Six Sigma: Defining the Problem

Six Sigma in Healthcare:
Defining and Measuring
the Problem
Leslie W. Hayes, MD
Six Sigma Black Belt
D M A I C

Six Sigma
 Greek letter, σ, used to denote variation
(spread) around the central tendency of a
process
 A term used to refer to a
 Cultural Value or Philosophy
 Goal
 Measurement System
 A process to drive out waste and improve
quality, cost and time performance of any
organization
D M A I C

The letter “f”
 Count the number of times the letter f appears
in the following:
Finished files are the result of years of scientific
study combined with the experience of years
D M A I C

How is Six Sigma Different from
other QI approaches?
 Strategically deployed
 Customer focused
 ROI calculations
 Statistically Based Y=f(x)
 Built-in project management
 Preoccupation with error proofing
 Quality improvement on steroids
D M A I C

Six Sigma
Some Terminology
 Sigma – expression of process yield based on the
number of defects per million opportunities (DPMO)
 Unit – the item produced or processed
 CTQ – Critical to Quality
 Truly critical to customer’s perception of quality
 Can be measured
 Can set specifications to know whether or not the CTQ
has been achieved
 Defect – any event that does not meet customer
specification
 Defect Opportunity – a measurable chance for a defect
to occur
 Defective – A unit with one or more defects
D M A I C

What is Six Sigma Performance?
Sigma Defects per Million
Opportunities
How Good is the
performance?
1 688,680 31.1%
2 308,537 69.1%
3 66,807 93.3%
4 6,210 99.4%
5 233 99.98%
6 3.4 99.99966%
20,000 times
improvement
D M A I C

Sigma Level
1,000,000
100,000
10,000
1,000
100
10
1
0 1 2 3 4 5 6
Domestic Airline
Fatality Rate
(0.43 DPMO)
Airline baggage handling
IRS Tax Advice
(phone in)
Prescription Writing
Healthcare associated harm
Restaurant bill mistakes
Reliable Performance is Elusive….
DefectsperMillion
6 sigma accuracy = 3.4 defects per million
LSL USL
p(d)
M
6 4 3 2 1 1 2 3 4 5 65
p(d)
A 6 Sigma Process includes
6 standard deviations between
the mean and the spec limit
Sigma Values
+/- 1 = 68.26%
+/- 2 = 95.44%
+/- 3 = 99.73%
Six Sigma
Point of Inflection
s1
7
Anesthesia deaths
ASA class I
D M A I C

Would you be happy with 99.9%
performance?
 1 hour of unsafe drinking water every month
 2 unsafe plane landings per day at O’Hare
 16,000 pieces of mail lost by the USPS every
hour
 500 incorrect surgical operations every week
 50 newborn babies dropped at birth by doctors
each day
 22,000 checks deducted from the wrong bank
accounts each hour
D M A I C

What is Six Sigma Quality?
Quality
Product
Features
That Customers Want
Freedom from
Defects
At Six Sigma Levels
D M A I C

The Methodology: DMAIC
 DEFINE Identify the right project
 MEASURE Identify and understand key
process and outcome
measures
 ANALYZE Identify key process
determinants
 IMPROVE Establish new model and
optimize performance
 CONTROL sustain the improvements
D M A I C

Comparison of different models
11
D M A I C

Project Focus
Phase
DEFINE The right project with the right team
MEASURE Process
Problems
Outputs (outcomes)
ANALYZE
IMPROVE
CONTROL
Process inputs
The Vital Few “x’s”
the “Y”
the “x’s”
Goal: Y = f(x)
D M A I C

DEFINE: the goals
 Identify the actual problem
 Identifying the customers of the project,
including their specifications
 Involve the right people
 Creating a team charter
D M A I C

Overview of Define
Define the
business
case
Gain
project
approval
Understand
The
customer
Define
the
process
Manage
the
project
• Problem
statement
• Goals
statements
• Costs of poor
quality
• Project plan
• Stakeholder
analysis
• Storyboards
• SIPOC• VOC
• Kano analysis
• CTQ tree
• Project
charter
D M A I C

SMART Problem Statements
 Specific
 Measurable
 Achievable
 Relevant
 Time Bound
D M A I C

Goal Statements
 Keep it brief
 Avoid technical language
 Use same metrics as your problem statement
 Be as specific as possible about dates
D M A I C

Cost of Poor Quality
 Rework
 Rejects
 Inspection
 Testing
 Customer returns/complaints
 Excess inventory
 High employee turnover
D M A I C

Voice of the Customer (VOC)
 Define your customer
 Frontline staff involvement
 Families/patients perspective
 Sampling methods
D M A I C

 “Delighters”
 “More is better”
 “Must haves”
Kano Analysis
D M A I C

S I P O C
Step
Process
starts
Step Step Step
Process
Ends
Operations
Sales
Accounts
Legal
Patients
Clinicians
Patient data
Specimens
Equipment
Supplies
Outcomes
Product
Process
Data
Clinician
Lab Tech
Patient
Family
D M A I C

SIPOC Exercise – 20 minutes
D M A I C

CTQ Tree (Key Driver Diagram)
 Provides clarity and structure
 Turns the customers need into a measureable
specification
 General steps
 VOC
 Key Drivers of the customer’s needs
 What element of the key driver is critical to a
quality process/outcome
 Specifications
D M A I C

D M A I C
What the
Customer
needs
What the
Customer
Means by
good #1
How do we
Define
Critical element?
How often
Should this
Occur?
VOC Drivers CTQs Specifications
What the
Customer
Means by
good #2
What the
Customer
Means by
good #3
How do we
Define
Critical element?
How do we
Define
Critical element?
How often
Should this
Occur?
How often
Should this
Occur?

D M A I C
GOOD
PIZZA
What the
Customer
Means by
good #1
How do we
Define
Critical element?
How often
Should this
Occur?
What the
Customer
Means by
good #2
What the
Customer
Means by
good #3
How do we
Define
Critical element?
How do we
Define
Critical element?
How often
Should this
Occur?
How often
Should this
Occur?

D M A I C
GOOD
PIZZA
TIMELY
How do we
Define
Critical element?
How often
Should this
Occur?
COOKED
RIGHT
ACCURATE
How do we
Define
Critical element?
How do we
Define
Critical element?
How often
Should this
Occur?
How often
Should this
Occur?

D M A I C
GOOD
PIZZA
TIMELY ≤ 15 minutes
100% of the
time
COOKED
RIGHT
ACCURATE
Correct internal
temperature
Product
matches
order
100% of the
time
100% of the
time
Cheese
browned
Crispy

D M A I C
Good
Pizza
Timely ≤ 15 minutes
100% of the
time
Cooked right
Accurate
Correct internal
temperature
Product matches
order
100% of the
time
100% of the
time
Cheese browned
Crispy

CTQ Exercise – 20 minutes
D M A I C

Project Charter
 Output of Define (summary)
 An agreement between management and the
team
 Your marching orders going forward
 Keeps the team focused
D M A I C

Team Charter
Name ______________________________
Title _______________________________
PURPOSE:
(Includes Problem Statement)
IMPORTANCE:
(business case; benefits to business,
customers, employees)
SCOPE
1. This process starts with
2. This process ends with
3. Inside scope
4. Outside Scope
Project Schedule
5. Project to start (date)
6. Project to end (date)
7. Define to end (date)
8. Measure to end (date)
9. Analyze to end (date)
10. Improve to end (date)
11. Control to end (date)
Budgetary Needs
Goals of Project
DELIVERABLES:
(List items delivered from the
project team)
Improved process, new process documentation, training, etc.
MEASURES:
(Key measures; how much
improvement is needed?)
1. We have (3) key measures.
They are :
2. Today we are operating at
3. Our target is to (increase or
decrease)
4. We will produce these
results by the end of (month and
year project ends)
 Purpose
 Importance
 Scope/focus
 Measures
 Deliverables
 Resources
Elements of a Charter
D M A I C

Consider working on a Project
Charter with your Team This
Weekend
D M A I C

Pulling Define Together
D M A I C

Background
 We have a large number of critical lab values
that must be reported by the lab techs in a
timely fashion to prevent harm from occurring
to patients and to maintain compliance with
regulatory standards.
 In reality, it all started with a page one
Monday morning…
D M A I C

S I P O C
LT
retrieves
value
Value
resulted on
machine
LT
determines if
Critical Value
LT
determines
who to call
LT
delivers
results
LT
documents
notification
Patient
Clinician
Collector
Order
Enterer
Transporter
Lab Tech
(LT)
Order
Specimen
Workers
Machine
Log Book
Telecommunications
Documentation
of the Critical
Value
Provider
Knowledge of
Critical Value
Clinician
Lab Tech
Patient
Family
D M A I C

D M A I C
Give and
Record
important
information
quickly
Accurate
Clinician
information
available
Timely
Notification of
information
Accurate
Patient
Information
Important
information
communicated
On-call list is
accurate
Correct service
information is
available
Patient location is
known
Time from value
available to
initial call to
clinician is short
Complete
notification of
values done in
stated time
Values on
‘Critical Value’
list are truly
critical
100% of time
100% of time
100% of time
Less than 30
minutes
100% of time
20% reduction
in notifications

Problem Statement Goal Statement
Hospital critical lab values are
reported by lab techs to the
appropriate healthcare providers.
Our standard is that notification
occurs within 30 minutes of the
resulted value. Our current rate of
compliance with this standard is
89%.
To increase notification within 30
minutes to 100% by January 31,
2010.
Project Scope Business Case/Financial Impact
Identify improvements to reduce
cycle time. Reduce the amount of
notifications made by analyzing
the criticality of results and making
adjustments.
Reduce time spent in notification
process by lab techs. Reduce the
probability of a citation by regulatory
agencies.
D M A I C

Charter
Customers and CTQs Project Team
Lab Tech
Clinician
Patient/Family
CTQs:
See CTQ Slide
Champion: Pathology MD
Process Owner: Lab
Director
Team Leaders: Black Belt
Core Team Members: Lab
techs, prescribers
D M A I C

Project Plan
Start Finish
Define 9/9/09 9/25/09
Measure 9/26/09 10/21/09
Analyze 10/22/09 10/28/09
Improve 10/29/09 12/14/09
Control 12/15/09 1/31/09
D M A I C

Data helps us…
 Separate what we think from what is real
 Confirm or disprove ideas
 Establish baseline
 Observe history of problem over time
 Understand variation
 Avoid “solutions” that don’t solve the real
problem
D M A I C

Overview of Measure
Develop
Process
measures
Baseline
process
capability
Collect
Process
data
Check
Data
quality
Understand
Process
behavior
• Metrics
• Operational
definitions
• Data worlds
• Distributions
• Process
stability
• Short/Long
term variation
• Measurement
system
analysis
• Collection
methods
• Collection
plans
• Sampling
• Process
capability
• DPMO
• Sigma Levels
• Sigma Shift
D M A I C

Overview of Measure
Develop
process
measures
Baseline
process
capability
Collect
process
data
Check
data
quality
Understand
process
behavior
• Metrics
• Operational
definitions
• Data worlds
• Distributions
• Process
stability
• Variation
• Measurement
system
analysis
• Collection
methods
• Data not
related to
time
• Data related
to time
• Process
capability
• DPMO
• Sigma Levels
• Sigma Shift
D M A I C

Approach to Measure
 Data Collection
 Data not related to time
 Pinpoint occurrence of problems
 Data related to time
 Identify variation (patterns) in process
 Create detailed process maps
 Calculate process sigma
D M A I C

Elements to Discuss
 Operational Definitions
 Data Worlds
 Data not related to time
 Data related to time
 Variation
 DPMO
 Process sigma
D M A I C

Metrics (KPIs)
 CTQs (Key Drivers) are the basis for your Key
Performance Indicators
 Measurements that reflect the VOC
 Data collection
 Balance efficiency and effectiveness
D M A I C

Please write down clipboard
clock time for each of the
following
1. Sign in _________________________
2. Registration done_________________
3. Called back & weighed_____________
4. Placed in room to wait______________
5. Nurse in room to see you____________
6. Doctor in room to see you____________
7. Discharge instructions done__________
8. Leave Clinic_______________________
D M A I C

 Granularity of data
needed can
determine collection
methods
D M A I C

What $20 and your patients’
families can do…
D M A I C

2892572251931611299765331
200
150
100
50
0
Clinic Visit
Timeinminutes
_
X=84.8
UCL=156.0
LCL=13.7
Total GI Clinic Encounter Time
D M A I C

Operational Definitions
 Specific and concrete
 Measurable
 Useful
 Questions:
 How will you measure your data?
 What related conditions will you record?
 Sampling technique?
 How or where will you record your data?
D M A I C

Exercise: Creating an Operational
Definition – 20 minutes
D M A I C

Taguchi Loss Function
Matching process with specifications
D M A I C

Desired Data Characteristics
Useful, meaningful data are… Typical problem
Sufficient
enough so the patterns you see are likely to
be real
Insufficient
not enough data to reach reliable
conclusions
Relevant
helps you solve/pinpoint the problem
Irrelevant
describes a characteristic that doesn’t help
you understand the problem
Representative
full range of actual process conditions seen
Biased
only represents certain process conditions
Contextual
collected along with other key information
Isolated
your data is the only information you have
about the process
D M A I C

Data Worlds
“Continuous” “Attribute”“Count”
“Measuring”
something
“Classifying”
something
“Counting”
things
• Calculated averages and
variation
• Resolution only limited
by measurement system
• Counting whole things
• Data can only be
integers
• Categories that do not
necessarily have
numerical value or order
D M A I C

Continuous Data World
 How to spot continuous data
 Not limited to whole numbers
 Examples:
 Oven temperature
 Length of hospital stay
 Time to next available appointment
 Laboratory values
 Invoice processing time
 Caution: resolution of the measurement system
can affect your data
D M A I C

Count Data World (Poisson)
 How to spot count data
 Half units not possible
 No physical upper limit
 Data recorded for a specific area of opportunity
 Defects per unit
 Examples
 Calls to the IT helpdesk each hour
 Employee needle sticks
 Patient complaints
D M A I C

Attribute Data World (Binomial)
 How to spot attribute data
 Classifications
 Often in percentages
 Examples
 Tossing a coin
 Proportion of patients experiencing harm
D M A I C

Data NOT Related to Time
 Tally (check) sheets
 Pareto
 Cause and Effect Diagram
 Detailed Process Mapping
D M A I C

Tally Sheets
.
Study
subject
PIB Type PIB
Placement
PIB Information:
Name Correct
PIB
Information:
Gender
Correct
PIB
Information:
DOB Correct
Age Required
Spanish
interpreter
(Y or N)
1
2
3
4
5
6
7
8
9
10
D M A I C

D M A I C
Documented Sever Severity by s/s Daytime Symp Night Cough/Awa Activity Limits Beta Agonist use Exac in <1 yr
Moderate Pers Persistent NR 1-2/week NR 1-2/month No
Moderate Pers Persistent NR Nightly
"could not tolerate PE
last year" 1/month No
Moderate Pers Persistent NR NR
Yes, "missing
significant amounts
[of school] due to
asthma" NR Yes >2
NR Persistent by ICS NR NR NR NR NR
Mild Pers Persistent 3/week None Some NR No
NR Persistent NR None None
No albuterol over 6
months Yes-1
NR Persistent NR NR NR NR Yes-1
NR Persistent by ICS NR NR NR NR No
Moderate Pers Persistent NR None None 1/month winter None
NR Persistent NR Nightly NR NR Yes >2
NR Intermittent <1 month NR NR <1 month No
Moderate Pers Persistent 1-2/week NR Alb before exercise NR Yes >2
NR ? NR NR NR NR NR
NR Persistent NR NR NR NR Yes >2
NR Persistent by ICS NR NR NR NR Yes >2
NR Persistent by ICS NR NR NR NR Yes-1
NR ? <1 month NR NR <1 month No
Moderate Pers Persistent NR NR NR NR Yes-1

What does your data collection
strategy look like?
D M A I C

Pareto Principle
 80:20 rule
 In the 1800s, an Italian
economist Vilfredo Pareto
noted that 80% of the land
in Italy was owned by 20%
of the population
 Principle applies in other
areas
.
D M A I C

Count 2 2 2 1 140 13 7 6 4 3 3 2
Percent 2 2 2 1 147 15 8 7 5 3 3 2
Cum % 93 95 98 99 10047 62 70 77 81 85 88 91
Mechanism
Pulled
behind
ATV
on
innertube
v
Pole
Peds
v
Tree
Lim
b
W
atercraft
TV
Peds
v
Tractor
Assault
M
otorcycle
GSWFall
Bike
ATV
Peds
v
Auto
M
VA
90
80
70
60
50
40
30
20
10
0
100
80
60
40
20
0
Count
Percent
Mechanism of Injury
D M A I C

Transfers 7 7 6 6 6 5 841 39 33 26 19 17 14 8
Percent 3 3 2 2 2 2 317 16 14 11 8 7 6 3
Cum % 84 87 90 92 95 97 10017 33 47 57 65 72 78 81
Unit
O
ther
M
7
W
5
OSCU
GynX
W
6P7S7P9
W
9
W
8P8S86SS9
250
200
150
100
50
0
100
80
60
40
20
0
TransfersbyUnit
Percent
Transfers to MICU Oct-12 through Aug-13
D M A I C

29
21
58.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
5
10
15
20
25
30
35
40
45
50
yes no
Nightsymp
Categories
Nighttime Symptoms Recorded 2014?
D M A I C

21
8
3 3
2 2 2
1 1 1 1 1 1 1 1 1
42.0%
58.0%
64.0%
70.0%
74.0%
78.0%
82.0%
84.0%
86.0%
88.0%
90.0%
92.0%
94.0%
96.0%
98.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
5
10
15
20
25
30
35
40
45
50Nightsymp
Categories
Nighttime Symptoms Present 2014?
D M A I C

21
14
10
3
2
42.0%
70.0%
90.0%
96.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
5
10
15
20
25
30
35
40
45
50
NR <2x/month >1x/week 7x/week 3-4x/month
Nightsymp
Categories
Nighttime Symptoms Present 2014 (Desired
Wording)
D M A I C

Questions about Pareto Charts?
D M A I C

Distribution Shapes and the
Normal Distribution
 Right skewed (positive skew)
 Left skewed (negative skew)
 Normal distribution
D M A I C

24020016012080400
Median
Mean
80706050403020
1st Q uartile 13.250
Median 43.000
3rd Q uartile 114.500
Maximum 244.000
55.429 82.291
27.000 66.289
59.433 78.635
A -Squared 4.71
P-V alue < 0.005
Mean 68.860
StDev 67.691
V ariance 4582.021
Skewness 0.852634
Kurtosis -0.496777
N 100
Minimum 0.000
A nderson-Darling Normality Test
95% C onfidence Interv al for Mean
95% C onfidence Interv al for Median
95% C onfidence Interv al for StDev
95% Confidence Intervals
Summary for Age at ICU Admission (months)
D M A I C

Normal Distribution
D M A I C
• 6σ performance = 99.99966%
• 6 Std Dev = 99.7% (4.3 σ)

DPMO
Sigma Defects per Million
Opportunities
How Good is the
performance?
1 688,680 31.1%
2 308,537 69.1%
3 66,807 93.3%
4 6,210 99.4%
5 233 99.98%
6 3.4 99.99966%
20,000 times
improvement
D M A I C

Detailed Process Mapping
D M A I C

24 steps 22 steps 12 steps
7 steps !!!
Detailed Process Mapping
D M A I C

Process Mapping Group Time
D M A I C

Six Sigma: Defining the Problem

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