Quality Academy Welcome

UAB Medicine Quality Academy
September 30, 2016
Scott E. Buchalter, MD
Welcome!

Session Format
Open discussion – ask questions, raise issues, share experiences…
but please raise hand, to maintain some semblance of order
We will start each session on time…
but there is no guarantee that we will end on time (due to
open discussion format). So…
Feel free to move about….
please be careful of your colleagues

Logistics
• Breakfast and Lunch Friday and Saturday. Breakfast on Sunday.
• Snacks and analgesics tables
• Restrooms out and to the right in alcove
• Breakout rooms across the hall for calls, pages, etc…..
• Remember – audio and video being recorded.
• Reserve the right to cut off some discussion, depending upon the
amount to be covered

Session Context
Focused on clinical medicine
• Based on professional values
• Using examples from a variety of sources
Redundant –
• Intense study and discussion
• At home: read, rethink, consolidate; discuss and experiment
with teams
• Meet again to re-explore and build on what we learn
Clinical QI is not particularly linear –
• Theory mixed with practical tools
• Things immediately useful mixed with longer term strategies
• Methods mixed with management philosophy
• System-level structural issues mixed with pragmatic front-line issues
All cross-linked –
• requires a willing suspension of disbelief until we have enough of the
paradigm tied together to judge it as a whole

Course Structure
Meet four times –
• Theory and QI tools
• Methods and Measurement
• Patient Safety
• Leadership and Project Presentations
With significant intervals – better for learning,
and essential for teams and projects
On-line learning with modules
Major goals –
• Lead/ facilitate clinical and operational improvement
• Serve as internal consultant on clinical QI and Patient Safety
• Teach QI and Safety to others
• Improve patient care
• Help us cross the chasm – be the “tipping point”

It Really is About Changing Culture
1962
Diffusion of
innovations is a
theory that seeks to
explain how, why, and
at what rate new ideas,
Improvements, and
technology spread

What is Diffusion of Innovation*?
A process by which any innovation diffuses
through certain channels and then adopted over
time among members of a social system
(population, organization, business)
*An innovation is the introduction of a new
or different idea, method, process,or
device

Involvement of People in a System
The chasm
“tipping point”
NumberofEmployees
Time• Visionaries
• Techies
• Tenacious enthusiasts
• Massively improve
patient care
• Opinion leaders
Pragmatists Conservatives
Skeptics

The Adoption Rate – The S Curve

Edwards Deming
The chasm
“tipping point”

Setting the Stage for QI
1) Modern Medicine – The Best the World has Seen?
Make the case for the cost of care and the financial imperative
for improving outcomes and eliminating waste.
2) Managing (Clinical) Processes
Review the hx of process management in business, the complexity of
medicine, and the history of QI
3) Challenges in Healthcare: Fixing What Ails Us and Setting
the Stage for Improvement
Introduce the basics of QI, the rationale, and the theory behind
reduction of variation

Modern Medicine:
The Best the World Has Ever Seen?

Dr. Smith Goes to Washington
 46 million people without health insurance
 Cost increases that are bankrupting the
country
The roots of reform……….

Since 2000, an increase of 165% in
The US federal debt
$50,000 for
every man,
woman
and child
in the US
U.S Federal Debt 1971 - 2012
The Rise in Federal Debt is Unsustainable
The Roots of Health Care Reform

The rise in health care
costs quickly outpaces revenue
PercentofGDP
Federal Revenue and Spending

49.2
51.5
56.4
59.2
63.6
68.1 69.9 70.8
73.5
75.4 76.9
0
25
50
75
100
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
“We Routinely Achieve Miracles”
Lifeexpectancyatbirth(years)
Since 1960, 6.97 years gained over 4 decades = 1.74 years/decade
(from 1900-1960, 20.7 years gained over 6 decades = 3.45 years/decade)
Cutler DM, Rosen AB, et al. The Value of Medical Spending in the United States
New Engl J Med 2006; 355(9): 920-7 (Aug 31)

Total Health – What’s Driving Health
Behavior
Genetics
Environment / Public Health
Health Care Delivery (Hospitals and Clinics)
40%
30%
20%
10%
• Tobacco
• Drug and Alcohol Abuse
• Movement Deficit Disorder
• Sexually-transmitted disease
• Violence, accidents, and suicide
• Teenage pregnancy

Medicare Patients with Acute MI

Managing Processes and
Clinical Care

The Probelmes with Taylorism
Taylor had very precise ideas about how to introduce his system:
Workers were supposed to be incapable of understanding what they were
doing. According to Taylor this was true even for rather simple tasks. “I can
say, without the slightest hesitation,” Taylor told a congressional committee,
“that the science of handling pig-iron is so great that the man who is…
physically able to handle pig-iron and is sufficiently phlegmatic and stupid
to choose this for his occupation is rarely able to comprehend the science
of handling pig-iron”
Taylor believed in transferring control from workers to management. He set
out to increase the distinction between mental (planning work) and manual
labor (executing work). Detailed plans specifying the job, and how it was to
be done, were to be formulated by management and communicated to the
workers.[11]
Problems with Taylorism?

Quality improvement is the science of managing
processes. It is a way of thinking that happens to
have some tools attached.
• Framework of ideas
• Makes statistics and probability relevant,
understandable, and useful
• Action to improve the underlying (causal)
process
Donald J. Wheeler

2000 2001
Institute of Medicine
98,000 deaths due to error Massive gaps in care delivery

McGlynn EA et al. NEJM 2003
Vol 8:2635-2645

Managed Care, November 2003
Center for Clinical Evaluative Sciences
Dartmouth Medical School
Practice Variation

Synthesize
information
Care decisionsEvidence
Influencing Factors
• Clinical preferences (training, experience)
• Existing local “norms”
• Resources
• Financial incentives
• Legal considerations
• Patient preferences
• Errors and complications
• Worsened outcomes
• Increased costs
• Massive waste
• Poor experience
Results
David Eddy, MD, PhD
Variation

The Problem is Variation
Routine
Medical Practice
Evidence in published
scientific research
Opinion, training
patterns,
environment, and
experience
Care delivered
Based on
evidence
Variation
25%
75%
55%
• Errors
• Increased cost
• Poor outcomes

The Problem: Variation
1911 – Frederick Taylor - Principles of Scientific Management
(standardized mass assembly
production)
1924 – Walter Shewhart – Economic Control of Quality of
Manufactured Product (statistical
process control)
1950 – Edwards Deming – Elementary Principles of the
Statistical Control of Quality
(System of profound knowledge;
Refined process control and PDSA)

Walter Shewhart
Economic Control of Quality of Manufactured Products
New York: Van Nostrand, 1931
The Birth of Statistical Process Control

Hawthorne Works Plant – Bell Telephone Co., 1925

1923
Hawthorne Works Plant - Today
• 1923 - National Research Council est.
Committee on Effect of Illumination on
Efficiency… Chair Thomas Edison
• 1924 – Western Electric invited to reproduce
these findings at Hawthorne plant
• First study – no relationship
• Six women in separate room, thirteen
sequential time periods / lighting
• Productivity rose independent of lighting
• Conclusion was productivity rose as result
of subjects being observed
• Became known as the Hawthorne effect
• Advanced through Management curricula at
Harvard Business School

 May 1924 at Hawthorne, Shewhart sent his boss a one page
memorandum outlining his theory and invention for using statistics
in operations and manufacturing.
 It contained a half-page drawing of what we now know as a
control chart
 This first control chart launched statistical process control, and
was the real beginning of the Quality Improvement movement
in this country
 Shewhart's work pointed out the importance of reducing variation
in a manufacturing process and the understanding that continual
process- adjustment in reaction to non-conformance actually
increased variation and degraded quality. Today, we often call this
tampering.
The Beginning of QI

Shewhart’s First Control Chart

• PhD in Mathematics and Physics from Yale in 1928
• Worked as consultant to the Dept of Agriculture and
met Shewhart in 1927. Took Shewhart’s ideas and
developed them into his theories of management,
including statistical process control and PDSA.
• He taught these techniques to the Japanese after the
war, transforming their industry into world leaders in
productivity and profit.
• One reason he learned so much from Shewhart, Deming
remarked in a videotaped interview, was that, while brilliant,
Shewhart had an "uncanny ability to make things difficult.”
Deming thus spent a great deal of time both copying
Shewhart's ideas and devising ways to present them with
his own twist.
• Transmissions – Ford vs Japanese. 1980 documentary – after which Ford, with
Demings help, became most profitable US Auto Co.
Edwards Deming

If you can't describe what you are doing
as a process,
you don't know what you're doing.
W. Edwards Deming

Bell Curve:
Inpatient Population
worse
Before
Tail
Defining an Approach to Change
Target all patients, or just a small subgroup considered at-risk?
Acceptable quality?

worse
After
Quality
Traditional Quality Assurance
Eliminating
statistical
outliers

worse Quality
better
If the team identifies a performance gap applicable to a wider patient population,
the team may design changes in processes with the potential for dramatic effect
Quality Improvement

worse
After
Quality
worse Quality
better
Improvement and
standardization in
processes reduces
variation (narrows the
curve) and raises quality
of care for all (shifts
entire curve toward
better care).
Defining
Quality Improvement

Understand Processes by Understanding Variation
Process
Type and distribution of data
(inherited from the process)
Understand process variation and probability
What does this tell us about the process?
Stable
(Random or common
cause variation)
Unstable
(Special or assignable
cause variation)
- Mean (average)
- Variation (SD)
- Probability
Control chart

hh
Special
Cause
Variation
Special
Cause
Variation
Common Cause Variation
Understanding Variation

Shewhart Control Chart – The Basics

Statistical Process Control Chart

Quality Improvement: W. Edwards Deming
Organize everything around
value-added (front-line) work
processes
Quality improvement is the science of process
management. It creates a framework for identifying,
analyzing, and improving clinical processes
effectively and efficiently

Fundamental Knowledge
- There is a difference between theory and reality
- Theory is an abstraction and an oversimplification
- Reality is the special circumstances and daily
work-arounds that define the actual work. It lives in
the mud and the weeds at the front line. The devil
really is in the details.
- Healthcare processes are complex. Organizations
store their process knowledge in their employees
- Most process-based work is done by teams
The key question for improvement….
How do we tap front-line workers’ fundamental
knowledge?

100% Participation : Putting Everyone to Work*
• Every employee is responsible to improve within
their own work environment
• This means that everyone has two jobs:
- 95% of the time: do their regular job
- 5% of their time: improve how they do their regular job
• Leaders are responsible for providing:
- tools and training to improve
- the time, usually structured as part of work assignments
- the vision and resources
…..So that local teams can improve
* Dr. Brent James

Low Hanging Fruit
Ground fruit
“logic and intuition”
Low Hanging Fruit
“incremental improvement of processes”
Sweet Fruit
“System redesign”

The Problem: Variation
 Often, our inside-out view of healthcare is based on
average or mean-based measures of our recent
past.
 Healthcare organizations and patients don’t feel
averages. They feel the variance in processes or
procedures.
 Quality Improvement focuses first on reducing the
variation in a process and then on improving the
process design, or capability.
 Organizations value consistent, predictable business
processes that deliver world-class levels of quality.
Organizations Feel the Variance, Not the Mean

Which Improvement Methodology is Best?
 Model for Improvement
 PDSA
 Focus – PDSA
 Lean
 Six Sigma

Plan
Do
Study
Act
Identify a problem
Organize a team
Define the process
Understand process
performance - data
Choose a process
change
• Framework for most
improvement methodologies
• QI tools are the enablers
• 8 Tools for Quality
Improvement and Patient
Safety
 Brainstorming
 Affinity diagrams
 Process mapping
 Run charts
 Control charts
 Pareto charts
 Fishbone diagrams
 Root cause analysis

Reduce Observed/Expected Mortality for UAB Hospital
Respiratory Failure
Pneumonia
CAP
Appropriate antibiotics within 4 hrs
What might be the AIM statement?

• Decrease O/E mortality for UAB Hospital
by 10% by March 1, 2016
• Decrease observed mortality at UAB Hospital
for CAP by 20% by March 1, 2016
• Decrease time to first antibiotic dose in patients
with CAP by 20% by July 31, 2016
Possible Aim Statements

Understand the Current Process
• Identify how the process is currently taking place (the
process as it is). Go observe.
• Generate a process map to represent the sequence of each
step.
• Collect baseline data about the current process.
• Determine if there is a best practice internally or externally
• Analyze baseline data compared to best practices - literature,
opinion experts, and published guidelines
• This may help fine-tune your AIM statement
• Brainstorming
• Affinity analysis
• Fishbone
diagrams
• Tally sheets
• Pareto charts
• Process maps
(flow charts)
• Run charts
• Control charts

MD assesses
Evaluated by MD
CXR completed
Patient placed
in room
Patient triaged
First dose abx
administered
Lab and CXR
ordered by MD
Abx ordered
by MD
New infiltrate
Yes
CAP Process Flow Diagram (Process Map)

UCL 695.4
CL 415.1
LCL 134.8
41.4
141.4
241.4
341.4
441.4
541.4
641.4
741.4
1 2 3 4 5 6 7 8 9
Minutes
Weeks
Time to First Dose Antibiotics
Target=240 min

Reduce Observed/Expected Mortality for UAB Hospital
Respiratory Failure
Pneumonia
CAP
Appropriate antibiotics within 4 hrs
Clinical and operational processes within the ED (triage, patient
flow, staffing, room turnover, hospital census, screening for
symptoms and CXR, medication dispensing system……

124
91 88
42 38
29 22 15
27.6%
47.9%
67.5%
76.8%
85.3%
91.8%
96.7%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
50
100
150
200
250
300
350
400
Placed in
room
Evaluated by
MD
CXR
completed
MD assesses First dose
Abx given
Patient
Triaged
Lab and CXR
ordered
Abx ordered
Minutes
Process steps
CAP Pneumonia in ED

MD assesses
Evaluated by MD
CXR completed
Patient placed
in room
Patient triaged
First dose abx
administered
Lab and CXR
ordered by MD
Abx ordered
by MD
New infiltrate
Yes
CAP Process Flow Diagram (Process Map)
PDSA #1
Fast track
based on
symptoms
PDSA #2
Automatic lab
and CXR

MD assesses
Lab and CXR
reports available
and MD notified
Patient placed
in room per
screening tool
Patient triaged
First dose abx
administered
Lab and CXR
performed
per protocol
Abx ordered
by MD
New infiltrate
CAP Process Flow Diagram (New Process)

UCL 497.2
CL 338.4
LCL 179.6
126.7
176.7
226.7
276.7
326.7
376.7
426.7
476.7
526.7
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
MInutes
Weeks
Time to First Dose Antibiotics for CAP
PDSA #1
PDSA #2
240 min

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