Understanding Variation
In Healthcare
W. Edwards Deming
“If I had to reduce my message to
management to just a few
words, I’d say it all has to do
with reducing unnecessary
variation.”
Numbers We Use Every Day
•
•
•
•
•
•
Time taken to drive to work
Number of patients in the ED
Number of medication errors
Revenue per month
Average daily census in the hospital
Number of research studies approved
by the IRB per week.
How to look at data
Registration Times
• Actual time (minutes) it took to
register patients in a hospital ED
15
67
4
14
10
12
54
3
7
11
14
83
54
17
20
10
53
What information do these numbers provide?
Does this help?
29.6
30
Minutes
25
22.4
20
15
10
5
0
Monday
Tuesday
Does this help?
• Average waiting time is…….
• The mode (frequent number) is……
• The median is…………..
Would any of these numbers help
improve the process?
Run Chart of ED Registration Time
90
80
70
60
50
40
30
MEAN
20
10
Patient Number
7
1
6
1
5
1
4
1
3
1
2
1
1
1
0
1
9
8
7
6
5
4
3
2
0
1
Minutes to Register
100
Run Chart
• May not give you all the answers, but it
well help you ask smarter questions (e.g.
What happened when the registration time was much higher?)
• Provides insight into process behavior
(Seems like there are two processes, one group registers quickly
the other more slowly.)
• No statistical calculations needed
• Use for any type of process and any type
of data
Understanding Variation
• Variation exists and permeates all
processes. No two things are exactly
alike. The problem we face is to be
able to measure the extent of the
variation and to establish to what
degree the variation matters and to
whom it matters.
Common and
Special Cause Variation
Write the letter “a” eight times on a
piece of paper using your
dominant hand.
Make all of them the same.
___ ___ ___ ___ ___ ___ ___ ___
Are they exactly the same?
Why or why not?
Common and
Special Cause Variation
Write the letter “a” three times using your
dominant hand, three times with
your other hand, then two times with
your dominant hand.
Make all of them the same.
___ ___ ___ ___ ___ ___ ___ ___
Are they the same? Why or why not?
• The dominant hand created variation
because of the pen and/or paper you used,
amount of coffee you’ve had, friction of
your hand, etc. etc. This is common cause
variation. It is inherent in the process.
• Using the non-dominant hand clearly
shows something very different. This is
special cause—it does not always happen
in the process of writing. Since it so
different, you would want to ask “why”.
Common and
Special Cause Variation
• Common cause variation
– is always present
– Is inherent in the process
• Special cause variation
– In addition to common cause variation it is
data that signifies the presence of a signal
that needs to be investigated.
• Not knowing the difference can create
wasted time and effort for all.
Taking Action
Action Needed
Yes
No
No
Action Taken
Yes
What rules govern your decision?
Actions to Take
Common Cause
•
•
•
•
Recognize the
variability inherent
in the process
Responding to this
variation is a waste
of time
However, the more
variation the lower
the reliability
To change the
results, change the
process
Special Cause
• Differentiate from
common cause
variation (rules
exist for this)
• Find out what
happened
• Eliminate or
minimize the impact
if negative
• Build positive
impact into process
Why Use Run Charts
• “Before and after” data can mask the
behavior of a process.
• Run charts allow you to see the
behavior of the process.
• Review the following charts that
display both “before and after” and
run charts.
Evaluating a Change: Displaying Before
and After Results
Change Made During Week 8
Averages of Before and After
Week-by-Week Values
Change Between Weeks 7 and 8
Change Between Weeks 7 and 8
8
7.38571428
6
7
5
4
Series1
3
3
2
1
0
Value
Average
6
10
9
8
7
6
5
4
3
2
1
0
Series1
1
WEEKS 1-7
WEEKS 9-14
Weeks
3
5
7
9
Week
11
13
15
Evaluating a Change: Displaying Before
and After Results
Change Made During Week 8
Week-by-Week Values
Averages of Before and After
Change Made During Week Eight
Change During Week Eight
8
7.28571428
6
10
9
7
8
6
Value
5
4
Series1
3
3
Value
7
6
5
Series1
4
3
2
2
1
1
0
0
WEEKS 1-7
WEEKS 9-14
Weeks
1
3
5
7
9
Week
11
13
15
Evaluating a Change: Displaying Before
and After Results
Change Made During Week 8
Averages of Before and After
Week-by-Week Values
Change During Week Eight
Change During Week 8
8
10
7
9
8
5.28571428
6
7
5
4
Series1
3
3
Values
Values
6
6
Series1
5
4
2
3
1
2
1
0
WEEKS 1-7
WEEKS 9-14
Weeks
0
1
3
5
7
9
Weeks
11
13
15
Evaluating a Change: Displaying Before
and After Results
Change Made During Week 8
Averages of Before and After
Week-by-Week Values
Change During Week 8
Change During Week 8
8
10
7
9
8
5
4
7
3.71428571
4
Series1
3
3
Values
Values
6
6
5
Series1
4
3
2
2
1
1
0
0
WEEKS 1-7
WEEKS 9-14
Weeks
1
3
5
7
9
Weeks
11
13
15
Summary
• “Before and after charts” would suggest
that the changes made at week 8 resulted
in improvements.
• Yet when you look at the run charts, data
suggest that some of the improvements
began before the action was taken. If this
improvement was an expensive
proposition, the wrong conclusions will be
made.
Relationship between outcomes and process
variables
There are many causes for the variation seen on the
run chart. All these must be taken into
consideration. Changing only one may not result in
a significant improvement.