea how crazy this can go, these are four projects that I've worked on, in my career.

The Blue line.

Does this mean my guess where the blue line is?

Notice the variation?

It goes from 1.2 down to point eight.

In terms of variation, in terms of number of patients arriving in a month, you might want to guess where that is.

Nobody's go ahead.

Pardon?

Colorado.

Well, it's a good guess.

No, but it's wrong.

It's Phoenix.

So you get the snowbird effect.

So if you look at that that emergency room in January is a completely different emergency room than it is in the summer.

And if you designed for the average, you would not be understanding the true nature of what the needs are for that emergency service in terms of peak demand.

Now, the gray when the spikes up in July is kind of a funny one, I'll tell you this one, because I don't think anybody can guess it.

This is Homer, Alaska and Homer.

Alaska has the unique fate of being the amateur salmon fishing capital of the world in July.

And apparently, if you get a fish hook in your thumb, you can deal with that.

If you get a fish hook in your ear, you go to the emergency room.

So this poor emergency room for one month becomes the epicenter of hooks and ear demand.

So that's a little unusual, but just I thought it was kind of fun in terms of what can happen.

The other variable that's usually fairly consistent is day of week.

And what we see is Monday is typically, the busiest day of the week.

Used to be the weekends.

And now it's Monday for a variety of factors.

You trying to get in to see your primary care physician and you can't get a schedule in to see them?

You know, I don't know if you should be going to work or not.

You haven't been feeling good over the weekend.

So you go to the emergency room.

So typically Mondays or the busiest day.

And we would again assume that that's a constant in terms of thinking about the future.

And then the last thing is time of day of arrival.

And this is almost universally constant.

What you see is and I always tell my friends, if you need to go to the emergency room, go at two in the morning, it's your best shot of not having to wait.

But you'll see that thing dip down and then it peaks up, starts to peak up around 10 or 11.

It'll hit its peak around 11:00, and then it'll start to dip back down.

In terms of percentage of patients arriving, usually within about a ten hour span in the middle of the day, you get about 60% of your total patient visits, and that's usually pretty consistent.

Now with pediatrics, there's a little bit of a shift there because it comes a little bit later in the day, but it's usually pretty consistent for pediatrics to.

So the last thing is the hardest one to predict is overall volume.

And what we saw for about the 1980s up until the early 2000 was an incremental 2% growth in eddy volume annually.

What you see now as you look at the chart is things start to get a little weird with Covid and a little recovery from Covid.

There's some policies in place in terms of access to health care for Medicaid that have impacted demand.

So this is really the hardest one to predict.

And one of the tools that I've used in the past that you may want to look into in terms of how you deal with your clients, is scenario planning, and, and scenario planning.

Basically, what we do is we list out all the things that could affect the emergency room, and then we cluster them together in different stories.

And in these stories we would then say, what is the result of this story in the number of treatment rooms, in terms of the volume of demand and with all the other factors that would take place?

Ideally, this is just like a one page summary and it has a funny title to it, so somebody will remember it.

So for example, this is a project I worked on in Chicago and one of the scenarios is Armageddon.

And in this scenario, everything that could possibly go wrong happens together.

And we work that through and say, here's what it means in terms of total volume change in volume over current.

And then we translate that.

And what does it mean in terms of number of exam rooms.

We had another one which was full speed ahead which had no major change.

And then the third one was, Doctor Pangloss.

And I suspect no one here probably knows who Doctor Pangloss is.

Does anybody know Doctor Pangloss?

Okay.

You didn't have literature in high school, did you?

Indeed.

Voltaire's candied the doctor in Voltaire's candied, who always saw everything is the best of all possible worlds was Doctor Pangloss.

Doctor Pangloss would always see the disasters would be happening, and he would say in this the best of all possible worlds.

So on the high side scenario, we had everything that could positively happen together.

So what they gave us, who was a range, and then our goal was to say we're going to pick one of these is our design standard, but we're then we're going to say, can this design adapt to these other scenarios.

So we came up with a base design and it said, right, here's our base design.

Now if Armageddon happens how do we adjust it?

If the Doctor Pangloss, best of all popular worlds possible worlds happens, how do we adjust it?

So this is one way to try to deal with the uncertainty of, planning in a system of this nature.

So, just to wrap this up, in terms of, predicting demand, this is a hypothetical example that I'll return to a little bit later.

This 57,000 annual visits we look at, we first factor out with the monthly demand.

We then factor out.

So you see our peak month is 10% higher.

So in the peak month we see 5200 patients peak day of week.

So 1.05.

So on a peak day we would see 177 patients.

Peak hour we see 10%.

So we work it all down and we get ten patients per hour riding our peak demand.

That's our design goal is ten patients per hour.

So if you just took the 57,000, you divided it into 24 hours and 365 days week, you'd be at 7.4.

So there's almost a 40% differential in terms of peak period.

True demand versus just what taking the averages.

So that's how we start to say our here's our flow through and a peak period that we want to design to.

So that's the external variables.

Then you flip to the internal side.

What we see going on on the internal side today in today's environment is a bunch of redesign strategies that work around lean.

And have you all been exposed to lean at this point?

Okay.

Lean.

Lean is, was originally developed by Toyota for process improvement.

A key component of the lean lean is to eliminate waste, period.

That's what lean is about.

Eliminating waste.

You eliminate waste.

You then you you improve the process.

So if we look at, if we look at emergency rooms, what we start to see is where their waste.

There's a lot of people.

And, doctor, Jody Crane, for example, I've had the privilege of work with and right with is a lean expert E.R.

doctor.

And he points out, what's the value?

What's the value of triage?

Do you go to the emergency room to go to triage?

No, you're going to be seen by a doctor.

So he starts questioning all of these assumptions about why do we have to do this?

What's the value to it?

How will improve the process and flow?

So what you see, for example, in this diagram is indicating what, what we're seeing as a look towards more of a, quick eye, a quick check first encounter and a quick check and immediately determine, are you really sick?

Are you really not sick?

And are you in the between the two for the really sick?

You want to get them directly into a treatment area ASAP.

You don't want to mess around with triage.

For those that are really not sick, they can wait a little bit.

Or they could be handled outside an exam room, for those in the middle.

Then you need to have your traditional assessment type process.

So we look at how to adjust the traditional model of how an emergency rooms are, how they want to work in the future, and to give you a crazy example, this is a, the left here is an emergency room in Syracuse, New York that I worked on that had an absolutely Byzantine, process for admissions because they had built on they had run out of space.

They got a space assigned here, they got space assigned there.

So then they have to decide, does this patient belong here?

Do they belong there?

We obviously don't want to replicate that in our planning or the future.

We want to say you can do something better than that.

So the diagram on the right is still a little complex, but it says, all right, this is where we want to be in the future.

So this is how we want the system to work.

And one of the things that we've seeing now is looking at does every patient have to go into an exam room, or does every patient have to spend their entire time in an exam room?

So there's been a number of models developed.

This is from Montreal project or worked on a long time ago that had a results waiting area that they could do in an initial assessment.

And one of the most significant patient populations to use this type of area is abdominal pain.

You don't know what you're dealing with with abdominal pain, but you need to watch the patient for a period of time.

They don't need to be in an exam room.

They can be in an area where one nurse can observe 30 or 40 different patients if they qualify, and free up the exam room.

And this this has worked very, very well for Jewish Hospital in Montreal.

One of my good friends who just passed away last year was Jim Lennon, who worked with HKS, on a design of a modular unit that is.

Now the patent has been sold to dirt, but it's been installed at Northwestern University in another number of other universities to be a relatively self-contained module that needs only 40 net square foot compared to a standard exam room.

And the US today would be probably 140 net square foot.

So you can get multiple stations in in the same area using a strategy like this where you first do that triage, you do what's called a split flow type model.

Okay.

So now, now we got to turn this into to number of rooms.

And we're going to I'm going to show you three different ways to try to determine the number of rooms.

And then we're going to go into design.

Okay.

So hang with me there.

We got to do the planning first and then we'll get into design.

So the three different models, the first one I, call the the bonehead approach, it says it's basically a calculation and you're all going to need your computer, your, your phones on this because you're going to have to do a calculation here.

Demand over capacity says, what's the demand and what's what's an exam room able to absorb.

So if we look at our situation here, so number of patients times their length of stay divided by what we think, how many, how many minutes of care can be provided by an exam room in a day.

Okay.

So that's seems straightforward.

So it's demand over capacity top creates the demand.

Bottom says this is the capacity.

And that tells us how many exam rooms we need okay exercise.

Tell me how many exam rooms we need.

You look like you've got an answer.

No you don't.

This is kind of like.

Are you as smart as a sixth grader?

Exercise.

Pardon?

24 is magic.

That is the right number.

Okay, so that's pretty straightforward, isn't it?

That's pretty relatively simple calculation.

What's the problem with this approach.

What can you think of what.

Why isn't this necessarily the best way to determine the number of exam rooms?

Well, the key here is that I made an assumption that the maximum utilization I could get out of an exam room, and today is 60%.

Why 60%?

Why not 100%?

What happened if I, if I had 100% utilization out of the exam rooms, what do you think would happen?

How can I get 100% exam, utilization out of an exam room?

Pardon?

I know the only way I can get 100% out of the exam rooms to have a bunch of patients queued up right outside of that exam room.

And as soon as that room is freed, you move another patient in.

So what that would mean in my peak period of analysis is I would have a ton of people in the waiting room because they can't get into an exam room because my exam rooms are being run at 100% utilization.

So the challenge here is what's that right number is is 60%.

Is it 50%.

Is it 80%.

This approach won't tell you that.

So there's a couple other ways we can start to deal with that.

All right here's my pop.

Another pop quiz question for you is anybody have a guess on what they object is on the left side of the screen here.

And I don't expect you to know it.

But you can take a guess.

There's nothing law.

So taking a guess.

No guesses a okay.

Well, back in the early part of the 20th century, before cell phones, if you can imagine that before there were cell phones, there were only landlines.

And landlines were dependent upon what's called a mechanical switching gear, mechanical switching gear, which would route a call to a given line.

Now, in the early part of the 20th century, most phone companies were regulated monopolies, and so they had a limited capital to invest.

So the challenge became how many channels do you build in a given location?

So what happens with a phone call?

Can you predict when a phone call comes in?

Typically not.

Can you predict how long a phone call is going to be?

Typically not.

You notice any parallels here to what we're dealing with.

Can you predict when a patient walks in the emergency room?

Typically not.

Can you can you tell how long they're going to stay in the emergency room?

Typically not, you know, averages, but you can't make an exact prediction.

So this is called a random arrival system with an exponential service time.

The man on the right is, Dutch mathematician named Erlang.

And he developed a set of formulas.

He says, if you tell me the arrival rate and the average length of stay, I can give you an estimate about how many calls will be waiting and how long they'll be waiting for calls, and what kind of utilization you get out of your phone system.

So we're going to do the same thing with emergency rooms.

Now we're going to say, if you can tell me the arrival rate and you can tell me the length of stay in an exam room, I can predict for you how many patients will be waiting to get into exam room, how long they'll be waiting, and what kind of utilization I'll get out of the exam room.

Then you start getting some useful information to look at trade offs.

So, this is the terminology that's used in what's called queuing theory.

Patient rivals are called lambda.

They're the rate in which patients arrive.

You've got the length of the service queue and then you've got the room service utilization.

Now fortunately.

And I will give, give you a copy of this Excel spreadsheet.

Fortunately, there's an Excel spreadsheet that a professor at Cornell University put together.

That would allow you to, do these calculations.

The top part is the input, and the blue part is the output.

And you notice I loaded it with the data from that, 24 exam room 57,000 visit model we were looking at.

So you can see in this case what it's telling us.

If we have 24 exam rooms and arrival rate of ten patients an hour, and we have a two hour length of stay, and this is a little bit tricky, that means that in a given hour, you're only meeting half the length of stay.

That's why that's point five.

What would happen is you would have on average 1.6 patients in the queue, which is not bad.

That's not bad for an emergency room at peak period.

And that the average length of stay would be 0.17 of 60 minutes.

So what is that, 12 15 minutes?

I can't do the math in my head with a tool like this.

Then you can start to do trade offs.

You can do do tests, you can quickly run.

What if I have put 26 rooms?

What if I put 23 and start to get an estimate of the impact.

And so I've used this quite extensively in terms of my planning, for emergency rooms, in terms of a tool to work with a decision makers, because they can grasp it, they can understand what's going on.

Now, the problem with this approach is that you've got to slice off a portion of the day and say, here's my peak period demand.

It doesn't give you what's happening over the rest of the day in terms of the overall system.

So the last method that we typically use is simulation modeling.

And that is I used to have to explain a simulation modeling to kids.

But you've all done enough games now that you have a general idea of what simulation modeling is.

But we've got some pretty sophisticated tools.

Have you done anything with flex sim at all in this class in your classes?

Okay.

All right, let's see if we can get this to work.

I may have to come over here and do.

This.

Well, we had this set up to, We're done, but it's.

It doesn't appear to.

I thought we had it set up.

Anyway, I had a video that I was going to show you that actually showed this.

It actually shows the patients walking through, the staff walking through very sophisticated modeling tools that you can build in all kinds of detail into it.

And it gives you precise predictions of what's going to happen.

Any luck on that?

I must have done.

I must have messed it up somehow.

I think so, Okay, well, we'll see if we can get this video running a little bit later.

See, we need to screw this now.

Okay?

Now, very sophisticated tool here is the biggest problem with it.

Only the people that build the model know how it really works.

I had a project on Saint Louis University, Saint Louis, where the industrial engineers built an incredibly sophisticated model of the emergency room and the observation area to try to predict demand.

And I knew intuitively something was not right.

But the the decision makers had no way of knowing what was going on inside the model, and only because I knew actually the code could I go in and see that they had made a critically wrong assumption about how patients were transferred from the emergency room to the observation area, and it was throwing off all their statistics.

And so there was no way their client could know that.

And that's that's the risk associated with a tool of this nature.

So one thing I have done with great success, well, you see here was quote, as I was saying, we was not doing anything to get it.

Impact of rising emergency department visits.

And this model allowed them, to be built behind that.

Yeah, yeah, we got to get so I think yeah, they, I take the delete that looks like a video.

Here we go.

The flexing health care model you see here was created by that.

Well that click that.

Yeah.

Yeah.

Get that.

The flex and health care model is you see here was created by Baptist Health South Florida.

They wanted to investigate the impact of rising emergency department of business.

And this model allowed them to do just that by testing a few.

What if scenarios.

Specifically, the model centered on two proposed department changes the rapid Care unit, a segregated unit with a streamlined process for lower acuity patients, and rapid evaluation, where a physician evaluates a patient earlier on to get their orders started.

After simulating and experimenting with their model, Black South Florida found an 8% reduction in door to provider time and a 27% decrease in patient length of stay in the rapid.

Here, the rapid evaluation scenario had an even greater impact.

A 46% reduction in door to provider time.

On top of that, the simulation model was used to evaluate and recommend multiple staffing scenarios that covered a variety of budget constraints.

Thanks in part to the results of the simulation study, Baptist Health South Florida has implemented the Rapid Care Unit on a permanent basis and are in the process of implementing rapid evaluation tri flex in health care free today and see how it can.

Oh, and I will skip the sales pitch here.

Okay, so you know you get an idea how sophisticated the tool that no, no go away okay.

So you get some idea how sophisticated some of the tools are you can use today.

But as I was saying, it, all of the key logic is buried inside the code.

And the the model builder understands that the user may or may not understand it.

So one tool that we've used very successfully over 20 years is what we call a paper simulation.

And we'll take an example of the the proposed design will take the busiest day in the previous month.

We'll sit down with the medical staff and we'll actually walk through that day patient by patient.

This is a picture from Brigham and Women's Hospital in Boston, where we were evaluating, change to their emergency room design.

The person at the top end is the E.R.

chief.

The person on the left is a circulating nurse person.

On the right is a triage nurse.

There's an administrator at the bottom, and we walk through.

Every patient said, where would you put this patient and how will it work?

And inevitably, what will happen is you'll get some questions about why are we doing this?

Or why were you doing it this way?

And you'll get some kind of dialog that you don't get out of a simulation model.

And what you also get is some either validation or cross-check against the simulation tool.

So this approach isn't as sophisticated as a simulation tool.

We can't do 100 days in a matter of seconds, but we can walk through a day and really give people a feel for how it works and so I've used this very successfully over 20 years with a number of clients.

How are we doing on time here?

Okay.

All right.

So now we're going to get to design.

Yes okay.

So how do we translate this now that we've got you know how many exam rooms we need.

We know how we want to run the emergency room operationally.

We've gone through a program and now we want to translate this into design.

I'm going to argue that there are fundamentally three different organizational models that we deal with, and each one has a strength and weakness.

Back in a long, long time ago, when I was first in this business, the most common model is what we call in the ballroom model up at the four upper left hand corner.

And that's really when we had open bay areas.

And you could get, you could stand in one spot and you could see a group of patients, and ed volumes were nowhere near what they are today.

And that model worked really well.

But what you see is as our volumes grow and we go from open bay areas to individual rooms, is this starts to get really big.

And what also happens is that blue square, which is the support space, gets out a balance to the red space.

So we end up with more blue space than we need.

So there's a couple of strategies to try to resolve that.

One is to break things into pods.

So if you see at the far right, rather than have everything stretched out, we're going to break it into pods, which means that that balance between the support space and the treatment space is more in line, and we can still see into the patient care areas.

The challenge with the pods scenario is let's say you fill up the left pod, all those beds are full and the next patient arrives.

What do you do?

Do you open up the next pod and you staff the next pod, and you have a 1 to 1 nursing ratio to patient ratio.

Do you have the patient sit outside and wait till there's enough patients to fully fill that second pod?

So the challenge with the pod approach is how you make these what's called breathing in the emergency room.

So from that 2:00 low point up to that 11:00 maximum point, how do you allow this thing to logically, breathe in the pod system as a challenge in terms of how to make that work?

The last model, again, I attribute to my my friend Jim Lennon that I mentioned earlier, and that's a linear type model.

And the theoretical concept is is kind of like a thermometer.

And the idea is that you have a base and then you incrementally can grow that base as the demand increases and you can bring it back down as, as the demand declines.

So let's look at some case studies.

Okay.

And I just wanted to say I showed you some clean models.

There's some variations on that.

These are three, four different emergency rooms that I worked on that follow some of those basic concepts.

But in no way, I mean, they're kind of fun in terms of how different they're going to be.

If we look at a sort of a traditional ballroom type model, this is a project or just worked on in, Colorado Springs, the patients arrive at the lower right hand corner over here.

We can see we don't have a pointer up.

They arrive over here.

They go into four intake rooms.

From those intake rooms, they can be discharged if they're a low acuity.

If they just need a prescription refill or something, they don't even enter the emergency room.

If they're really low acuity, they go into the short stay area where they're treated as in recliners.

And the argument is, if you treat a patient vertically, the staff will tend to treat them differently than if they're horizontal.

So the idea on a really low acuity type patient is keep them vertical, get them there, get them out and get them out of the get out of the space.

And there's a small results waiting area there.

And then you have the main Ed, which was designed to have complete, flexibility and adaptability in rooms, except for the major trauma rooms.

I will say the one thing about this, this emergency room, which was very unique and is very hard, you can't really see it here.

But that is a beautiful view of Pikes Peak.

And there's very few emergency rooms that kind of do that.

But this is, look down that center core area.

And again, the challenge we get in this design is that center core gets really big.

And so you sort of find the staff trying to invent purposes for some of the spaces because they're so big.

This is a project that's under construction now that I worked on in, Lynchburg, Virginia, that really incorporates a number of the ideas that I was trying to describe to you.

And this is designed for.

Right.

If my memory's correct, about nine for 95,000, patient visit volume.

And what they did in the front end is patients come in to get a quick triage.

There's a set of smaller cubicle areas along the bottom there that you can see that if they're really low acuity, they're handled there if there needs some additional but they're not really seriously medical to a super track area.

Each area has its own waiting area.

So the family can come in and be with the patient.

So you can really start to move low acuity patients in and out of the emergency room without getting them into the main Ed.

You'll also notice that we have the imaging area right across from it.

So the idea is again, if I come in and you get to determine, did I sprained my thumb or break my thumb, you can immediately get that down and get a read on it and either discharge you with a sprain or say, we've got a set the bone, whatever.

So, that's the front end.

Then the main ID is this large rectangular type model.

And the idea here is that there are three nursing stations in this, one in each hand and one in the middle.

And the thinking is the two on the right.

On the right would be open 24 hours a day, and the one on the left would open and close based on demand.

So again, it's trying to, but there's still would be the ability to kind of sneak patients in.

And if they needed to into that closed module because there's the exam rooms would be available.

So trying to respond to that kind of demand.

And then the last piece is the behavioral.

And I haven't had a chance to talk much about behavioral care.

But that's a huge issue.

In emergency room to design.

And there's a whole movement now to say, because of the extremely long length of stay that most behavioral patients experience in the emergency room is not good for them to be sitting in an exam room by themselves for that period of time.

Many of them, are safe enough that they don't have to be in the exam room.

So there is a model of caring component in the emergency room.

Care called em care.

That is, based on an approach I was involved in about 20 years ago up in Maine that says for certain patients, you can have them in a large lounge area, and in this case, both large and in an outdoor area where they can, decompress, deal with their medical issues and not have to be locked up in an exam room.

So, this, this is, going to be finished in about a year.

It will be interesting to go back and do a post occupancy and see how that works.

Just to show you an example of a ballroom type, this is one in Springfield that had universal rooms.

Was the concept there.

And then the idea was that you would have a main circulation spine, and then you would have pods on each side.

So you can see what I was talking about earlier, the difficulty if the top pods fill up, how do you if you can't really incrementally open up the lower pods so it becomes a challenge on how you do that.

One solution to this that I've seen, is Marvin Williams with Perkinson.

Wills suggested taking that idea and kind of staggering it.

So you have a little bit of a stagger so you can kind of work your way more like a shape, a serpentine type of relationship.

And I thought that was kind of an interesting strategy.

Then the last approach is the linear model.

So a project I worked on a little rock, Arkansas.

And again, the idea here is this is in an inner core work area.

You can't really see the mouse moving there, can you?

In a core work area with the exam rooms with dual entry exam rooms.

So staff enters on one side, patients and families circulate along the perimeter side.

Staff has basically everything they need on the inside.

And then patients, come in and enter and can leave.

So this is what it looks like on the inside for the staff work area.

And then this is just a typical patient room in this one way for behavior.

We had the drop down, walls to, to protect the patient from the medical system there rather than having dedicated rooms.

The, they did a post occupancy on this about three years ago, and it's worked pretty well.

Staff likes it.

There are some issues with this approach.

One of the biggest issues is my favorite subject croppers.

Where do you put the bathroom?

Do you put the bathroom between the exam rooms and in which case you stretch out the size of the unit, do you put it on the patient side, in which case you don't you lose supervision of the patient if, if they go to use it, do you put it on the inside?

And then you've got patients coming into your core area.

So the one of the big challenges on how to make this kind of a design work is, is how do you deal with the, the patient toilets.

The other problem is that the staff on the inside have no sense of how busy things are going on the outside, so all hell can be breaking loose, and they're in this very pleasant interior work area.

So getting a sense of of chaos that might be going on, you kind of loose that in this interior type model.

So those are three examples of how you design an emergency room today.

I think anybody that works with emergency room designs has an obligation to say, how does this how will we respond to major events?

Because the emergency room will be the front door of the hospital.

If there's a mass shooting, there's a fire, there's a flood pandemic.

The emergency room will be there.

And unfortunately, very few hospitals actually want to deal with that kind of issue.

But, I was involved in a study several years ago with HKS, for the Department of Homeland Security, and we went through a whole bunch of different scenarios about how do you protect the emergency room from, somebody coming up with a bomb?

How do you protect it from pandemics?

How do you allow allow it to surge without building a lot of additional space?

Unfortunately, very few, examples were built out of this.

One that I worked on was in Tampa General and Tampa General.

When we designed the emergency room there, you'll notice that it's lifted up 15ft off the ground.

Well, if they have a category three hurricane, hurricane on Davis Island, the, the the hospital will be 15ft underwater.

So you don't want your emergency room there.

So what that allowed them to do was that they took they lifted the emergency room up and then they made the space underneath it, initially valet parking, but they designed it so it could be an emergency staging area, as I'll show you in a little bit.

The other thing they did is throughout the hospital, they have these metal and they see these compartments, and those concealed compartments have medical gases.

So they can go from 77 treatment spaces to 277 treatment spaces inside the same space.

They took office areas, they allowed them to be converted.

They could they have the medical panels in the office spaces and waiting rooms and corridors.

They put dual head walls in each exam room to allow them to be able to respond.

Because they are the major trauma center for the Tampa area.

So each of those black dots in this diagram illustrates where one of those those medical panels were, and then you can see the dual head walls in the exam room.

And they had toilets in the exam room.

So I did a post occupancy after Covid to say, how did this work for you?

The toilets in the exam room.

Great.

The dual head walls did not work because most of they're dealing with respiratory problems, and they needed floor based equipment, and there wasn't enough space for floor space.

So that didn't work for that particular surge event.

But what they did do is they took the space underneath that was designed to be a mass decontamination area, and they made it their major Covid receiving point.

So you come in in the emergency room and you never penetrate the emergency room.

If you're a suspect patient, you get routed down to the other area.

And that was set up to deal with pandemic and that worked incredibly well.

But I think the key thing is you got to have these kind of discussions, because the emergency room will at some point be a major focal point for some type of surge event.

Okay.

And so now let's have some fun.

I've shown you a lot of serious stuff.

I thought it kind of kind of thing I hope you get to do is students, this was a, a fun exercise I did with a group of students where we said if we could design the future of emergency room care, what might it be?

And what we came up with this was the Jubilance, and the OOB Alliance was an auto driven container that you could put different, different units on to respond to different events.

So, there would be four different modules.

There would be a just a general transport model.

You got to take a patient or pick up a patient, and you could send you balloons out to pick them up or take them home.

There would be an on site response.

So you could take an exam room out and plop it on site and build off of site.

If there's an event happening, there would be a mass decontamination, transport module that allow you to deal with mass to kind of bring it back in.

So the idea would be that you'd have a warehouse full of these different containers, and the depending upon the need, you would just go in and plug in and then go to wherever what you, how you need, need to be.

So then we said, then how do you design the emergency room.

So this is the docking station where the module can come in and discharge the container in that container.

You can then can feed into the emergency room with the decontamination area.

So if there's a High-Risk patient, you can manage them still keep them in the container.

You don't even need to bring them in until they're stable enough.

And then in terms of just ideas, overall emergency room design.

So that area I just showed you is the green area up in the top.

You've got your core exam room in the middle.

On the other side, we had a results waiting area, but outside of each results waiting area, we had a set of doors that would normally be closed but could be opened up.

And then surge didn't just surge demand.

So you could almost do a 3,040% increase in volume just by, an idea like this.

And then that's kind of what it might look like in terms of reality.

But I think the thing is, this is a you're at a point in your education that you should have fun and you should be thinking about ideas like this.

So what I've tried to do is give you an overall idea about how we approach planning, illustrates some of the, how we translate operational concepts into design, show you some case studies, talk a little bit about planning for su, for events, scenarios and having some fun.

Thank you so much, Frank.

Thank you.

Amazing presentation.

And thank you so much for the programing exercises.

Our students really needed those.

Yeah.

So, we have time for one question from the audience.

Students.

Especially those of you who are in the studio working on the behavioral health.

No questions.

It's either really good news or really bad news one or the other.

There's a lot of information.

It is a lot, and I do.

I warned you to put your seatbelts on.

I threw a lot at you.

So we have Grace.

You talked a lot about the calculations for, deciding how many exam rooms you're going to need and prepare for.

How would you say you then break that down even more to decide how many behavioral units and how many for chest pain and and how do we make the spaces more flexible, like.

Yeah, well that's that's a good question.

There's sort of two concepts right now that we're playing with an emergency room design.

One is called a universal exam room type model that says, particularly for the low acuity patients versus the higher acuity.

The challenge is trying to get that balance right.

So if you do what I showed you with those little compartments, like Jim Lennon had done, you can estimate how many you need each side.

But if you're wrong, you're toast.

You know, if you you end up needing more exam rooms than the than the open bay areas.

So one idea is to say, let's make all the physical rooms the same and equip them different so we can put a recliner in a room.

It's bigger than what you would need, but it gives that room.

Adaptability.

Over time, what we would typically try to do is take the ones that are unique, like the trauma service and the behavioral service.

We say we know these are going to need different types of space.

And we'd go through that same exercise I just went through for overall demand just for those pieces.

So we would say, here's the arrival pattern for behavioral patients length of stay.

And we need.

So we would break those out.

What that would typically mean if you if you add up the total rooms needed over time, you're going to get a bigger number than if you just aggregated everybody together.

But that's typically how we would do that.

Thank you so much.

Thank you.

And of course, a friend will be here for a few minutes in case you want to, talk to him and ask additional questions.

But let's wrap up the lecture.

Thank you again, Frank, for joining us.