An-Introduction-to-Quality controle .ppt

QI Theory:
Quality Improvement in the Hospital
Goals for this Primer
• Understand fundamental concepts in
quality improvement
• Identify the environment and key steps for
a successful quality improvement project
• Become familiar with several quality
improvement tools and their use

Quality Improvement:
Bridging the Implementation Gap
Patient care
Progress
Time
How good is American healthcare?

Patient care
Progress
Time
We get it right 54% of the time.
-Brent James, MD, MStat
Executive Director, Intermountain Health Care

Implementation
Gap
Scientific
understanding
Patient care
Progress
Time

Hospitalists and Quality Improvement
• Complex process problems need multidisciplinary
solutions
• We are at the frontlines seeing system failures, process
errors, and performance gaps with our own eyes -- which
is our competitive advantage
• Improved quality delivers:
 better patient care…
 at lower costs…
 with potentially higher reimbursements (pay-for-performance)
…
And it can make our jobs more interesting, fun, and rewarding.

Section I:
Quality Improvement and Change
in the Hospital Atmosphere

Definition of Quality
• Meeting the needs and exceeding the
expectations of those we serve
• Delivering all and only the care that the patient
and family needs

“Definition” of Improvement
It is NOT…
 yelling at people to work harder, faster, or safer
 creating order sets or protocols and then failing to
monitor their use or effect
 traditional Quality Assurance
 research (but they can co-exist nicely)

Principle #1:
Improvement Requires Change
Improvement Requires Change
Every system is perfectly designed to achieve
Every system is perfectly designed to achieve
exactly the results it gets
exactly the results it gets
To improve the system, change the system…

Principle #2:
Less is More
Less is More
You cannot destroy productivity
You cannot destroy productivity
When changing the system, keep it simple

Illustrating Principle #2: Less Is More
Probability of Performing Perfectly
No.
Elements
Probability of Success, Each Element
0.95 0.99 0.999 0.999999
1
25
50
100
0.95
0.28
0.08
0.006
0.99
0.78
0.61
0.37
0.999
0.98
0.95
0.90
0.999999
0.998
0.995
0.99

Understanding Change in the Hospital
Atmosphere
• Change = not just doing something different, but
engineering something different
• at least one step in at least one process
• Hospital Atmosphere = hospitals tend to be viscous,
complex systems with default levels of performance
• change engineered to improve performance can be a foreign
concept - or even overtly resisted

Atmosphere
A Common Strategy Which Commonly Fails:
• Experts design a comprehensive protocol using EBM
over several months
• Protocol is presented as a finished, stand alone
product
• Customization of protocol is discouraged
• Compliance depends on vigilance and hard work
• Monitoring for success or failure is the exception to
the rule (with failures coming to light after patients
are harmed)
• Flawed implementation leads to repetitive efforts
down the road

Atmosphere
High-Reliability Strategies Commonly Succeed:
• Build a “decision aide” or reminder into the system
• Make the desired action the default action (not doing
the desired action requires opting out)
• Build redundancy into responsibilities (e.g. if one
person in the chain overlooks it, someone else will
catch it)
• Schedule steps to occur at known intervals or events
• Standardize a process so that deviation feels weird
• Take advantage of work habits or reliable patterns of
behavior Build at least one - if not more - of these high-
Build at least one - if not more - of these high-
reliability strategies into any changed process.
reliability strategies into any changed process.

Atmosphere
Change engineered to drive improvement depends on…
• Workplace Culture: personnel must be receptive to change
• Awareness: administrative and medical staffs must care
about performance and support its improvement through
change
• Evidence: local experts must identify which research to
translate into practice
• Experience: a skilled team must choose, implement, and
follow up changes to ensure:
1) improvement efforts are ongoing and yielding better
performance
2) productivity is preserved

An Atmosphere for Change
A
AWARENESS
WARENESS
OF THE LOCAL PERFORMANCE GAP
Patient
Medical Staff
Administrative Support
E
EXPERIENCE
XPERIENCE
WITH SIMILAR IMPROVEMENT
EFFORTS
Hospitalist Quality Officer
Hospitalist Quality Officer
Multidisciplinary Team Members
Success Stories From Other Institutions
Success Stories From Other Institutions
E
EVIDENCE
VIDENCE
TO TRANSLATE INTO PRACTICE
“Bedside” Teaching
Didactic Teaching Sessions
Local Expertise in Disease Literature
W
WORKPLACE
ORKPLACE C
CULTURE
ULTURE
READY TO ACCEPT CHANGE
Task Load
Culture of Improvement
Culture of Negative Expectations

A
AWARENESS
WARENESS
OF THE LOCAL PERFORMANCE GAP
Patient
Medical Staff
Hospital Administration
 Patient
At mercy and increasingly aware of
underperforming status quo
Now can access a new resource promoting
transparency in hospital performance:
www.hospitalcompare.hhs.gov
 Hospital Administration
Understands status quo is unacceptable
(IOM, Leapfrog, NQF, JCAHO)
Sees fiscal health tied to performance against
national benchmarks, ability to reduce
costs & LOS, improve margins, and
competitive reputation in the community
 Medical Staff
Has professional responsibility to improve
Knows all too well where system fails
Recognizes that professional livelihood will
depend on paying attention to outcomes:
Pay-for-Performance

E
EXPERIENCE
XPERIENCE
WITH SIMILAR IMPROVEMENT EFFORTS
Hospitalist Team Facilitator
Successful Strategies Used By Others
Hospitalist Team Facilitator 
Technical expert on Quality Improvement
theory and tools
Owns the team process, enforces ground
rules, helps judge feasibility
Teaches the team while doing
Multidisciplinary Team Members 
Chosen for hands-on, fundamental
knowledge of key processes
Inclusive, open, & consensus seeking
Impact not only the change(s) but the
implementation
Successful Strategies Used By Others 
Learn from mistakes of others
Adapt successes of others (tools and
methods): steal shamelessly
Get specific advice in ’Ask the Expert’
forums or other consortiums that collect
and share experience

E
EVIDENCE
VIDENCE
TO TRANSLATE INTO PRACTICE
To an audience of residents or students
To build cadre of “experts” (and to help meet
ACGME requirements)
Download teaching pearls from SHM resource rooms

Decide what changes to make based on the level
of evidence
Establishes team’s credibility
Extends team’s authority when local sub-
specialists or experts participate in selecting
and implementing change

To an audience of peers, administrators, nurses, or
support staff
To boost awareness, knowledge, enthusiasm, and
support
Download slide sets from SHM resource rooms


W
WORKPLACE
ORKPLACE C
CULTURE
ULTURE
READY TO ACCEPT CHANGE
Task Load
Culture of Improvement vs.
Task Load
Be sensitive about piling new tasks onto over-tasked
personnel
Use the input of personnel who will be responsibile for
implementing
Make it easy and desirable to do the right thing

Overcome it, one person and one project at a time
Attach pride to balance between performance
successes and failures
Consider using a ‘cultural survey’ to identify
problems and address them through proper
channels 
Culture of Improvement
Extend it, one person and one project at a time
Advertise successes
Use or adapt this online ‘cultural survey:’
http://www.patientsafetygroup.org/program/step1c.cfm


Section II:
The Multidisciplinary Team

The Driving Force for Change
T
THE
HE M
MULTIDISCIPLINARY
ULTIDISCIPLINARY T
TEAM
EAM
Leverages frontline expertise and experience.
Impacts not only the change/interventions,
but also the implementation

The Driving Force for Change:
The Multidisciplinary Team
A team is not the same as a committee…
Committee
• individuals bring representation
• productive capacity = single most able member
Team
• individuals bring fundamental knowledge
• productive capacity = synergistic (more than the sum of all
individual team members together)

Features of a good team…
• Safe (no ad hominem attacks)
• Inclusive (values all potential contributors including
diverse views; not a clique)
• Open (considers all ideas fairly)
• Consensus seeking

Consensus…
• definition: finding a solution acceptable enough that
all members can support it; no member opposes it
• It is not:
 A unanimous vote (consensus may not represent
everyone’s first priorities)
 A majority vote (in a majority vote, only the majority gets
something they are happy with; people in the minority
may get something they don’t want at all, which is not
what consensus is all about)
 Everyone totally satisfied

Three types of team members…
1) Team Leader
2) Team Facilitator
3) Process Owners (members with operational, hands-on
fundamental knowledge of the process)

Team Leader…
• schedules and chairs team meetings
• sets the agenda (printed at each meeting)
• records team activities (working documents in
binder)
• reports to management (Steering Team)
• often a member of Steering Team

Team Facilitator…
• owns the team process (enforces ground rules)
• technical expert on QI theory and tools
• assists Team Leader
• teaches while doing, within team

Process Owners…
• chosen for fundamental knowledge
• will help implement
• should become leaders (so choose wisely)

Team Ground Rules…
• All team members and opinions are equal
• Team members will speak freely and in turn
 We will listen attentively to others
 Each must be heard
 No one may dominate
• Problems will be discussed, analyzed, or attacked (not people)
• All agreements are kept unless renegotiated
• Once we agree, we will speak with "One Voice" (especially after leaving the meeting)
• Honesty before cohesiveness
• Consensus vs. democracy: each gets his say, not his way
• Silence equals agreement
• Members will attend regularly
• Meetings will start and end on time

A Brief Digression into Quality
Improvement Theory

Defining an Approach to Change
worse better
Quality
After
Before
Quality Assurance
Bell Curve:
Inpatient Population
Tail
Will the team target ‘all’ patients in the
inpatient bell curve, or just a sub-group
considered ‘at-risk’ (depicted in the
outlying tail)? Is the quality of inpatient care
which is not in the tail somehow
‘acceptable?’

worse better
Quality
After
Before
worse better
Quality
After
Quality
Quality Assurance
Bell Curve:
Tail
If the team can identify and define an inpatient sub-group
‘at-risk,’ then improvement efforts could conceivably
focus just on these ‘at-risk’ patients - this is similar to
traditional Quality Assurance. Note that even if tail
events are eliminated, the quality of care for the rest of
the inpatient population (depicted by the unchanged
position and shape of the bell curve) does not improve at
all. While the mean does move toward better care, this is
due only to eliminating statistical outliers.

worse better
worse better
Quality
Quality
After
Before
Quality
worse better
Quality
After
Quality
Quality Assurance
Quality Improvement
Bell Curve:
Tail

better
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:
improvement and standardization in processes reduces
variation (narrows the curve) and raises quality of care for
all (shifts entire curve toward better care). This radical
change is what defines Quality Improvement.

Section III:
Tools for Engineering Change

Engineering Change
• Hospitals have two dynamic levels impacting
performance:
1) Processes
• tasks performed in series or in parallel, impacting patient care
and potentially patient outcomes
2) Personnel
• skilled people with hearts and minds, with variable levels of
attention, time, and expertise

Engineering Change:
What Variables Impact Quality Outcomes of Care?
Structure Processes Outcomes of Care
Inputs Steps Outputs
•Patients
•Equipment
•Supplies
•Training
•Environment
•Inventory Methods
•Coordination
•Physician orders
•Nursing Care
•Ancillary staff
•Housekeeping
•Transport
•Physiologic
parameters
•Functional status
•Satisfaction
•Cost

Engineering Change:
What Variables Impact Quality Outcomes of Care?
Processes
Steps
•Inventory Methods
•Coordination
•Physician orders
•Nursing Care
•Ancillary staff
•Housekeeping
•Transport
The two most dynamic levels impacting performance
Personnel

Engineering Change
• Processes
 all those affecting relevant aspects of patient
care
• clinical decision making, order writing, admission
intake, medication delivery, direct patient care,
discharge planning, PCP communication, discharge
follow-up, etc

Engineering Change
• Personnel
 anybody who touches the patient or a relevant
process in the system
• departments, physicians, clerks, pharmacy,
nursing, RT, PT/OT/ST, care technicians,
phlebotomist, patient transport, administration

Engineering Change:
The Multidisicplinary Team Asks “What?”
• What?
 is the right thing to do?
 will make the system more effective?

Engineering Change:
The Multidisicplinary Team Asks
“Where?”
• Where?
 are the processes to improve?
• Brainstorming
• Multivoting & nominal group technique
• Affinity grouping
 do we start? (dissect and understand the processes)
• Cause and effect diagrams (Ishikawa or ‘fishbone’ diagrams)
• Tally sheets
• Pareto charts
• Flow (conceptual flow, decision flow) charts
• Run charts
• SPC charts
• Scatter charts

Tools for Engineering Change:
Cause-and-Effect Diagram
• sometimes also called a ‘fishbone’ or Ishikawa diagram
• graphically displays list of possible factors, focused on one
topic or objective
• used to quickly organize and categorize ideas during a
brainstorming session, often as an interactive part of the
session itself (the added organization can help produce
balanced ideas during a brainstorming session)

Cause-and-Effect Diagram
Physiologic
Factors
Pharmocologic
Factors
Drug
Administration
Errors
Ordering
Errors
Transcribing
Spelling
Pharmacokinetics
Renal
Dilution
Time
Nurse
Route
Rate
ADE
Nurse
Physician
Pharmacist
Physician
Pharmacy
Nurse/Clerk
Pharmacist
Patient
Physician
Dietician
Patient
Wrong
Drug
Dose
Scheduling
Dosage
Route
Past Allergic
Reaction
Absorption
Weight
Age
Gender
Electrolyte
Hepatic
Race
Pharmacodyamics
Expected
Drug/Drug
Unforeseen
Drug/Food
Drug/Lab
Cognitive
Psychiatric
Compliance
Patient
Errors
Order Missed
Place outcome here
Example: Adverse Drug Events (ADE)

Pareto Chart
• graphical display of the relative weights or frequencies of competing
events, choices, or options
• a bar chart, sorted from greatest to smallest, that summarizes the
relative frequencies of events, choices, or options within a class
• often includes a cumulative total line
• used to focus within a broad category containing many choices, based
on factual or opinion-based information
• can combine factors that contribute to each item's practical
significance

0
10
20
30
40
50
60
70
80
90
100
Percent
Causes
Causes
Pareto Chart
Contributing Causes Contributing to Adverse Drug Events

Sketching Processes or Flow
• Macro Process Maps
• Decision Flow Diagrams

Macro Process Map
The patient is
admitted to the
hospital
The patient is
clinically identified
as having heart
failure
The ejection fraction
is evaluated
is documented in the
chart
< 40%
> 39%
The patient is
prescribed an ACEI
in hospital
The patient is
prescribed an ACEI
at discharge
The patient is not
prescribed an ACEI
in hospital
The contraindication
for an ACEI is
documented in the
chart
The patient is
excluded from the
target population
Example: Heart Failure Core Measures 2-3

Deep Post-Op
Wound Infection
Bacteremia
UTI Pneumonia Other
Prevention
Detection
Treatment
Patient
Preparation
Prophylactic
Antibiotics
Surgery
Post-Op
Wound Care
- Sterile Technique
- Operative Findings
Prevention
Patient
Selection
Antibiotic
Selection
Delivery
- Duration
Prophylaxis
- Timing
Decision Flow Diagram
For iatrogenic infections, any
given type of infection can be
dissected into the hierarchy of
contributing layers.
Contributing layer dissected:
Prevention
Contributing layer dissected:
Prophylactic Antibiotics
Calling out the contributing layers
helps the team think through the steps
ripest for change.

• Our brains understand graphics better than tables
• Tabular information doesn’t convey trends over time very
well
• Keep it simple
• In center of horizontal axis place: baseline mean
performance
• In center of vertical axis place: implementation point
• Can add upper and lower control limits, but usually not
needed
Run Charts

Percent Sliding Scale Insulin Only
0
10
20
30
40
50
60
70
80
Percent
10/20/03
New Order Set
01/20/04
CPOE - TH
Run Charts

Percent with Frank Hypoglycemic Events
0
2
4
6
8
10
12
14
16
Percent
10/20/03
New Order Set
CPOE
TH - 1/04
HC - 8/04
March 2003
Team Forms
Run Charts

Percent with Optimal/Acceptable Glucose Readings
0
10
20
30
40
50
60
70
80
90
100
Percent
CPOE
TH - 1/04
HC - 8/04
10/20/03
New Order Set
March 2003
Team Forms
Run Charts

Engineering Change:
The Multidisicplinary Team Asks “How?”
• How?
 can you make it easy to do the right thing?
• You cannot destroy productivity
– Changes must maintain, or enhance, workplace efficiency or balance
• You must devote as much attention to fitting changes into clinical
work flow as you do to the evidence-based guideline
– Changes must be blended into the flow of clinical care
– Important variables to consider: staffing, training, supplies, physical
layout, information flow, and educational materials

Engineering Change
Improve incrementally. Learn through action.
Improve incrementally. Learn through action.
P
Plan
lan D
Do
o S
Study
tudy A
Act
ct
PDSA PDSA  PDSA  PDSA PDSA  PDSA
Test your changes. Assess their effect.
Test your changes. Assess their effect.
Then re-work the changes and do it again…and again…
Then re-work the changes and do it again…and again…

Engineering Change:
PDSA
(the Benefits of Repeated Cycles)
• Increases belief that change will result in
improvement
• Allows opportunities for “failures” without
impacting performance
• Provides documentation of improvement
• Adapts to meet changing environment
• Evaluates costs and side-effects of the change
• Minimizes resistance upon implementation

Engineering Change:
PDSA
• Overview:
 scientific method for action-oriented learning:
shorthand for testing a change in the real world setting
 test a change by: planning it, trying it, measuring its
results… and then trying to do it better the next time
 multiple rounds of changes – some failures and some
successes - should lead to improved aggregate
outcome

Engineering Change:
PDSA
• Principles for Success:
 start new changes on the smallest possible scale, e.g.
one patient, one nurse, one doctor
 run just as many PDSA cycles as necessary to gain
confidence in your change – then expand
 expand incrementally to more patients
 expand to involve more nurses, more doctors, more
departments
 balance changes within system to ensure other
processes not adversely stressed

What do we want to achieve?
How will we measure our progress?
What changes will drive our progress?
How should we modify our latest changes?
modified from: The Foundation of Improvement by Thomas W. Nolan et. al

Engineering Change
What do we want to achieve?
Set an outcome aim.
(It should be ambitious, must be measurable and must
specify a time-period and a definite population in your
hospital.)
List the outcome aim again, then:
– ask “why” three times,
– ask “how” three times,
– look at the new aim statements, and
– pick the best one
“Function
Expansion”

Engineering Change
What changes will drive our progress ?
Select change(s) to your system, the one(s) most
likely to improve outcomes.
(Recognize that not all changes improve outcomes or
offer balance.)

Engineering Change
How will we measure our progress?
Define what you will measure quantitatively.
(Collect data, chart measures regularly over specified
time-period, and chart against benchmarks & goal lines.)
Principles of Measurement:
Seek usefulness, not perfection.
Integrate measurement into the daily routine.
Use qualitative and quantitative data.
Use sampling.
Plot data over time.
Three Types of Measures:
1) Outcomes
2) Process
3) Balancing measures
(Use a balanced set of measures for all
improvement efforts.)

An-Introduction-to-Quality controle .ppt

Engineering Change
How should we modify our latest changes?
Test your changes.
(Run PDSA cycles to learn from the work setting.)

Engineering Change:
Hints for Success
• Empower nursing
• Expedite order set and protocol passage through appropriate medical staff committees
• Better to implement an imperfect, compromise change than no change at all
• Pilot newest changes on smallest scale
• Provide hot line or support for difficult implementation situations
• Use your new system as a shared baseline, with clinicians free to vary based on individual patient
needs
• Follow metrics continuously as you implement
• Feed metrics back into subsequent PDSA cycles
• Measure, learn, and over time eliminate variation arising from professionals; retain variation arising
from patients
• Keep big picture in mind
• Negotiate ‘speed bumps’
 Time delays in getting data
 Incomplete buy-in
 Go around obstacles instead of through them (can always go back to them later)
 Some who disagree with you may be correct
 Make changes painless as possible: make it easy to do the right thing

QI Theory:
Quality Improvement in the Hospital
• Suggested next steps:
1) Share this primer in QI Theory with other hospitalists in
your group
2) Identify an important QI project at your hospital
3) Lead the QI project using all available resources
4) Learn from your experience and be among the first to
mentor other hospitalists
Use SHM’s topic-specific resource rooms to ask questions,
share experiences & tools, review the literature, and to
download presentations to help you educate others.

Acknowledgments
• Brent James, MD, MStat (Intermountain Health Care's Institute for
Health Care Delivery Research): concepts, content, figures
• Thomas Nolan, PhD (Institute for Healthcare Improvement): concepts,
content, figures
• Greg Maynard, MD, MSc (University of California, San Diego):
editorial composition and review
• Jason Stein, MD (Emory University School of Medicine): editorial
composition

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