why 85% of decisions made in your organization are wrong and how to fix it!
DESCRIPTION
TRANSCRIPT
Why are 85% of your decisions wrong and
how to fix it?
John Bachman
Strategies
►Run up the hill
►Something different-The foreman stopped set fire to an area and jumped into the burnt out area (escape fire) Beckoned his men to joint him
►Men died…. All of them had their packs on and were carrying their axes or shovels
Points of the Story
1. Danger happens and change is needed
2. Escape Fires are present along the way
3. Cling to our past and hold on to the familiar
1. Knowledge is learning something new. Wisdom is letting go of something old.
Why are 85% of your decisions wrong and
how to fix it?
John Bachman
Outrageous
►Escape Fire
►Let go of things that are holding you back and are a part of your every day life!
That’s a lot of nerve
► Edwards Deming
►He felt over 90% of decisions designed to make things better were wrong
► Father of Quality improvement
Quality Improvement
►We have quality improvement!
►Six Sigma Lean and all sorts of tools!
►Organizations have improved!
►Point to an area and see what we have done
►We reorganized things and it is better
►We have data to support it
Deming would smile at us
► Language-overuse reduces meaning
► Finding a better way to scrape burnt toast
► Flavor of the month…. Of course you can improve things for a little while and then if you watch things it regresses
►Reorganizations 25% successful at 4 years
►Victims of a constantly changing environment and controlled by outside forces
►We lead and get what we want and that is the problem
Deming would then say “Let us learn a new philosophy”
What is a System?
What is the Aim of a System?
►Person?
►Office?
►Health Care System?
►Fastest way to get to the heart of an issue
Example Joan
Example Group Please the top
►Better than that
►How do we measure it?????
How do we manage a system?
Management by Results
► Peter Drucker
► “People on a balance sheet are recorded as liabilities”
► 1950s
► Extremely common method
►Deming’s view
Neighbors
One of 14 points not to use it
Top Rung
► Leadership sets up goals and objectives for the system
►Give it to the rung below them
►Give it to the rung below them
►Give to the rung below them
MANAGEMENT BY RESULTS
Makes sense
►Give Responsibility to other so they have freedom to act
► Performance reviews
►Control of resources
► Logical and organized
► “Command and Control”
Problems with Management of Results
► Please the people above you-Give the results they
need to see (Management gets what it wants)
► Silos-nurses, secretaries, medical, financial
► We have accountability of individuals? How much do we control?
Diabetes
Problems with Management of Results
►Communication
►Knowledge of processes
Top management 4%
Middle management 9%
Supervisors 74%
Frontline 100%
► Implementation is success
►Compliance vs Commitment
► Numbers-Fear-Fudging-short term thinking
► Elite group design future for the many (design team)
6-12 people supervisors professionals and workers
Analysis
Redesign
One best design
► Shortcomings
Resistance
Misses subtleties
Long time
70% failure rate at 4 years
Management by Results
►Summary: Better to do things right then to do the right thing.
What is the Alternative?
Different Approach-Profound Knowledge
1. System
2. Variation-Take a group next
3. Knowledge
4. Psychology
What is the difference between Data, Information, and
Knowledge?
Data is figures
LOOK AROUND YOU
DATA DATA EVERYWHERE AND NOT A BIT TO THINK
We can explain data Numbers have power
Davis Balestracci
www.davisdatasanity.com
Déjà vu? How many meetings?
We make decisions by reacting to observed variations in data or information???
Davis Balestracci
www.davisdatasanity.com
Board Member #1: “Find out what happened!”
“Why are we having more bacteremias?”
Information
1. Describes the present or past
2. Data organized in patterns
1. Prejudice
2. Percentages
3. Comparisons to other groups (benchmarking and rankings)
4. Experiments or Pilots
Experiments (Implementation is Success)
Davis Balestracci
www.davisdatasanity.com
“We have a trend of steady progress”
Annualised Attrition rate
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Jul-07
Aug-0
7
Sep-0
7
Oct-
07
Nov-0
7
Dec-0
7
Jan-0
8
Feb-0
8
Mar-
08
Apr-
08
May-0
8
Jun-0
8
Jul-08
Aug-0
8
Sep-0
8
Oct-
08
Nov-0
8
Dec-0
8
Jan-0
9
Feb-0
9
Mar-
09
Apr-
09
May-0
9
Jun-0
9
Jul-09
Aug-0
9
But do we?
Davis Balestracci
www.davisdatasanity.com
What is the trend? Nursing Attrition Rate (Monthly)
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
Ju
l-0
7
Au
g-0
7
Se
p-0
7
Oct-
07
No
v-0
7
De
c-0
7
Ja
n-0
8
Fe
b-0
8
Ma
r-0
8
Ap
r-0
8
Ma
y-0
8
Ju
n-0
8
Ju
l-0
8
Au
g-0
8
Se
p-0
8
Oct-
08
No
v-0
8
De
c-0
8
Ja
n-0
9
Fe
b-0
9
Ma
r-0
9
Ap
r-0
9
Ma
y-0
9
Ju
n-0
9
Adults Hospital Private Hospitals Childrens Hospitals Mother's Hospitals Combined Hospitals
Davis Balestracci
www.davisdatasanity.com
Profound truth: Given two different numbers…
Something
Important
Yesterday Today
…one will be larger!
Davis Balestracci
www.davisdatasanity.com
“Account for your performance!”
Time
“Upward Trend”
“Downturn”
“Rebound”
“Setback”
“Turnaround”
“Downward Trend”
This month…
vs. last month…
vs. the month before
How much time is wasted explaining random variation?
A=AA B=TB and C=LC
F=ML H=IY
L=BB
M=DC
Q=BE
“Let’s set some stretch goals”
►The bottom 10% of the group will improve to the 50th percent
►We will be in the top 80% of all quality markers
Example
►Teachers
Your child has a test and is below average
Your child has now had two tests and is below average
How do we know what we are doing?
Knowledge
►Rooster
►Knowledge implies theory
Means it can be revised
Predictive
► Future related
What would be a real trend???
Trend
►Variation All processes vary Is it just background noise (common cause)
►Variation Is this related to something new (special cause )
People Need to Solve their Problems!!!!
Davis Balestracci
www.davisdatasanity.com
Tampering ►Tampering: Treating common cause as
special cause
Human tendency is to account for ALL variation as special
Looking for an explanation and finding one - positive or negative
Wastes time and resources
►Deming: “The losses caused by tampering are incalculable.”
Knowledge is Prediction
Davis Balestracci
www.davisdatasanity.com
A statistical definition of “trend”
Time
"Sw
eat"
Index
Upward Trend
Time
Downward Trend
Special Cause –
A sequence of SIX successive increases
or decreases
Usually indicates a process “in transition”
Diabetes
Davis Balestracci
www.davisdatasanity.com
“I can’t wait for five or six increases!”
►You don’t have to in the context of variation
►Increase the frequency of measurement (quarterlyweekly)
►Use other methods
Davis Balestracci
www.davisdatasanity.com
If We Talk Improvement:
Knowledge=Plot the Dots ►Eliminate tampering
►Meaningful Interventions
►Improved Conversations
►Eliminate 75-85% of data and information
“Your current processes are perfectly designed to get the
results you are already getting.”
Plot the dots
Keep Sampling the Stream!
Davis Balestracci
www.davisdatasanity.com
Bread-and-butter tool: Run Chart
Time ordered plot with the MEDIAN as reference
Median=Middle Value
Davis Balestracci
www.davisdatasanity.com
Special Cause: A consecutive sequence of 8 or more points on one side of the
median
Indicates a probable shift in the
process during this time period
Davis Balestracci
www.davisdatasanity.com
What would you do now? - Plot the dots!
Have things
changed?
Davis Balestracci
www.davisdatasanity.com
“What is happening with NICU Infections?”
0
2
4
6
8
10
12
14
16
1 2 3 4 5 6 7 8 9 101112131415161718
0
200
400
600
800
1000
1200
1400
# Infections
#Patients
Infection Rate
-0.5
0
0.5
1
1.5
2
2.5
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Month
Infe
cction R
atePlot the rate
(Infections/Patients)
Davis Balestracci
www.davisdatasanity.com
Do you do “Percent Compliance?” West
93.6%
90.8%
90.2%
90.1%
91.8%
90.7%
90.1%
91.7%
89.7%
89.8%
88.5%
91.0%
89.7%
91.1%
90.1%
90.1%
91.1%
90.8%
91.4%
91.9%
IF you plot the dots …
Red…Yellow…Green…
Davis Balestracci
www.davisdatasanity.com
With a stable process, we can construct a CONTROL CHART
Week-to-week EXPECTED variation: 3.5%
93.2%
87.9%
90.6%
93.6%
Davis Balestracci
www.davisdatasanity.com
Remember this?…
Annualised Attrition rate
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Jul-07
Aug-0
7
Sep-0
7
Oct-
07
Nov-0
7
Dec-0
7
Jan-0
8
Feb-0
8
Mar-
08
Apr-
08
May-0
8
Jun-0
8
Jul-08
Aug-0
8
Sep-0
8
Oct-
08
Nov-0
8
Dec-0
8
Jan-0
9
Feb-0
9
Mar-
09
Apr-
09
May-0
9
Jun-0
9
Jul-09
Aug-0
9
Davis Balestracci
www.davisdatasanity.com
Is there as steady trend?
Annualized Attrition Rate
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
Aug
-07
Oct
-07
Dec
-07
Feb
-08
Apr
-08
Jun-
08
Aug
-08
Oct
-08
Dec
-08
Feb
-09
Apr
-09
Jun-
09
Period
Indiv
idual V
alu
e
Special Cause Flag
Did we improve the
A1c?
What about the LDL?
Constructing Run and Control Charts
►Quality Academy templates http://mayoweb.mayo.edu/quality-learning/qa-templates.html
Select C-chart 5e
Copy 50 cells to paste
View control chart
Relabel chart title and axes
►Copy and paste chart into document
►Get Software
► http://asq.org/learn-about-quality/data-collection-analysis-tools/overview/control-chart.html
Amundson and Scott
Amundsen-Exploring
►Preparation
Dolphin was eaten
Expeditions
Read original work-Thinking
Scott
►Tradition of Britain “We can do it” “We are English”
► Scientific background
Scott used Ponies and Motorized Sleds (Manly thing to push)
Ponies died and motorized sleds stopped working in a week 4500 calories given 7000 used for hauling
Amundsen
Amundsen used dogs…. Excessive use of animals Abundance of materials carried redundancy
Concept of the 20 mile March
►Amundsen used the 20 mile march
►Good days or bad would try to go 15-20 Miles.
►Scott would on fair weather go long Distances and then not be ready if bad Weather came
►Point was constancy of purpose!
What did they do to be successful
►Preparation-know what status of environment is-(Stable System)
►Used proven methods (control and run charts)
►Constancy of purpose (PDSA cycles)
Lets Take an Example
►Our office
We were having issues with “open access”
All the slots would fill up and we would call an access alert
Patients not happy
Clinicians not happy because mess-hours
►Add more slots that would be open-lose continuity
►Add more slots in general
►Decrease panel Size
What should we plot?
Unfilled Slots and Sames
►We could go to the computer and get this information
►It has been around for years
It would lead you completely astray!
Step 1 Get together and discuss what things mean!
►Same=a slot that is open and kept open for people who call in on that day
►Actually at 3 PM the preceding day it starts
►Actually a doctor can put a person in if no space
►Actually we will put a person in who is a bleeding heart
Deming
►“There is no meaning to anything!!!”
Raw Data
►Kept track of it on a graph (Put the numbers in the template) We used Mayo You can use ASQI (google calculate control chart)
Step 2
►We plotted people who needed to be seen that day and from the previous day
►We plotted unfilled slots
We Looked at a Stable System
►We shared it with everyone
►This is the PowerPoint We Used
Access is a Big Issue for us!
Access Can be Broken Down
►Availability On a given day can a patient be seen
►Access (Continuity) Can the patient see own doctor
►Affordability Can a patient afford it
►Acceptability Can a patient come in at a time of choosing
We are Going to Look at Availability
If I am Sick Can I be Seen at Baldwin today
It is really nice to see a
doctor when I am sick!!!
We want a balance between supply of patients and openings
Patients in Patients
Taken Care
of
No alerts, cramming, or compromise in care
How Many Slots Do We Need to Serve Each Day Who Call in and
are Seen That Day?
►40 per day
►60 per day
►80 per day
►100 per day
►150 per day
The answer
►About 60!
If you look at the next graph you can learn a few things
MORNING
Average is 25
AFTERNOON
Average is 42
TOTAL DAY
Spikes INDICATE MONDAYS
MONDAYS ARE ALWAYS BUSIEST DAYS OF THE WEEK FOLLOWING!!!
MORINGS 25, AFTERNOONS 42 AND TOTAL 67
VARIATION
►Averages of 65 are nice but not practical
►You can have one foot in ice water and another in boiling water and on average you are fine
►We need 0-140 slots a day!
►No wonder we have problems!!!
Deming said “The Key to Process Improvement is
Decrease Variation
We can….
Look at next graph…
This is the Next Step
►Decrease variation
►Implement a new system
Eliminate Mondays
Look at this less variation if we just eliminate Mondays!!!!!!
Mondays has more activity by almost 50%
AM on consecutive Mondays PMs
TOTAL
Interesting
►If we eliminate Mondays=Variation reduced by 40
►Mondays average 100 slots
►We use as many slots on Monday PM as we do for whole days Tues to Thurs
►Two days (Biggest Numbers are Tuesdays after Busy Mondays)
►So our first step would be
Eliminate Mondays!
We are Kidding
►However We Need to Have Mondays Handled Differently then Tues-Friday
►We have on average 40 people scheduled the day before On Monday we average 25 from the weekend
►There are some other add ons ER and Hospital Visits are higher
So Step 1 in Improving Availability
►Treat Monday as Something Different
►We can expect more patients and more complex patients.
►If we handle Monday better will Tuesday be better??
►We have set up a PDSA group to work on Monday
So that is where we are
1. We know that we have a stable system but with a great deal of variability
2. By using Data a group will help with making Monday better for handling increased demand
It makes sense
►Yes, This is not revolutionary but we have data to support it so when we make changes we can see impact
►This is going to take awhile but we are moving in a direction of continuous improvement!
What did we come up with
►Monday Afternoon was total blocked
Monday PM First 30 minutes used for Hospital Recheck, ER Recheck, Newborns
Doctor could override system and see patient (no one else)
We will have excess access and expect some afternoons will be quiet but what ever happens Monday will be taken care of!!!
Weekly Fill Rates
• Fill rates in Q4 2011 mainly between 90% and 95%
• Overall daily and weekly fill rates declined early in 2012
• Fill rates stabilized from Feb 2012 through July 2012
• Ranged between 85 and 90% – more acceptable/manageable
Family Medicine Baldwin
Filled in Last 2 Days
• Pre-Pilot: 7%
• During Pilot: 24%
During Day Fill Rate
• Pre-Pilot: 32%
• During Pilot: 52%
End of Day Unfilled Rate
• Pre-Pilot: 6%
• During Pilot: 21%
Baldwin -- Monday PM Fill Rates
Baldwin – Mondays
Same Day Slots Filled
• The counts of PM slots filled
during the day has ranged
from 70 to 115 over the past
six months, significantly
higher than in 2011
Overall Slots Filled
• Average counts of filled slots
has slightly decreased
during the pilot phase (one
of the goals)
• Variability of filled slots is
similar during both phases
July-2012.........Sept-2011
140
120
100
80
60
40
20
0
Date
Slo
ts F
ille
d S
am
e D
ay
_X=90
UCL=136.0
LCL=44.0
Pre-Pilot Pilot Phase
PM Slots Filled Same Day - Monday Only (Or 1st Day of Week)
July-2012.........Sept-2011
400
350
300
250
200
Date
Fille
d S
lots
_X=299.7
UCL=392.0
LCL=207.4
Pre-Pilot Pilot Phase
Monday Filled Slots
Tuesday Filled Slots
• Average number of filled
slots is slightly higher during
pilot phase with significantly
less variability
Wednesday Filled Slots
• Average number of filled
slots is slightly higher during
pilot phase with significantly
less variability
Baldwin – Tuesday / Wednesday
July-2012.........Sept-2011
450
400
350
300
250
200
Date
Fille
d S
lots _
X=329.3
UCL=396.7
LCL=261.9
Pre-Pilot Pilot Phase
Tuesday Filled Slots
July-2012.........Sept-2011
400
350
300
250
200
150
Date
Fille
d S
lots
_X=276.3
UCL=352.3
LCL=200.3
Pre-Pilot Pilot Phase
Wednesday Filled Slots
Thursday Filled Slots
• Average number of filled
slots is higher during pilot
phase with significantly less
variability
Friday Filled Slots
• The average number of filled
slots is higher during the
pilot phase with less
variability
Baldwin – Thursday / Friday Slots
July-2012.........Sept-2011
400
350
300
250
200
Date
Fille
d S
lots _
X=291.1
UCL=376.0
LCL=206.2
Pre-Pilot Pilot Phase
1
Thursday Filled Slots
July-2012.........Sept-2011
400
350
300
250
200
Date
Fille
d S
lots _
X=300.2
UCL=383.3
LCL=217.1
Pre-Pilot Pilot Phase
Friday Filled Slots
Other Items
► Stopped churning on Mondays
Phone calls
Triage
Complex patients now seen by own clinician
► Decreased testing
► Decreased coming back
► Providers very happy Patients very happy
► No access alerts
Providers being ill not an issue
Monday AM Team meetings
► Further PDSA Thursday for complex pts
►More likely to have add ons
Constancy of Purpose
►Weekly to monthly graphs
►PDSA Thursday PM for Complex patients from hospital, ER, or Newborn
►Monday AM team meetings
►Not an issue…
Moving on to appt times
How do we make continual improvement
►Don Berwick
Outsiders Management can make judgments on improvement
Insiders are the ones who can make improvement
Constancy of Purpose
Resources
►Web Site: http://www.qualityandtraining.com
This has short films for teams about this
IHI Open School
►www.ihi.org/offerings/ihiopenschool/Pages/default.aspx
Books
►Fundamentals of Health Care Improvement
www.ihi.org/.../ihiopenschool/.../FundamentalsofHealthCareImprovement.aspx
►Deep Change
►www.amazon.com/Deep-Change-Discovering...Bass.../0787902446
►Great by Choice
www.amazon.com/Great-Choice-Uncertainty-Luck.../0062120999
Best All Around
►DATA SANITY
►davisdatasanity.com/
Weekly newsletter
Book
Different Approach-Profound Knowledge
1. System
2. Variation
3. Knowledge
4. Psychology
Variation
►All Processes Vary
►Reacting to individual fluctuations is tampering
►Not understanding a special cause leads to tampering
►Tampering is successful initially and then over times falls apart because of the 8 influences on processes
Response to Variation
“If I had to reduce my message for management to just a few words, I’d say that it all had to do
with reducing variation”
W.E.DEMING
RED BEAD EXPERIMENT
Control Chart Template (free)
►http://asq.org/learn-about-quality/data-collection-analysis-tools/overview/control-chart.html
Funnel Experiment
If you aim at the target and drop the ball 50 times
You Get a Circle
What Causes Variation?
Imagine
►You are leading a parade…….
People cause variation
Now you are pushing a wheelbarrow
Machines may alter variation
You Come to a Building Where Someone Gives
you instructions
Methods Cause Variation
Someone Dumps Cement into Your
Wheelbarrow
Materials
Alter Variation
Materials go to a Certain Line
Measurement
Varies
Go Out in the Sun where it is Hot
Environment
causes variation
Causes of Variation
OUTSIDE
1. People
2. Machines
3. Methods
INSIDE
1. Materials
2. Measurement
3. Environment
MONEY AND MAINTENANCE
How to use????
►My car will not start
►Fish Bone Diagram
Instructions
►Draw a line
►Draw 6-8 bones of causes of variation
►Use sticky notes to put on the sides of causes
►Keep drilling deeper 5 Whys?
►Brainstorming Not to think
Funnel Rule 1 Variation
►Management or people look at the pattern and think they can just improve it
Rule 2 Messed up by people
►Drop a ball on the target
►Measure the distance from the ball and go 180 degrees in the opposite direction
►You will now be dropping a ball on the target again.
►Now….. Measure the distance between the impact of two balls and go 180 degrees opposite from the second impact
►Keep using last ball as your marker
Rule 2 Tweaking!
Simply put, your reference point for adjustment is the last event.
We base our decision on last result
and tweak it
By chance it may improve
“Confirming Evidence Trap”
Variation increases 40%
Examples
► Adjusting a process when a part is out of specifications
Complaint from a patient
► Operator adjustments without the aid of control charts
► Changing company policy based on the latest attitude survey
► Recalibrating instruments to a standard
Gun firing in the morning
► Adjusting the quota to reflect current output
► Stock market reaction to last month's deficit
Rule 3
►Drop the ball and measure distance from the target. Measure the distance from the target and go 180 degrees opposite
►Fire a gun…. Adjust in the opposite and fire again
Simply put, your reference point for adjustment is a standard.
More Variation in Different Quadrants
Rule 3 Compensation for Errors
►Illicit drugs. Enforcement improves so drugs become scarcer. The price goes up which stimulates the import of more drugs. The cycle repeats.
►Gambler increases his bet to cover losses
►Farmers doing supply and demand
►Unfilled Slots in appt schedule
Rule 4 There we go to the Milky Way
►Drop the Ball
►Aim at the Last landing place
Examples
► History passed down from generation to generation.
► Worker training replacements in succession
► Adjustment of time of meeting based on last actual starting time.
► Use of last board cut as a pattern for the next board.
► Sitting in a circle with a number of people. One person whispers a secret to the next person who in turns whispers it to the next person and so on.
► Train the trainer
Examples
►Normal Variation
►Tweaking
►Compensating
►Going to the Milky Way
Reorganizations
►1-4 success after 3-4 years
►Start out great and then run out of steam
Why?
Process
►If I implement a change…Does it make a difference…..
Quality templates have information
Enough Theory-Example
Gathering Data-IHI Open School
►Students from College or Medical Schoo
►Faculty from school and clinic
►Students learn 18 courses and receive certification
►Develop projects
►Free
Get Then Together and Do a Project
Where to get materials for projects?
Materials to use
Started a Study
►Shadowing and Interviewing Patients by IHI students
►Initially free
►Purpose 1 Measure Times and Get Impressions of Patients
►Purpose 2 See about Hand Hygiene
Look at what we learned!
Average time waiting 15 minutes Median is 12 minutes
Average time waiting 10 minutes Median in 9
Waiting in Room 12 minutes Median is 9 minutes
Time spent with clinician 19 minutes Median 16.5 minutes
61 minutes is average Median is 62 minutes
Percentages
Look what we have
►15 30 45 minute appts
►50% of the time patients are waiting
►Stable system
►Intervention
Another Project Participation by Design
►This is what is happening with diabetes
What we have done
►Variation….
Bead test
Funnel test
►Examples
IHI open school
Appointments
Diabetes-Participation by design
I have no control!!!
►His response was very quick
►“Go back to your work”
►“ Teach”
►“ Be patient”
►“Share your knowledge
►He most likely would have loved the next painting……
What is the Title of This Painting??
On display at the Getty Center
Crazy parade? Health Care Systems? Chaos?? No….
On display at the Getty Center
Christ Entry Into Brussels 1989! Where is Christ????
On display at the Getty Center
Christ Entry Into Brussels 1989!
►First painting to put Christ in background
►Point is in the crazy parade one person influence only those around him
On display at the Getty Center
Who knows maybe you will
Help change the parade!
Deming thought you could
Homework
►Find a partner
►Select an area of improvement you wish to see implemented and how you might plot the dots!!!!
►http://intqhc.oxfordjournals.org/content/10/1/69.full.pdf
►http://www.statit.com/services/CQIOverview.pdf