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2013 East Coast
User Group Meeting
Balancing Patient Satisfaction and
Staff Efficiency: Logistics of Meal
Delivery
December 11, 2013
SIMUL8 Corporation | SIMUL8.com | [email protected]
1 800 547 6024 | +44 141 552 6888
Presenter
Seth Hostetler
Process Engineer, Care Support Services
Geisinger Health System
• Care Support Services includes Supply Chain and Enterprise
Pharmacy
• Been with Geisinger for 2+ years
• Educational background is in Industrial Engineering and Operations
Research
• Member of IIE, SHS, and INFORMS
Heal • Teach • Discover • Serve Copyright Geisinger Health System 2013
Not for reuse or distribution without permission
Geisinger Health System Confidential and Proprietary
Agenda
• Introduction and objectives
• Approach and the proposed system
• Phase 1 Modeling
• Experiment
• Results and insights
• Recommendations and future directions
• Phase 2 Modeling
• Model adjustments
• Operational strategy testing
• Analysis and recommendations
• Complete experimental results
| 3
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Introduction
• Geisinger Medical Center’s (GMC) food service
department was planning a transition to on-demand,
room service style delivery of meals to inpatients in 2013
• 18 inpatient units, approx. average census = 360
• Excludes inpatient psych unit
• The new system will result in:
• Changes in resource management and requirements
• Changes in process and employee roles
• Changes in patient service
| 4
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Objectives
1. Create a representation of the new food service
delivery process in a simulation environment
2. Use simulation to show how changing system
parameters will affect patient service levels and
resource requirements
3. Through model analysis, create operational
recommendations for the forthcoming system changes
| 5
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The Model and the Team
• This work is based on a model that we have been using
building and working with since 2010
• Original model was developed by a consulting group,
Efficiency Engineers
• Geisinger did not have the in-house expertise to create
• Able to leverage consulting expertise to develop the complex
model
• Helped to gain buy-in from senior leadership to help develop the
process engineering team
• Model was handed off to the engineering to for further
development and use
• Phase 1 of this work was the thesis research of an
Industrial Engineering Masters student at Penn State | 6
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The Internal Logistics Simulation Model
• Captures all support service functions within GMC
• 19 inpatient units
• 33 outpatient clinics
• 51 ancillary service departments
• Captures food delivery to:
• Med/Surg. Units
• Adult critical care units
• Women’s and Children’s
| 7
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Internal
Logistics
Simulation
Model
2.1 Miles of Hallway
38 Elevators
11 Floors
199 Network Nodes
160 Destinations
35 Transport Groups
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Modeling the New Food Services System
• Three delivery zones
• Dispatch timer on carts
• Once the first tray is placed on a cart a timer is set
• The cart will leave when it is full or when the timer
expires, whichever occurs first
• Nearest neighbor delivery route
• Cart and staff resource modeled as one entity
• Always a host to travel with a cart
• Three meals per day
• Approximately 1060 meals served between 5:30am
and 9:30pm
| 9
Zone A Zone B Zone JK
AGP4 GP2 WILL1
AICU4 SCU3 CH2
SCU4 SCU5 CH3
AGP5 BP5 HfAM7
ICS5 BP6 HfAM8
AICU5 BP7
BP8
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The Delivery Process
| 10
Patient orders
meal
Is there a
cart
waiting for
that zone?
Initiate new
cart for the
zone
Add meal to
zone cart
Is cart at
capacity
?
Has the
time limit
been
met?
Wait for
another meal
or until time
limit met
Send trays for
delivery
N
Y
N
Y
N
Y
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Input Data
• Distribution of meal orders
• Estimate of meal delivery count every 30 minutes
• Patient census snapshot
• Time to serve meal to patient
• Estimated with time studies
• ~59 seconds to serve meal
• ~49 additional seconds for isolation patient
• 10% of patients modeled as isolation status
• Travel speed
• 185 feet/min
| 11
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Key Performance Measures
PATIENT SATISFACTION
• Service time
• Wait time on cart before
routing
• Percent delivered after
30*, 40, 45 and 50
minutes
OPERATIONAL EFFICIENCY
• Cart utilization
• Maximum number of
carts used*
• Number of delivery trips
made in a day
| 12
* Management chose these two metrics as the most important.
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The Phase 1 Experiment
• Carts modeled as an unlimited resource
• Three dispatch times
• 8, 10, or 12 minutes
• Three cart capacities
• 12, 14 or 18 trays
Which combination of dispatch time and cart
capacities would be most effective?
| 13
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Results
| 14
Service Time Max Number of Carts Number of Delivery Trips
Parameters Minutes Cart Capacity Average 95% CI Average 95% CI Average 95% CI
8 12 17.22 (17.15, 17.29) 16.00 (15.83, 16.17) 242.60 (241.40, 243.80) 8 14 17.20 (17.13, 17.27) 15.93 (15.66, 16.21) 242.70 (241.39, 244.01) 8 18 17.23 (17.17, 17.29) 15.90 (15.72, 16.08) 243.23 (241.64, 244.82)
10 12 19.23 (19.16, 19.30) 14.63 (14.45, 14.82) 206.53 (205.36, 207.70) 10 14 19.31 (19.23, 19.38) 14.64 (14.46, 14.83) 205.00 (203.77, 206.23) 10 18 19.31 (19.23, 19.39) 14.37 (14.18, 14.55) 205.43 (204.39, 206.47) 12 12 20.97 (20.89, 21.04) 13.70 (13.53, 13.87) 179.60 (178.82, 180.38) 12 14 21.20 (21.11, 21.30) 13.27 (13.10, 13.43) 177.77 (176.79, 178.75)
Cart Utilization
Wait Time on Cart Before Routing
Percent delivered after 30 min Parameters
Minutes Cart Capacity Average 95% CI Average 95% CI Average 95% CI 8 12 0.3613 (0.3597, 0.3629) 4.78 (4.77, 4.80) 2.06 (1.83, 2.29) 8 14 0.3086 (0.3068, 0.3105) 4.80 (4.78, 4.83) 2.00 (1.78, 2.21) 8 18 0.2399 (0.2387, 0.2412) 4.80 (4.78, 4.81) 2.10 (1.92, 2.29)
10 12 0.4235 (0.4210, 0.4259) 5.80 (5.82, 5.77) 5.67 (6.02, 5.32) 10 14 0.3660 (0.3640, 0.3681) 5.83 (5.81, 5.85) 6.08 (5.78, 6.38) 10 18 0.2850 (0.2835, 0.2864) 5.85 (5.83, 5.87) 5.97 (5.59, 6.35) 12 12 0.4878 (0.4856, 0.4899) 6.72 (6.69, 6.76) 10.79 (10.41, 11.16) 12 14 0.4238 (0.4217, 0.4260) 6.81 (6.78, 6.84) 12.04 (11.58, 12.49)
Percent delivered after 40 min
Percent delivered after 45 min
Percent delivered after 50 min Parameters
Minutes Cart Capacity Average 95% CI Average 95% CI Average 95% CI 8 12 0 (0, 0) 0 (0, 0) 0 (0, 0) 8 14 0.003 (-0.003, 0.010) 0 (0, 0) 0 (0, 0) 8 18 0.003 (-0.003, 0.010) 0 (0, 0) 0 (0, 0)
10 12 0.061 (0.026, 0.095) 0 (0, 0) 0 (0, 0) 10 14 0.117 (0.073, 0.161) 0 (0, 0) 0 (0, 0) 10 18 0.199 (0.129, 0.270) 0.013 (-0.003, 0.028) 0 (0, 0) 12 12 0.231 (0.175, 0.288) 0 (0, 0) 0 (0, 0) 12 14 0.434 (0.310, 0.558) 0.010 (-0.001, 0.020) 0 (0, 0)
Dispatch Timer
Cart Utilization
Service Time
Max # Carts
# Delivery Trips
Service Level
Cart Capacity
Cart Utilization
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Interpreting the Results
• These trends reveal a broad theme within the meal delivery system:
A trade-off exists between patient service and efficient use of
resources.
• The 8 minute dispatch timer provides the best performance in terms of
percent of meals delivered beyond each of the time intervals.
• As the dispatch timer increases, the results show an improvement in the
efficient use of resources; however, the factors measuring patient
service perform worse as the timer length grows.
• A cart capacity of 12 meal trays provides the highest utilization for each
of the three dispatch timer settings.
– Cart utilization is the only measure significantly affected by a change in cart capacity.
– For this reason, the 12 meal tray carts were selected. | 15
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Results
| 16
12-Tray Cart Capacity
Max Number of Carts Number of Delivery Trips Cart Utilization
Parameters
Minutes Average 95% CI Average 95% CI Average 95% CI
8 16.00 (15.83, 16.17) 242.60 (241.40, 243.80) 0.3613 (0.3597, 0.3629)
10 14.63 (14.45, 14.82) 206.53 (205.36, 207.70) 0.4235 (0.4210, 0.4259)
12 13.70 (13.53, 13.87) 179.60 (178.82, 180.38) 0.4878 (0.4856, 0.4899)
Percent delivered after 30 min
Percent delivered after 40 min
Parameters
Minutes Average 95% CI Average 95% CI
8 2.06 (1.83, 2.29) 0 (0, 0)
10 5.67 (6.02, 5.32) 0.061 (0.026, 0.095)
12 10.79 (10.41, 11.16) 0.231 (0.175, 0.288)
8 Minutes
10 Minutes
12 Minutes
0
2
4
6
8
10
12
13.5 14 14.5 15 15.5 16 16.5
% D
eliv
ere
d a
fter
30 m
inu
tes
Max Number of Carts
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| 17
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
18.00%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Pe
rce
nt
of
Tim
e in
Us
e
Number of Carts in Use
Usage Profile for the 12-Tray Cart
8 Minutes
10 Minutes
12 Minutes
• Must consider more than just the max number of carts used.
• For example, the 8 minute dispatch timer experiences a count of 17 carts in
use for a period of time in a day, but it is for less than 0.01% of the time.
• A balance must be struck between the need to have a cart available to
deliver meals, and the acceptable limit of time that a meal must wait to be
delivered because it is waiting for a cart.
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Phase 1 Recommendations
• 12 tray cart capacity will provide best cart utilization and
lowest equipment cost
• Depending on dispatch timer setting, trade-offs exist
between:
• Required number of carts (14-17)
• Number of delivery trips (178-244)
• Cart Utilization (35%-49%)
• Service Level (1.83%-11.16% delivered after 30 min)
• Shorter timer will provide better service level
• Longer timer will sacrifice service level for improved
resource usage | 18
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Phase 2 Model
• The operational staff schedule provided did not provide
enough employee hours to satisfy work requirements
• Utilization is greater than 100%
• Combined delivery and pickup processes determined to
enhance service levels
• Estimated approx. 40% reduction in number of trips required
• Inclusion of return process
• Empty cart swapped with cart full of dirty trays on return route
• Return trip route based on a cyclical zone schedule
• Carts cleaned after each round trip
| 19
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Additional Model Assumptions
• Food preparation and cart cleaning time included
• Zone routing for pickup and delivery
• Carts modeled as an unlimited resource
• Cart use limited by number of staff available
• No break times included in resource schedule • At request of management
• Adjustments made to original order distribution to create
a 7am-7pm order estimate | 20
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Performance Measures
1. Service level
– Percent of carts delivered in 45 minutes or less
2. Resource utilization
– Percent of time resources are in use for
delivery/pickup services
3. Scheduled work hours in one day
| 21
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Experimentation Objective
• Determine the optimal staffing schedule,
as well as the most efficient delivery and
pickup routing methods
• Test various daily employee schedules to
determine an hourly schedule which
allows for high service levels and worker
utilization
• Management asked that staff be
scheduled hourly, not by shift
• Ability to flex staff across various tasks
| 22
Example Schedule
Time Staff Count
7am-8am 9
8am-9am 12
9am-10am 12
10am-11am 8
11am-12pm 8
12pm-1pm 13
1pm-2pm 12
2pm-3pm 10
3pm-4pm 9
4-pm-5pm 7
5pm-6pm 9
6pm-7pm 11
7pm-8pm 9
8pm-7am 0
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Delivery and Pickup Routing Scenarios
Testing performed on three scenarios:
A. Standard original operations (3 zones, fixed route
schedule)
B. Modified pickup schedule
• Rotational delivery schedule forces delivery route to begin
from different unit on each trip
• Pickup unit is last unit in delivery schedule
C. Six zone facility layout with original operations
Zone 1 2 3 4 5 6
Units
AGP4 AGP5 GP02 BP05 WLL1 HFAM6
AICU4 AICU5 SCU3 BP06 CHM2 HFAM7
SCU4 ICS5 SCU5 BP07 CHM3 HFAM8
BP08
| 23
Which of these scenarios do you think will be most effective?
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Scenario Testing
• All scenarios tested in a 24-hour simulation period
• Includes routing and staffing variations
• Seven highest performing scenarios tested in 30-day
simulation period
• Reduction of variability
• Testing to maximize service level and utilization
• Minimization of total employee hours used to break “ties”
| 24
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85
80.8 79.75
74.78
94 95
96 97
80
75.86 74.83
69.7
95 96
97 98
90.52
88.4 87.5
83.7
96
98 98 99
60
65
70
75
80
85
90
95
100
105
3 7 6 5
Schedule
Standard Util
Standard Service
Rotational Util
Rotational Service
6 Zone Util
6 Zone Service
2
5
120 129 131 142 | 25
Comparison of Service Level (squares) and Resource Utilization (triangles) for
the 4 best performing staff schedules. Option A: Shown in green, is the standard routing, 3-zone option.
Option B: Shown in red, is the modified, rotational, 3-zone option.
Option C: Shown in blue, is the standard routing, 6-zone option.
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90.52 88.4
83.7
96 98 99
60
65
70
75
80
85
90
95
100
105
110
3 7 5
Schedule
6 Zone Operation Utilization-Service Trade-Off
Utilization
Service
Six Zone Delivery Layout
98% Service Level ~20/meals per day delivered after 45 minutes
88.4 % Utilization 114 hours/day busy (129 total) Schedule 7
Time Staff Count
7am-8am 8
8am-9am 13
9am-10am 12
10am-11am 7
11am-12pm 8
12pm-1pm 13
1pm-2pm 11
2pm-3pm 10
3pm-4pm 8
4-pm-5pm 7
5pm-6pm 10
6pm-7pm 12
7pm-8pm 10
8pm-7am 0 * Schedule 6 was eliminated from comparison because it performed
comparable to Schedule 7, however the utilization was slightly lower
and it used additional scheduled work hours | 26
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Conclusions and Recommendations
• Six zone facility layout allows for best service with least
compromise in employee utilization
• Best found schedule requires 129 hours scheduled for
delivery/pickup services per day • Break times not included in schedule
Zone 1 2 3 4 5 6
Units
AGP4 AGP5 GP02 BP05 WLL1 HFAM6
AICU4 AICU5 SCU3 BP06 CHM2 HFAM7
SCU4 ICS5 SCU5 BP07 CHM3 HFAM8
BP08
| 27
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Final Thoughts
• We chose to use Simul8 due to the ease of use, system
performance, and low-cost
• The simulation model has been great at helping us gain
stakeholder buy-in from various groups
• Allows us to model test of change before implementing in actual
system
• We have used a variety of resources to help us with our
model
• Consultants helped with initial build and continue to help with
difficult problems on an ad-hoc basis
• Students have developed pieces of the model
• Process engineering team provides in-house support
| 28
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Final Thoughts
Keys to Success
• Involve the process stakeholders
• Good communication with the management and staff of the
processes you are modeling is essential.
• Take time to fully understand the system
• Do the job, or shadow the job, to truly understand the processes.
• Gather accurate data
• Don’t always just trust system to provide good data, you may
need to manually collect the data yourself.
• Build and test iteratively
• Build the model in small pieces and constantly test it to make
sure your model is performing how you desire.
| 29
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THANK YOU FOR ATTENDING!
WHO HAS QUESTIONS?
Seth Hostetler
Geisinger Health System
570-214-7029 30 |