CLIENT:
Winnipeg Regional Health Authority CASE STUDY
Winnipeg, Manitoba, Canada
Simulation Model Study: Reducing Patient Arrival Batch Size Decreases Patient Waiting Time While a Canadian public health system was in the early planning stages for a new regional dialysis infusion center, they wanted to remove inefficiencies from their patient arrival and hook-up process. Unable to grasp the impact patient arrival schedules had on infusion hook-up wait times, they desired a quick way to evaluate the differences before making a decision.
CHALLENGE
EXECUTIVE SUMMARY
Dialysis center staff were unsure of how
In Canada, healthcare is a public service provided to all citizens. As the cost of
a change to their patient arrival process
health services increases, administration looked for ways to reduce inefficiencies.
might impact staffing and wait times.
An infusion center in Winnipeg was interested to see whether smaller arrival groups
Early in the project, they needed to decide
could improve dialysis patient hook-up efficiency. Array developed a simulation model
how they might adjust their process
to quickly demonstrate the efficiency difference between two patient arrival patterns.
and desired evidence to support their
The simulation took into account two patient types, each with different set up
selection.
durations. Across both patient types, dialysis infusion durations can last between three and four hours. Patients arrive to the center, go to an open infusion bay where a nurse hooks them up, and remain until their treatment is complete, at which point
SOLUTION
they leave the facility.
Strategic Decision Support
We presented two scenarios to our client, which demonstrate the difference between staggering 20 patient arrivals by groups of five over 20 minutes and batching 20
Array was able to quickly model this
patients in one arrival group. For each patient in the different scenarios, we measured
system’s problem using discrete event
the length of time from arrival to the start of set up.
simulation. The model was designed to answer a simple question, “How do
The model demonstrated a significant reduction in patient waiting time between
patient arrival patterns impact patient
arrival and hook-up when staggering arrivals by groups of five. Additionally, we
waiting times?” We designed the model
presented an option to stagger nursing shift arrivals to help minimize the cost of
using high-level patient arrival data and
staffing and align staffing with patient volumes. By visualizing the possible scenarios,
combined different arrival strategies with
we were able to provide concrete evidence of potential efficiency gains.
various nursing options. The simulation results provided the data necessary for the team to make a quick decision.
PROJECT HIGHLIGHTS
4
Staffing Options
9
Fewer People Waiting
10 min. Wait Time Reducation
CLIENT PROFILE Winnipeg Regional Health Authority Winnipeg, Manitoba, Canada
Problem In an infusion center, a large group of 20 patients are asked to arrive for the same appointment time. These patients are all led to their bed and wait while eight nurses set up and begin treatment on only eight patients at a time. While a nurse attends to the first patient, the unlucky last person is waiting. In a facility like this, that last
The Winnipeg Regional Health Authority
patient might wait more than 10 minutes before a provider sets up and begins their
(WRHA) is one of the largest, most diverse
treatment.
health regions in Canada. It is responsible
Patients don’t like waiting and health systems try their best to reduce patient waiting
for providing healthcare to more than
time. By asking smaller groups of patients to show up at staggered times, systems
700,000 people living in the City of
can drastically reduce patient waiting time. Array developed a short simulation
Winnipeg, as well as the surrounding
model to show how systems can achieve these shortened patient wait times without
Rural Municipalities of East and West St.
incurring cost.
Paul and the Town of Churchill, located in northern Manitoba.
In this simulation, there are two types of patients: 40% fistula (green) and 60% central line (red). Fistula patients have a set-up time between six and 15 minutes.
The WRHA also provides healthcare
Central line patients have a set-up time between three and 10 minutes. All patients
support and specialty referral services
have treatment duration of three to four hours.
to nearly 500,000 Manitobans who live outside its boundaries, as well as residents require the specialty referral services and expertise available in Winnipeg. www.wrha.mb.ca
Batch
of northwestern Ontario and Nunavut, who
Figure 1: Simulation model demonstrating 20 patients arriving at 8:00 am.
TOOL
Batch Arrivals In the model above, providers lead 20 patients to their beds at exactly 8:00 am. Then eight nurses work to begin an infusion treatment and make sure each patient is comfortable. By 8:26 am, all 20 patients have begun their treatment.
Strategic Decision Support
Twenty-six minutes to set up 20 patients might seem like a great turn-around time, but it comes at a cost. Since there are only eight providers, 12 people must wait at
Every day, we make choices. They can
least a small amount of time before a nurse can attend to them. On average, those
be trivial, only affecting a small group;
12 people wait for about 10 minutes before a nurse can see them. Additionally, the
they can also be critical, affecting many
maximum waiting time for a single patient is about 16 minutes.
aspects of an organization. Array’s trusted advisors can assist with your next strategic decision so you can see the impacts of your options before choosing. Utilizing proven techniques, we provide a range of custom analysis options that focus on your specific need.
Page 2 | Case Study
Simple models can show the impact of different options, leading to more informed decisions.
Stagger
TRANSFORMATION Our core mission is the same as that of our clients: improve the quality of our work, increase our efficiency, and motivate our staff to reach for success. At Array, we are establishing a culture of continuous improvement at all levels of our Figure 2: Simulation model demonstrating 5 patients arriving at 8:00 am.
organization. We seek to empower team members to be agents for good change.
Staggered Arrivals
We begin all endeavors by considering
In the model above, patient-arrival times are staggered, with five patients arriving
process before exploring solutions. Our
every 10 minutes. The nursing staff is also staggered, with four providers starting
team can guide your organization through
at 8:00 am, two more starting at 8:10 am and an additional two starting at 8:30
pre-design, ensuring clear goal-setting;
am. By increasing the nursing staff as patients arrive, fewer patients need to wait
target outcomes; process analysis
to begin their infusion treatment. By 8:38 am, all 20 patients have begun their
and design; and decision support. Our
treatment.
Lean-led approach to project definition
While the staggered option completes about 12 minutes after the batch option, the number of patients waiting, and their average waiting time, has drastically decreased. Since the staffing matches the patient arrivals more closely, only three patients must wait before a nurse attends to them. On average, those three people are only waiting about two minutes before being seen, with a maximum waiting time for a single patient of about six minutes.
provides a clear path to the right project before you begin to design.
How can we test strategic planning options? Our team of experts can help you evaluate the strengths and weaknesses of different strategic planning options. Whether you’re making decisions about department adjacencies or trying to analyze the benefits of hiring an additional surgeon, we provide the tools and talent necessary to make the process easier.
Tools used: Figure 3: Experiment results showing effects of increasing initial nursing capacity on patient waiting time and number of patients waiting in stagger model.
Simulation Modeling, Observation, Time Study
Results Array developed an experiment 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. This model is applicable to a number of different situations. A health system could use the results of this experiment to decide how many nurses to begin the day with, and determine whether there could be cost-savings associated with staggered staff starting times. Systems can adjust any of the variables to reflect their individual operating procedures.
Cast Study | Page 3
DISCOVERING YOUR HEALTHCARE SOLUTIONS TOGETHER We are innovators who specialize in the areas your system seeks out to leverage its valuable operational and facility resources. Array Advisors has the expertise and skills to reach beyond your milestones and provide you the decision support you need.
OUR SOLUTIONS
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We are dedicated to improvement.
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Problem-solving and forward-thinking
We are Array Advisors, your trusted partners in Strategy Development, Organizational
individuals lead our efforts, which focus on your unique place in the healthcare delivery spectrum. Our knowledgeable staff can help you solve strategic business problems and develop a method to improve efficiency and utilization.
Transformation, and Facility Informatics. The challenges you face are not unique, but your solutions should be. Through a partnership of Strategy and Transformation we help you achieve and sustain. Our process begins by understanding your current operations and clearly defining your system’s goals before generating options. We employ a variety of integrated methods tailored to your strategic challenges, such as process mapping; operational planning; and healthcare real estate portfolio optimization, to help position your organization for future success.
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Informatics Building Information Model management (BIM) is an enabler of most other technology trends in the Architecture, Engineering, Construction, Operations (AECO) industry, including but not limited to: sustainable design, offsite fabrication, LEAN construction, and energy efficient operations. Carefully considering how best to leverage virtual/digital representations of physical buildings can provide significant returns on innovation throughout the entire lifecycle of your facilities.
Strategy The need for healthcare real estate portfolio optimization has never been greater. With the acceleration in mergers and acquisitions, as well as the evolution of clinical models, healthcare organizations must continuously evaluate their physical assets and maximize the value they derive from them.
Transformation Transformation and lean methods are very useful when focusing on operational process improvement. By bringing all constituents together and giving them the tools to experiment and test new ideas, current state barriers can be identified and transcended.
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Published: FEBRUARY 2016