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 ContextFocused 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”

Num

ber o

f Em

ploy

ees

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% inThe US federal debt

$50,000 for every man,

woman and childin 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

Perc

ent o

f GD

PFederal Revenue and Spending

0

25

50

75

100

49.251.5

56.459.2

63.668.1 69.9 70.8 73.5

75.4 76.9

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

“We Routinely Achieve Miracles”

Life

exp

ecta

ncy

at b

irth

(yea

rs)

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 StatesNew 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

The Grateful Dead

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 2003Vol 8:2635-2645

Managed Care, November 2003Center for Clinical Evaluative SciencesDartmouth 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, andexperience

Care deliveredBased 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 ProductsNew York: Van Nostrand, 1931

The Birth of Statistical Process Control

Hawthorne Works Plant – Bell Telephone Co., 1925

1923Hawthorne 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

Konosuke Matsushita

Bell Curve:Inpatient Population

worse better Quality

Before

Tail

Defining an Approach to Change

Target all patients, or just a small subgroup considered at-risk?

Acceptable quality?

After

worse betterQuality

After

Quality

Traditional Quality Assurance

Eliminating statistical

outliers

worse betterQuality 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

After

worse betterQuality

After

Quality

worse betterQuality 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 abxadministered

Lab and CXR ordered by MD

Abx ordered by MD

New infiltrate

Yes

CAP Process Flow Diagram (Process Map)

1 2 3 4 5 6 7 8 941.4

141.4

241.4

341.4

441.4

541.4

641.4

741.4UCL 695.4

CL 415.1

LCL 134.8

Time to First Dose Antibiotics

Weeks

Min

utes

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……

MD assesses

Evaluated by MD

CXR completed


Patient triaged



Abx ordered by MD

New infiltrate

Yes


Placed

in ro

om

Evalua

ted by

MD

CXR comple

ted

MD asse

sses

First d

ose A

bx gi

ven

Patien

t Tria

ged

Lab a

nd C

XR orde

red

Abx or

dered

0

50

100

150

200

250

300

350

400

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

27.6%

47.9%

67.5%

76.8%

85.3%91.8%

96.7%

CAP Pneumonia in ED

Process steps

Min

utes

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

MD assesses

Evaluated by MD

CXR completed


Patient triaged



Abx ordered by MD

New infiltrate

Yes


PDSA #1Fast track based on

symptoms

PDSA #2Automatic lab

and CXR

MD assesses

Lab and CXR reports available and MD notified

Patient placed in room per

screening tool

Patient triaged


Lab and CXR performed per protocol

Abx ordered by MDNew infiltrate

CAP Process Flow Diagram (New Process)

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 27126.7

176.7

226.7

276.7

326.7

376.7

426.7

476.7

526.7UCL 497.2

CL 338.4

LCL 179.6

Time to First Dose Antibiotics for CAP

Weeks

MIn

utes

PDSA #1

PDSA #2

240 min

Discussion

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