mark graban shs 2014: two data points are not a trend: using spc to manage better
Post on 14-Sep-2014
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Healthcare leaders often make bad decisions due to a lack of statistical understanding. This session will remind attendees that simple comparisons of two data points or comparisons to goals and targets can be misleading. Control charts allow us to better validate project success and make better ongoing management decisions. It’s far too easy for improvement facilitators to draw incorrect conclusions about the success of their Lean event or Six Sigma project if they are simply comparing before and after performance. Likewise, healthcare leaders make bad decisions when they are likewise comparing two data points (today versus a previous month or year or today versus a target). Basic Statistical Process Control (SPC) methods, like control charts, are a simple and proven alternative. Key Learning Objectives 1) Understand some of the common pitfalls in the creation and use of performance measures in various healthcare settings 2) See statistical chart analysis methods that allow for the best management decision making, such as knowing if we are improving and if a "bad day" requires investigation or if it is merely "noise" in the system's performance 3) Connect key principles of Lean management and the Deming philosophy into modern KPI and metrics management By the end of this session attendees will 1) Understand the importance of "control charts" for management decision making 2) Be able to create and interpret a basic management control chart 3) Know of other resources for more learning Mark Graban is author of the Shingo-Award winning book "Lean Hospitals: Improving Quality, Patient Safety, and Employee Engagement." Mark is also co-author, with Joe Swartz, of "Healthcare Kaizen: Engaging Front-Line Staff in Sustainable Continuous Improvements" (also a Shingo recipient) and "The Executive Guide to Healthcare Kaizen." He serves as a consultant to healthcare organizations through his company, Constancy, Inc and is also the Chief Improvement Officer of the technology company KaiNexus. Mark has a B.S. in Industrial Engineering from Northwestern University and an M.S. in Mechanical Engineering and an M.B.A. from the Massachusetts Institute of Technology’s Leaders for Global Operations Program. Mark and his wife live in San Antonio, Texas.TRANSCRIPT
Two Data Points Are Not a Trend: Using SPC to Manage Better
Mark GrabanVP of Innovation & Improvement Services, KaiNexus
#shs2014 @MarkGraban
Slides & Audio: www.MarkGraban.com/SHS2014
Key Management Questions
• How are we performing?– Are we getting better or worse?
• What action should we take?
Some rights reserved by Marco Bellucci
Or Not Take Action“Management must understand the
theory of variation: If you don’t understand variation and how it comes from the system itself, you can only react to every figure.
The result is you often overcompensate, when it would have been better to just leave things alone.”
W. Edwards Deming
My Most Favorite Book Ever
http://www.spcpress.com/Amazon: http://bit.ly/wheeler-book
Donald J. Wheeler, PhD
“No data have meaning apart from their context”
Comparisons of 2 Data Points
1992 1995 1998 2001 2004 2007 20100
0.20.40.60.8
11.21.41.61.8
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Fatalities per 100 Million Vehicle Miles Traveled (U.S. & CT)
U.S.
CT
Need to Look for Trends
“You don't want to make a big conclusion based on just one year.”
– Jonathan Adkins of the Governors Highway Safety Association
“Office Space”
2-Point Comparisons in Politics
47%46%
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Did We Improve?
Run Charts Show More Context
2 Data Points Lack Context
• Total triage cycle time was reduced by 23 minutes
• Total ED-IP cycle time was reduced by 33 minutes
• Average LOS decreased from 97 to 61 minutes
Source: Case study, “Harris Methodist saves $648,695 through SIPOC process changes”
What About the Other Data Points?“The average patient satisfaction
increased from 87.2 to 89%”
The Good News…
There is a better way:SPC charts
“X” Control Chart(Chart for Individual Values)
“Every system is perfectly designed to get the results it gets.” (Deming)
Goal = 25 minutes
X and MR Chart Combo
Applications of SPC Charts• Monthly employee attrition %• Daily % of patients discharged before 11 am• Daily lab test turnaround times• Weekly patient satisfaction scores• Daily % of on-time case starts• Daily % of patients who arrive late / no-show
Small Business Revenueas a Stable Process?
X chart
MR chart
Deming’s 7 Concepts of Variation1. All variation is caused – specific reasons2. There are 4 types of causes:
1. Common causes 2. Special causes 3. Tampering 4. Structural
3. Managers must distinguish amongst these– Each one requires different managerial actions
Deming’s 7 Concepts of Variation4. For special causes, get timely data5. For common causes, all data are relevant – In-depth knowledge of the process being improved is
needed – statistics, flow charts, Pareto, stratification analysis, DOE
6. When all variation is common cause, the system is said to be “stable” and “predictable”
7. SPC limits let a manager predict future performance with some confidence
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Responding to Daily Changes?
KB
Daily Length of Stay Average
Praise Team
PTPT
Are we helping? Is this process stable?
KBKick Butt
So we should do nothing?
“Don’t just do something, stand there.” -- Deming
Creating a Control Chart
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Upper Control Limit
Lower Control Limit
“Western Electric” Rules (1956)• 8 consecutive points on same side of mean
• 6 consecutive points moving same direction
• 14 alternating up/down points in a row
• Any single point above or below 3-sigma LCL or UCL
– Full rules http://bit.ly/WErules
Step 1: Initial Data – LeanBlog.org• Generally need 20 data
points to calculate control limits
Step 2: Mean & MRs• Calculate mean of the
first 20 points• Calculate the moving
range of the first 20 points– Ex: =ABS(E5-E4)
Step 3: Draw Initial Chart(with Mean line)
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Step 4: Add Control Limits• Calculate “MR-bar”– Average of the 1st 19
MRs• Calculate Control Limits
– LCL = Mean – 3*(MR bar)/1.126– UCL = Mean + 3*(MR bar)/1.126
Step 5: Review Chart & Limits
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Special Cause?
Step 6: Revise Limits
Step 7: Evaluate Over Time
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Step 7: Evaluate Over Time
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Step 8: Shift the Limits
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Testing for Process Shifts• If you made a change that you expected to improve the system,
use a control chart to test the hypothesis
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Process Shift
Daily TAT
Long-Term Process Shifts
NOT Understanding Variation Leads To…
• Pressuring people to get better results by working harder within the same system
• Wasting time looking for explanations of a perceived trend when nothing has changed
• Taking other actions when it would have been better to do nothing
• Not focusing on systemic improvements
Isn’t it always the system?
It’s (almost) always the system.
Q&A / Contact Info• President, Constancy, Inc.
– www.constancy.us• VP of Professional Services, KaiNexus
– www.KaiNexus.com • Founder, LeanBlog.org
– [email protected]• Twitter @MarkGraban• Books: www.MarkGraban.com
Backup Slides
The Funnel Experiment
• Lloyd Nelson, 1987– Suspend a funnel on a stand a
few inches off the ground– Drop 50 marbles
x
A “Stable” System
• Does NOT mean:– Zero variability– System meets customer
requirements
• It only means:– Causes of variation are basically constant over time
We Have to Try Harder!!!• 4 different rules for adjusting the funnel
No adjustmentAdjust relativeto last position
Adjust relativeto center
Learn more – online simulator at http://www.symphonytech.com/dfunnel.htm