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Ensuring the feasibility of a $31 million OR expansion project: Capacity planning, system design, and patient flow Presenter: Todd Roberts, Memorial Health System The second workshop in our series will look at a recent project at Memorial Health System (MHS) in Illinois. Todd Roberts, System Director of Operations Improvement at MHS will discuss and demonstrate the use of discrete simulation modeling to analyze floor design and throughput for a new Rapid Clinical Examination provider model for a 70,000 annual visit, Level I trauma center emergency department at a 507 bed, tertiary, urban, academic medical center and flow for all aspects of architectural design proposal for $31 million dollar operating room expansion project, including pre-op admission, transport to OR, OR time, and post-anesthesia care units (PACU) for admitted and outpatient surgery. Through the use of discrete simulation modeling, Memorial has reduced length to stay for non-admitted patients in the emergency department by 27%, reduced percentage of patients leaving by without treatment by 50%, and released admit hold time by 37% while improving patient satisfaction from the 57th to 99th percentile (Press Ganey). In addition, Memorial has used simulation to determine the appropriate facilities layout for its new OR expansion project, determining that optimizing the flow of traffic will lead to a reduction of 30 minutes per case in wasted movement and waiting.
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Memorial Health System
Discrete Event Simulation
Todd S. Roberts, MBA, CLSSMBB
System Director, Operations Improvement
Memorial Health System
May 15, 2013
Systems thinking is the ability to see things as a whole (or holistically), including the many different types of relationships between the diverse elements of a complex system
Necessary component of “learning organizations”
Takes cause-and-effect thinking to a higher level and encourages the user to see not just the linear causal connections but also the web of causal interconnections that come into play in real systems
“The Fifth Discipline”
“Adjusting the system or process
inputs to produce the best possible
average response with minimum
variability”
System Optimization
The sensitive
dependence on initial
conditions, where a
small change at one
place can result in
large differences to a
later state.
Butterfly Effect
Three types of failures in complex systems:
– Procedural
• Failure to adhere to/execute a defined process
• Single, obvious mistakes
• Special-cause variation
• Plan, Do, Check, Act or corrective action
– Engineered • People, process, materials
• Common-cause variation
• Defined processes
• Lean Six Sigma projects
– System • Complex interactions between processes and risk factors
• Difficult to understand and pinpoint cause and effect relationships
• Discrete event simulation
Failure in Complex Systems
Simulated floor design and throughput for new Rapid Clinical Examination provider model for a 70,000 annual visit, Level I trauma center emergency department at a 507 bed, tertiary, urban, academic medical center
Simulation was constructed using floor layout schematic and provider resource models based upon historic hourly ED arrival (Poisson) and service distribution rates (exponential) for high, mid, and low acuity patients as well as admitted vs. discharged dispensation
ED Flow Redesign Project
Goals of the simulation model were as follows:
– Determine the most efficient model for routing patients through the system (high acuity patients to main ED, low acuity patients to rapid clinical examination)
– Determine the number of provider resources necessary for staffing based upon patient distribution
– Determine primary macro factors affecting length of stay for all patients
– Identify process constraints and bottlenecks
– Identify factors contributing to increased patient wait time and patients leaving without treatment (LWOT)
ED Simulation Goals
Determined the appropriate routing model for patients to the main ED and the Rapid Clinical Examination process
The provider mix was adjusted to accommodate peak volumes throughout the day in an effort to minimize wait times and LWOTS
A number of Lean Six Sigma projects were chartered based upon the findings of the Simulation model, including time from imaging complete to discharge, lab turnaround time, and CT utilization and turnaround time
Simulation Results
EMERGENCY DEPARTMENT RAPID CLINICAL EXAMINATION MODEL POST-IMPROVEMENT DATA
UCL
285.2
CL
208.9
LCL 132.5
104
154
204
254
304
354
404
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Ove
rall
LOS
Date
Overall Length of Stay
16% Improvement
UCL
231.8
CL
154.7
LCL 77.6
49
59
69
79
89
99
109
119
129
139
149
159
169
179
189
199
209
219
229
239
249
259
269
279
289
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12
06
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31
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27
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RC
E LO
S
Date
Rapid Clinical Examination Length of Stay
26% Overall Improvement
UCL
356.2
CL
259.6
LCL 163.0
130
155
180
205
230
255
280
305
330
355
380
405
430
455
480
505
530
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Mai
n E
D L
OS
Date
Main ED Length of Stay
16% Improvement
UCL
4.83%
CL
1.27%
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
10.00%
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LWO
T as
% o
f To
tal V
olu
me
Date
Left Without Treatment (LWOT) as % of Total Volume
53% Improvement
ED Admitted Patient Average Length of Stay (minutes) 2nd consecutive month below 200 minutes & 1st month below 100 minutes
UCL
211.908
CL
125.017
LCL 38.125
4.70
104.70
204.70
304.70
404.70
504.70
604.70
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Ad
mit
Re
qu
est
to
Ch
eck
ou
t A
vera
ge
Date
ED Admit Request to Checkout Average
50% Improvement
Emergency Department Patient Satisfaction over 80th%ile for 3nd consecutive month & 2nd consecutive month at 98th%ile or above . 2nd quarter FY 2013 99th%ile .
– May 2012 – RCE Launch
– July 1, 2012 – RCE Fully implemented 7 days/week
– August 17, 2012 – RCE Red Flag criteria change (based on Simulation)
– January 21, 2013 – 4th lane of RCE added (Based on Simulation)
– April 9, 2013 – ED facilities remodeled to support process flow
Key Process Changes
Simulate flow for all aspects of architectural design proposal for $31 million dollar operating room expansion project, including pre-op admission, transport to OR, OR time, and post-anesthesia care units (PACU) for admitted and outpatient surgery
Test assumptions for capacity based on an expansion of 5 operating rooms (and pre-op/PACU beds) and increased volumes of 15% over the next 5 years
OR Renovation Design Simulation
2 Elevators
3 Elevators
Operating Room Opportunity Cost = $54/minute
Identified process bottlenecks and determined that with a surge of patients transported to the OR for first and second-case starts, that two elevators from the pre-op holding area to the ORs is not adequate for flow, and will lead to staff, physician, and patient dissatisfaction while increasing overall variation by 30 minutes per case throughout the day.
Decision was made to add a third elevator to the design to satisfy flow demand
The discovery of downstream increase in variation could not have been achieved and recognized using static waiting line models.
Simulation Results
Lean Six Sigma projects have been chartered to
streamline scheduling processes and OR room
turnover processes to further reduce variation
and increase capacity
Studies conducted for projected increased
volume year over year have allowed the building
of adequate facilities for the next 20 years
Next Steps
Requires deep process understanding (avoid tampering)
Creates a shared visual understanding of the process for all parties
Allows for observational analysis and modification without physical intervention in a complex environment (offline trial and error)
Supports improved decision-making through management by fact
Discrete Event Simulation Benefits
