sfgh quality leadership training
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Welcome Back
Quality Leadership AcademySession 3
“How Do You Know it Works?”Anna Roth, RN, MS, MPH
Report on Projects to Date
• Refine and refresh aim statements
• Share results of our small tests of change
• Will or did you revise your test of change?
• If so, what would/did you revise and why?
Theory
Today’s ObjectivesReview results of your project
Review small tests of change
Review techniques for organizing and displaying data for maximum impact
Your toolkit- Driver Diagram
Share examples of reports designed to get the attention of those who need the information
Action Planning
How will we know?
Why Else Should We Measure?
• You can’t manage what you don’t measure
• How else would you know that your steps are making things better or worse?
• It’s often cause for reward, recognition and celebration
Choosing appropriate statistics
Median v Mean
• 10 people are on the bus• The mean income of the
riders is $50,000/yr• The median income of
the riders is $50,000/yr
• What does this tell us?????
Median v Mean
• The median income of the riders remains $50,000/year
• The mean income is now approx $50 million
• So is the average income of bus riders now $50 million because Bill Gates got on the bus?
Mean
Mean (average)Measures the center, or
middle, of a numerical data set
The sum of all the numbers divided by the total number of numbers
May not be a fair representation of the data
Easily influenced by outliers
Median
Median Also measures the center of a
numerical data set Much like the median of an
interstate highway The point at which there are an
equal number of data points whose values lie above and below the median value
Is truly the middle of the data set
Better measure of CT than the mean when there are outlying values in the data set
Percentage or Percentile?
• Suppose your score on the GRE was reported to be the 80th percentile
• Does this mean you scored 80% of the questions correctly?
Honest Errors
• Arithmetic errors or omissions– Check to see if
everything adds up– Double check even the
basic calculations– Verify the total to put
results in proper perspective; if sample size really small you may not want to use
Excercise
Report Out
Back in 15 minutes
Finding your way/Telling your story
Data Display and Analysis
• How do you want to tell your story??
• Who are you going to tell your story to?
Common types of data display
• Pie charts• Bar graphs• Tables• Time charts• Run charts• Control charts
Charts and Graphs and Spiders Oh My
• Watch for pitfalls• Size matters! • Be aware of tick marks
on the y-axis• 10s, 20s, 100s, 1000s?• Check the scale to put
results in perspective
Sizing up a pie chart
• Do the percentages add up to 100
• Beware of slices that are called ‘other’ if they are larger than many other slices of the pie
• Look for a reported total number of units so you can see how big the pie was before it was divided up
UCL
LCL
X
Indi
cato
r
Time
An indication of a special cause
Elements of a Control Chart
Non-Random Rules for Run Charts
VariationCommon Cause vs. Special Cause
Common causeAlways presentInherent in processIs due to regular, natural,
ordinary causesResults in a stable process
that is predictable
Special causeAbnormal, unexpectedDue to causes not inherent
in processAlso known as non-random
or assignable process
Special cause• Identify and study special
cause• If negative, minimize or
prevent• If positive, build into
process
Appropriate Actions to TakeCommon causeIf undesirable need to
change the process.If only common cause
variation and treat as special cause (tampering), leads to greater variation, mistakes, defects
First 24 Observations from Red Bead Data
(without outlier employee)
12 Runsexpect to find between 8 and 18
runs
On Death, Dying & Data
DENIAL
ANGER
BARGAINING
DEPRESSION
ACCEPTANCE
On Death, Dying & Data
DENIAL“The data are wrong”
ANGER“The data are right, but it’s not a problem”
BARGAINING“The data are right; it is a problem; but it is
not my problem.”
DEPRESSION“This feels too hard to do”
ACCEPTANCE“I accept the burden
of improvement”
Stages of Facing Reality: “To live divided no more”
• “The data are wrong”• “The data are right, but it’s not a problem”• “The data are right; it is a problem; but it is
not my problem.”
“I accept the burden of improvement”
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Crimson Bead Company
“Every system is perfectly designed to achieve the results that it achieves”
Berwick: central law of improvement BMJ1996 312:619-622
Discussion
Oversight
Oversight
Project-level e.g.• % AMI patients getting
evidence-based care• % Pneumonia patients
getting evidence-based care• Time to answer call light on
5 West
System-level e.g.• Hospital mortality rate• Cost per admission• Adverse drug events per
1000 doses• Patient satisfaction scores
Lesson #3 Execution
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Projects Connected to Big Dots
* Mortality Rate* Cost per Admission
* Adverse Events* Functional Outcomes* Patient Satisfaction
* 3rd Available Appointment* Voluntary Turnover
* Condition-specific, clinical process indicators
* Preventive care measures* Office visit cycle time
* ER to bed placement time* PACU to bed placement time* ICU to bed placement time* Bed to LTC placement time
* ICU mortality* Catheter related BSI
* Average ventilator days per patient * Adverse events/ICU day
47
* Surgical Site Infection Rate* Percent of un-reconciled medications* Staff reporting positive safety climate
* Percent of turnover in first year
* Employee loyalty
A Senior Leader Perspective on Projects
The Project: e.g., Ventilator-Acquired Pneumonia
Spreading and Sustaining This Improvement
Spreading and Sustaining These Design Concepts: “A Place Where…”
Changing the Organization:•HR•IT•Finance•Leadership Processes•Business Strategy•Environmental Strategy
Issues at Each Tier (Examples)
Tier 1: Big Dot
Tier 2:Portfolio
Tier 3:Projects
Aims of strategic importance to the system as a whole “Big Dot” measure of progress Executive, Board and Senior Leader engagement Vision and the associated structural changes Strong linkage to finance Learning and mitigation of risks Managing the learning, the politics, and the risks
Understanding “drivers” and causal linkages Outcomes of consequence tracked over time Middle Management key“Connecting the Dots” – putting the learning together Continual readjustment of portfolio Strong linkage to finance Some structural changes (e.g., job roles) Team organization and capacity matter Process and outcome tracked over time Leaders remove obstacles Change concepts help Ability to run PDSA cycles Temporary infrastructures facilitate progress
Project Level Measure (Tier 3)• Family assistance• May 05 to Oct 06: 17 months of NO VAP’s• IHI Mentor Hospital
• Bundled orders with opt out• 30 degree head of bed elevation
marked on walls with tape• Now spreading to floor beds post
extubation
“One Patient, One List”
Project Level Measure (Tier 3)
Project Level Measure (Tier 3)
• % meds unreconciled:admission 25% 3%• % meds unreconciled:transfer 12% 4%• % pre-admit meds unreconciled 19%1%• % of patients with ANY unreconciled
meds decreased from 36% 3%
• Discharge….still testing
Driver Diagrams
PrimaryDriversOutcome
SecondaryDrivers
ProcessChanges
AIM:A New
ME!
Calories In
Limit dailyintake
TrackCalories
CaloriesOut
Substitutelow calorie
foods
Avoidalcohol
Work out 5days
Walk toerrands
PlanMeals
Drink H2ONot Soda
drives
drives
drives
drives
drives
drives
drives
drives
What Changes Can We Make?Understanding the System for Weight Loss
“Every system is perfectly designed to achieve the results that it gets”
How Will We Know We Are Improving?Understanding the System for Weight Loss with Measures
PrimaryDriversOutcome
SecondaryDrivers
ProcessChanges
AIM:A New
ME!
Calories In
Limit dailyintake
TrackCalories
CaloriesOut
Substitutelow calorie
foods
Avoidalcohol
Work out 5days
Walk toerrands
PlanMeals
Drink H2ONot Soda
drives
drives
drives
drives
drives
drives
drives
drives
• Weight• BMI• Body Fat• Waist size
• Daily caloriecount
• Exercisecalorie count • Days between
workouts
• Avg drinks/week
• Runningcalorie total
• % ofopportunitiesused
• Sodas/week
• Meals off-plan/week
• Avg cal/day
Etc...
Measures let us• Monitor progress in improving the
system• Identify effective changes
AIM Primary Driver Secondary Driver
• At your tables write down 4-6 primary drivers for your project
• For each primary driver, come up with 2-3 secondary drivers
• If you have time, write a few small tests of change for each secondary driver
Report Out
Tying it together
Transforming Care at the Bedside (TCAB)
Med-Psych Workgroup
Clinical Informatics
ED Safety
Central Line Infection Team
Multidisciplinary Rounds
Rapid Response TeamOffice Practice Team
Perinatal Impact Team
Total Joint Team
VAP Prevention Team
Perioperative Care
Medication Reconciliation Team
Care that is;
safe, effective, patient-
centered, timely, efficient and equitable
Staff satisfaction
Involve Patients in all improvement teams
Involve ethics in all improvement and operations
Culture of continuous quality improvement
Build Innovation engine
Mortality-RRT, Sepsis Medication safety Falls Pressure Ulcers Re-admissions– Transitions Harm/Adverse events Infection-SSI,UTI,VAP,MRSA
Ownership of agreed upon set of outcomes Review of outcomes at each meeting Quality and safety comprises 25% of agenda Involve patients in safety Visible on all senior leader agenda Culture of Safety/Fair and Just
Shared meaningful vision from Board to the patient
Expert at communication and marketing methods coaching
Program design and structure
Infrastructure supports improvement measurement
Clear, shared measurement set
Inventory national programs and measurements
Recovery plans for unmet outcomes
Strengthen IT infrastructure
Secondary Drivers Primary Drivers
OPERATIONS/QUALITY DRIVERS
Leadership and Culture
Deliver the Program
Measurement
Communication
Capacity and Infrastructure
System Level Aims
System Level Aims
Primary System Aims
Additional System Level AimsZero Hospital acquired infections
Patient overall satisfaction to be >90%
Readmission rate to decrease by 30%
Planned System Level Aims to begin by 2010
Eliminate inequality in at least ten improvement /operational areas by 25%
Reduce Ambulatory Care Sensitive Admissions (ACS) to CCRMC by 15%
Patient engagement on every innovation and improvement team by January 1, 2010
Develop a formal process for engagement of ethics expertise in operations and quality improvement.
Prophylactic Antibiotics One Hour Prior to Incision
Hours of Behavioral Restraint Use
Inpatient Psychiatry: Discharge Care Planning
VAP per 1000 Ventilator Days
11.610.8
1.5 1.3
3.1
0
2
4
6
8
10
12
14
2003 2004 2005 2006 2007
Ventilator Days were 777 in 2006 and 645 in 2007
VAP per 1000 Ventilator Days
Number of VAPs and Ventilator Days
CCRMC 30 Day Readmission Rates
Heart Failure Discharge Instructions Given
Heart Failure Discharge Instructions Given
Aiming for Perfect Care
•Discharge Instructions
•Evaluation of LVS Function
•ACEI or ARB for LVSD
•Adult Smoking Cessation Advice/Counseling
Percent of Patients Who Received All Heart Failure Interventions at CCRMC
Percent of Patients Who Received All Heart Failure Interventions at CCRMC
All-or-Nothing Measurement
Why the time is now
Who will if not you?
What can you do by next Tuesday?
Thank you
Anna Roth, CEOContra Costa Regional Medical Center