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Simulation Model Study: Reducing Patient Arrival Batch Size Decreases Patient Waiting Time By: Laura Silvoy, Healthcare Systems Engineer
Batch
An infusion center is interested in seeing if smaller arrival groups can
Batch Nurse Initial Capacity
Batch Average Wait (minutes)
Option 1
8
10.26
15.84
12
decrease patient waiting time. Array developed a simulation model to study
Option 2
8
10.27
16.00
12
this concept. Two types of patients, each with different set up durations,
Option 3
8
10.28
15.99
12
are modeled. In each scenario, 20 patients are set up for dialysis treatment.
Option 4
8
10.29
16.04
12
For each patient, the length of time from arrival to the start of set up was
Stagger Nurse Initial Capacity
Stagger Average Wait (minutes)
Stagger Maximum Wait (minutes)
Stagger Number Waiting
Option 1
2
5.36
9.78
7.41
Option 2
3
4.52
7.79
4.62
Option 3
4
3.79
6.05
2.36
Option 4
5
0.00
0.00
0.79
Scenario
Scenario
Stagger
ABSTRACT
Batch Maximum Wait (minutes)
Batch Number Waiting
measured. This will be called “waiting time.” The first scenario, “batch,” demonstrates what happens to waiting time when all 20 patients arrive to the System at once. The second scenario, “stagger,” demonstrates the effect on waiting time when patients arrive in smaller groups of five, every 10 minutes.
About Laura Laura’s background in both architecture and healthcare systems engineering provides a unique blend of proficiency around the built environment, improvement methodologies and analytical approaches. Armed with technical expertise and the philosophies of lean, Laura transforms high-level process mapping data into digestible information clients can utilize as they work toward an ideal future state. About Array Architects We are a team of architects and designers with unique backgrounds, but we all have one thing in common – we share a strong desire to use our expertise and knowledge to design solutions that will help people in moments that matter most. This focus makes us leaders in our field. Together, we discover optimal solutions with our clients. It’s our four decades of specialization that allow for effective communication, collaboration and precision in the complex, changing world of healthcare.
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Simulation Model Study: Reducing Patient Arrival Batch Size Decreases Patient Waiting Time In an infusion center, a large group of twenty patients are asked to
In the top model, 20 patients are led to their beds at exactly
arrive for the same appointment time. These patients are all led to
8:00 am. Then eight nurses work to begin an infusion treatment
their bed and wait while eight nurses set up and begin treatment
and make sure each patient is comfortable. By 8:26 am, all 20
on only eight patients at a time. While the first patient is attended
patients have started their treatment.
to, the unlucky last person is waiting. In a facility like this, that last patient might wait more than 10 minutes before a provider sets
Twenty-six minutes to set up 20 patients might seem like a great turn-around time, but it comes at a cost. Since there
up and begins their treatment.
are only eight providers, 12 people must wait at least a small
Patients don’t like waiting and Health systems try their best
amount of time before a nurse can attend to them. On average,
to reduce patient waiting time. By asking smaller groups of
those 12 people wait for about 10 minutes before they are seen.
patients to show up at staggered times, patient waiting time can
Additionally, the maximum waiting time for a single patient is
be drastically reduced. This short simulation model shows how
about 16 minutes.
Systems can achieve these shortened patient wait times without incurring cost.
In the bottom model, patient arrival times are staggered, with five patients arriving every 10 minutes. The nursing staff is also
In this simulation, there are two types of patients: 40% fistula
staggered, with four providers starting at 8:00 am, two more
(green) and 60% central line (red). Fistula patients have a set
starting at 8:10 am and an additional two starting at 8:30 am. By
up time between six and 15 minutes. Central line patients have
increasing the nursing staff as patients arrive, fewer patients
a set up time between three and 10 minutes. All patients have a
need to wait to begin their infusion treatment. By 8:38 am, all 20
treatment duration of three to four hours.
patients have started their treatment.
Batch Nurse Initial Capacity
Batch Average Wait (minutes)
Option 1
8
10.26
15.84
12
Option 2
8
10.27
16.00
12
Option 3
8
10.28
15.99
12
Option 4
8
10.29
16.04
12
Stagger Nurse Initial Capacity
Stagger Average Wait (minutes)
Stagger Maximum Wait (minutes)
Stagger Number Waiting
Option 1
2
5.36
9.78
7.41
Option 2
3
4.52
7.79
4.62
Option 3
4
3.79
6.05
2.36
Option 4
5
0.00
0.00
0.79
Batch
Scenario
Stagger
Scenario
Batch Maximum Wait (minutes)
Batch Number Waiting
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Simulation Model Study: Reducing Patient Arrival Batch Size Decreases Patient Waiting Time
While the staggered option completes about 12 minutes after the
This model can be applied to a number of different situations. A
batch option, the number of patients waiting, and their average
health system could use the results of this experiment to decide
waiting time, has drastically decreased. Since the staffing
how many nurses to begin the day with, and determine whether
matches the patient arrivals more closely, only three patients
there could be cost-savings associated with staggered staff
must wait before a nurse attends to them. On average, those
starting times. Systems can adjust any of the variables to reflect
three people are only waiting about two minutes before being
their individual operating procedures.
seen, with a maximum waiting time for a single patient of about six minutes. An experiment was developed to test the impact of starting the stagger model with different numbers of nurses. As expected, the results show that as the initial nursing capacity for staggered patients increases, the number of patients waiting, and the duration of the wait decreases.
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