1-1 Rev. A Printed 04/12/23© 2005 by Sigma Breakthrough Technologies, Inc.
Managing Patient Throughput by Process Improvement to Improve
Quality and Control Cost
Maria MadrigalMaria MadrigalBlack BeltBlack Belt
Sigma Breakthrough TechnologiesSigma Breakthrough Technologies
Rev. A Printed 04/12/23© 2005 by Sigma Breakthrough Technologies, Inc.
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Your TakeawaysYour Takeaways
You will take away from this presentation: In-depth knowledge of the Six Sigma and Lean
methodologies of process improvement
An example of how Six Sigma and Lean concepts can work together in helping hospitals solve problems and increase revenues
Understanding of how two hospitals found outstanding results by using these concepts
Useful ideas on beginning these types of initiatives in your healthcare facility
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IntroductionIntroduction
Before we get started, we want to hear from YOU! What would make this 45 minutes worthwhile of your time?
What initiatives in your facility prompted you to attend this conference?
What tools are you hoping to return with?
Do you want to be entertained? Educated? Both?
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A MeasurementA Measurement
2 308,5373 66,8074 6,2105 2336 3.4
SigmaLevels
Parts per Million Defective
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Practical MeaningPractical Meaning
99% Good 99.99966% Good
Postal System
20,000 Lost Articles of Mail / Hr
Airline System
Two Short/Long Landings / Day
Medical Profession
200,000 Wrong Drug Prescriptions / Yr
7 Lost Articles / Hr
1 Short / Long every 5 Years
68 Wrong Drug Prescriptions
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The Hidden Process YieldThe Hidden Process Yield
ShrinkageShrinkage(waste)(waste)
>95% >95% Customer QualityCustomer Quality
RedoRedoHidden Process
NOTOK
Yield At Measurement
OperationOperationInputsInputs MeasureMeasure FinalFinal‘Yield’‘Yield’ =
OK
Final Yield ignores the hidden process. Final yield performance is a function of post measurement.
65% 65% is notis not 95% 95% ... why not?... why not?
Process1 2 3
90%90%YieldYield
90%90%YieldYield
85%85%YieldYield =
FPY/RTY 81 % 69 %
95%95%YieldYield
4
65 %
>95%>95%‘Yield’‘Yield’
Final Measurement
Process Variation Causes A "Hidden Process"
Increased Cost – Lost Capacity
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Rolled Throughput in HealthcareRolled Throughput in Healthcare
ShrinkageShrinkage(waste)(waste)
>95% >95% Customer QualityCustomer Quality
RedoRedoHidden Process
NOTOK
Yield At Measurement
X-RayX-RayPatient presentsPatient presents
for x-rayfor x-ray
ResultsResults FinalFinal‘Yield’‘Yield’ =
OK
Final Yield ignores the hidden process. Final yield performance is a function of post measurement.
65% 65% is notis not 95% 95% ... why not?... why not?
Process1 2 3
90%90%
X-RayX-Ray
90%90%
Correct TestCorrect Test
85%85%
ResultsResults =FPY/RTY 81 % 69 %
95%95%
ReturnedReturned
4
65 %
>95%>95%‘Yield’‘Yield’
Final Measurement
Process Variation Causes A "Hidden Process"
Increased Cost – Lost Capacity
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Variation Causes DefectsVariation Causes Defects
LSL USL
Poor Support of Robust Product
Functionality
Process Capability
No standard process for
staff membersInadequate
Staffing Needs
Variation in Medical Supplies
No Metrics
Way off Target
Out of Spec.
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Time
Pe
rfo
rma
nc
eBreakthroughs in
Process Performance
GOOD
BAD
3 Sigma (CpK = 1)
6 Sigma (Cpk = 2)
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Changing the Decision Making ProcessesChanging the Decision Making Processes
Decision MakingGrowth Path
Types of ProblemsYou Will Normally Solve
1. Intuition, gut feel, I think …..
2. We have Raw Data and look at it
3. We make graphs / charts of the data
4. We use advanced statistical toolsto evaluate the data
Simple
Complex
How Many Times Have Your Heard This ? “I Think The Problem Is…”
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Overall ApproachOverall Approach
Practical ProblemPractical Problem Statistical ProblemStatistical Problem
Statistical SolutionStatistical SolutionPractical SolutionPractical Solution
y f x x x k ( , , . . . , )1 2
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The Funneling Effect
Optimized Process
30+ Inputs
8 - 10
4 - 8
3 - 6
Found Critical X’s
Controlling Critical X’s
10 - 15
All X’s
1st “Hit List”
Screened List
MEASURE
ANALYZE
IMPROVE
CONTROL
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Triage TeamTriage TeamA.K.A. “Muda Busters!”A.K.A. “Muda Busters!”
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Accelerated Change Event, “ACE”Accelerated Change Event, “ACE”
Time Period
Team Given
Clear Objectives
Team Composition
Support
Timeline
• Lead time reduction • Cost reduction• Yield enhancement• Meet customer demand
• 1/3 are process specialists from area• 1/3 are people related to the area • 1/3 are those from outside of area
• 5 Days Ground Rules
Cannot damage the customer
Cannot permanently “harm” internal operations
Use creativity before capital
AM
PM
MON TUE THU FRIWED
TRAINING
CURRENT STATEMAP
CONCEPT & DETAILDESIGN
“TAKE ACTION”
IMPLEMENTIMPROVEMENTS
REFINE
Stabilize / MeasureIMPROVEMENTS
REFINE CHANGESPREPARE PRESENTATION
PRESENTATION& CELEBRATION
“TAKE ACTION” 14
DESIRED STATEGAP ANALYSIS
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What is Lean?What is Lean?
Lean is the identification and elimination of “Waste” with in a
process
Waste is define as anything that adds cost but Does not add value to the process.
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TYPES OF WASTETYPES OF WASTE
PEOPLE
TYPESOF
WASTE
Processing
Motion
Waiting
FixingDefects
Making TooMuch
MovingThings
Inventory
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Lean Tools UsedLean Tools Used
Value Stream Mapping
SIPOC
Spaghetti Mapping
Shift Transition Score Card
Flow Analysis
Time / Value Mapping
5S
C & E Matrix
Kanban
Visual Workplace
Consensus Building
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ACE Events Focus on ACE Events Focus on Non Value-Added Activity To Reduce Lead Time Non Value-Added Activity To Reduce Lead Time
Reducing value-added (VA) activities usually results in only minor gains
Reducing Non Value-added (NVA, aka Waste) usually results in major lead time reductions without adding resources or capital
Typical company VA NVA Original lead time
Traditional cost reductions VA NVA
Minor improvement
VA NVA Major improvement
Don’ t make capital investments on improving VAs
until the NVAs achieve equilibrium with the VAs
ACE waste reduction
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The Value Stream MapThe Value Stream Map
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Changes In MTCChanges In MTC
Change: Clear criteria at Meeter/Greeter
and in MTC as to which patients can be transferred directly to MTC
Benefits: Reduction in ALOS for MTC
Reduction in load on ER Triage
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Changes In MTCChanges In MTC
Change: Standardize daytime registration & Fast Track after 11pm
Benefits: Reduction in patient ALOS
Cuts registration from 2-3 hours to 15 minutes
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Changes In MTCChanges In MTC
Change: Visible performance tracking metrics
MTC volume
ALOS for discharged
ALOS admitted patients
5s scores
Benefits: Sustain the gains
Pride of ownership
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Changes In MTCChanges In MTCChange: 5s in MTC (everything has a place, everything in its place)
Move nurse station computers to central area Relocate crash carts, eye-trays, Pixus, glove dispensers, slit lamp, fridges, linen Remove unnecessary items Mend exam light Painted Omnicells redesigned, removed unused inventory and repositioned Increased accessibility to & visibility of crash carts
Benefits: Reduced travel time Improved patient / visitor safety Increased workspace efficiency Decreased inventory Increased patient throughput Reduce patient ALOS
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BeforeBefore
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AfterAfter
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MTC Tech Travel To SplintMTC Tech Travel To Splint
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MTC ALOS ImpactMTC ALOS Impact
Before After (conservative)
Process Steps 45 40
VA Time (mins) 48-123 46-121
NVA Time 100-926 95-712
Historical MTC ALOS = 7’30”
End of the week MTC ALOS = 3’04”
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QuotesQuotes
“We have More ‘Blue’ than anything” (blue being waste in the current process”
“Everything that we’re talking about we’ve been trying to change for 2 years”
“I think there are a lot of us that are working against ourselves”
“It usually takes 6 months to move a computer, we’ve moved 3 today”
“It usually takes 2 months to move an Omnicell, we did it in hours”
“These teams could put a man on the moon”
“We’ve achieved more this week than we have in the last year!”
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Lean + Six SigmaLean + Six SigmaLeanLean
Waste Elimination Standard Work Flow Customer PULL
Six SigmaSix Sigma Variation Reduction Scrap / Rework Elimination Process Optimization Process Control
SPEEDSTABILITY & ACCURACY
LEAN + SIX SIGMA = A POWERFUL UNIONLEAN + SIX SIGMA = A POWERFUL UNION
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113-bed hospital located in Central Texas
35 miles south of Austin; 45 miles north of
San Antonio. Out migration has always been
a problem
57.7% of inpatient admissions come through the Emergency Department
Factual InformationFactual Information
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VOC, VOB and Problem StatementVOC, VOB and Problem Statement
Q3 02 Q4 02 Q1 03 Q2 03
2.732.952.902.97
0
0.5
1
1.5
2
2.5
3
3.5
4 Only 27% Patients reported being “Very Satisfied”.
Where do unsatisfactory delays occur? 81 % stated before being taken
to a treatment room. 56 % stated before being
treated by a physician.
Facility had been concerned over customer satisfaction ratings with wait times in the ED. It was thought that people from the community were heading to area hospitals in Austin and San Antonio to receive
care (with shorter waiting times)
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Metrics IdentifiedMetrics Identified
ALOS (Average Length of Stay) Goal to see a 5% reduction in ALOS
Triage to ER Bed Goal of reducing turnaround time by 20 minutes
LWBS (Left Without Being Seen) Goal to reduce LWBS to under 2%
Patient Satisfaction Measured Gallup poll scores in these areas:
ED Overall Satisfaction Wait Time Helpful and Courteous Staff ED Efficiency Speed of Service
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Data CollectionData Collection
LOS (minutes) Triage to ER bed
220.0200.0
180.0160.0
140.0120.0
100.080.0
60.040.0
20.00.0
Median = 34 minutes
Mode = 25 minutes
Fre
qu
en
cy
300
200
100
0
Std. Dev = 29.73
Mean = 42.3
N = 1023.00
Cycle Time from Triage to Bed Using Six Sigma tools, we
began collecting data on variables in the process. We
found that the average waiting time for a patient to be placed in a bed was over 42
minutes!
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Data CollectionData Collection
Tl Length of Stay (LOS) in minutes
675.0625.0
575.0525.0
475.0425.0
375.0325.0
275.0225.0
175.0125.0
75.025.0
Median = 128 minutes
Mode = 55, 90, and 95 minutes
Fre
qu
en
cy
300
200
100
0
Std. Dev = 88.84
Mean = 149.6
N = 1285.00
ALOSWe also found that the
Average Length of Stay for our ED patients was 2.5
hours.
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Using Lean Tools to Drive ResultsUsing Lean Tools to Drive Results
Lean Tools, such as 5S, allowed us to organize the medical supply
closets in the ED. Labels were created, excess inventory
returned and par levels adjusted to provide a savings of over
$32,000.00.
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Result 1: Triage to ER BedResult 1: Triage to ER Bed
Old Process New Process
Average of 19 MinutesAverage of 43 Minutes
Over 50% reduction in overall cycle time!
Observation
Ind
ivid
ua
l V
alu
e
2532251971691411138557291
150
100
50
0
-50
_X=19.2
UCL=48.7
LCL=-10.4
October Direct April
Triage to ER Bed
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Result 2: Average Length of StayResult 2: Average Length of Stay
6005004003002001000
Median
Mean
145140135130125120
Anderson-Darling Normality Test
Variance 7618.62Skewness 1.32885Kurtosis 2.54811N 2587
Minimum 1.00
A-Squared
1st Quartile 80.00Median 123.003rd Quartile 183.00Maximum 680.00
95% Confidence Interval for Mean
139.31
56.75
146.04
95% Confidence Interval for Median
120.00 127.00
95% Confidence Interval for StDev
84.97 89.73
P-Value < 0.005
Mean 142.68StDev 87.28
95% Confidence I ntervals
Summary for LOS
Old Process New Process
Variation of 29 MinutesVariation of 87 Minutes
Over 60% reduction in overall variation!
18016014012010080
Median
Mean
140135130125120
Anderson-Darling Normality Test
Variance 883.18Skewness -0.152343Kurtosis -0.856168N 31
Minimum 76.00
A-Squared
1st Quartile 108.00Median 126.003rd Quartile 157.00Maximum 178.00
95% Confidence Interval for Mean
116.71
0.56
138.51
95% Confidence Interval for Median
119.40 137.52
95% Confidence Interval for StDev
23.75 39.72
P-Value 0.140
Mean 127.61StDev 29.72
95% Confidence I ntervals
Summary for June
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Result 3: Left Without Being Seen (LWBS)Result 3: Left Without Being Seen (LWBS)
Reduction from 2% to 0.84%!
60% Reduction in LWBS
Observation
Ind
ivid
ua
l V
alu
e
554943373125191371
4
3
2
1
0
_X=0.84
UCL=1.950
LCL=-0.270
Before After
2
2
22
6
6
1
I Chart of Rate by Label 2
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End NotesEnd Notes
Before Project:
ER was ranked anywhere from 7 to 10 out of the Multi-State region of 17
No goals to become the “2nd to None” ED
No formal data collection process to prove where the problems were coming from
We knew we had problems, however lacked a clear roadmap
After Project:
2nd to None ED-pushing into national top quartile customer satisfaction ratings
Moving to become the benchmark (leading) ED
LWBS = $181,800.00 savings
Reducing Average Length of Stay to allow for increase of 95 patients per month
Medical supplies returned and par level adjustments = $32,923.70
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End NotesEnd Notes
Before Project:
ER was ranked anywhere from 7 to 10 out of the Multi-State region of 17
No goals to become the “2nd to None” ED
No formal data collection process to prove where the problems were coming from
We knew we had problems, however lacked a clear roadmap
After Project:
2nd to None ED-pushing into national top quartile customer satisfaction ratings
Moving to become the benchmark (leading) ED
LWBS = $181,800.00 savings
Reducing Average Length of Stay to allow for increase of 95 patients per month
Medical supplies returned and par level adjustments = $32,923.70
Rev. A Printed 04/12/23© 2005 by Sigma Breakthrough Technologies, Inc.
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Questions & CommentsQuestions & Comments
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