Sfgh Quality Leadership Training

Welcome Back Quality Leadership Academy Session 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 Objectives Review 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

Elements of a Control Chart An indication of a special cause

Indicator

UCL X LCL Time

Non-Random Rules for Run Charts

Variation Common Cause vs. Special Cause Common cause Always present Inherent in process Is due to regular, natural, ordinary causes Results in a stable process that is predictable

Special cause Abnormal, unexpected Due to causes not inherent in process Also known as non-random or assignable process

Appropriate Actions to Take Common cause If undesirable need to

Special cause

• Identify and study special change the process. cause If only common cause • If negative, minimize or variation and treat as prevent special cause (tampering), • If positive, build into leads to greater variation, process mistakes, defects

First 24 Observations from Red Bead Data (without outlier employee)

12 Runs expect to find between 8 and 18 runs

On Death, Dying & Data ACCEPTANCE DEPRESSION

BARGAINING

ANGER

DENIAL

On Death, Dying & Data

ACCEPTANCE “I accept the burden of improvement”

DEPRESSION “This feels too hard to do” BARGAINING “The data are right; it is a problem; but it is not my problem.”

ANGER “The data are right, but it’s not a problem” DENIAL “The data are wrong”

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 BMJ 1996 312:619-622

Discussion

Oversight

Lesson #3 Execution 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

• • • •

46

System-level e.g. Hospital mortality rate Cost per admission Adverse drug events per 1000 doses Patient satisfaction scores

Projects Connected to Big Dots * Surgical Site Infection Rate * Percent of un-reconciled medications * Staff reporting positive safety climate * Mortality Rate * Cost per Admission * Adverse Events * Functional Outcomes * Patient Satisfaction * 3rd Available Appointment * Voluntary Turnover

* ER to bed placement time * PACU to bed placement time * ICU to bed placement time * Bed to LTC placement time * Percent of turnover in first year * Employee loyalty

* ICU mortality * Catheter related BSI * Average ventilator days per patient * Adverse events/ICU day 47

* Condition-specific, clinical process indicators * Preventive care measures * Office visit cycle time

A Senior Leader Perspective on Projects Changing the Organization: •HR •IT •Finance •Leadership Processes •Business Strategy •Environmental Strategy

Spreading and Sustaining These Design Concepts: “A Place Where…”

Spreading and Sustaining This Improvement

The Project: e.g., Ventilator-Acquired Pneumonia

Issues at Each Tier (Examples) Tier 1: Big Dot

 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

Tier 2: Portfolio

 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)

Tier 3: Projects

 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) • • •

Bundled orders with opt out 30 degree head of bed elevation marked on walls with tape Now spreading to floor beds post extubation

• • •

Family assistance May 05 to Oct 06: 17 months of NO VAP’s IHI Mentor Hospital

Project Level Measure (Tier 3)

“One Patient, One List”

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

What Changes Can We Make? Understanding the System for Weight Loss Primary Drivers

Outcome

Secondary Drivers

drives

Calories In

Limit daily intake

drives drives drives

AIM: A New ME!

Substitute low calorie foods

Avoid alcohol drives drives

Calories Out drives

“Every system is perfectly designed to achieve the results that it gets”

Work out 5 days drives

Walk to errands

Process Changes

Track Calories

Plan Meals

Drink H2O Not Soda

How Will We Know We Are Improving? Understanding the System for Weight Loss with Measures Primary Drivers

Outcome

Secondary Drivers

Process Changes

• Avg cal/day drives

Calories In drives

• Daily calorie count

drives

drives

AIM: A New ME!

• Weight • BMI • Body Fat • Waist size

Calories Measures let us Out • Monitor progress in improving the • Exercise calorie count system • Identify effective changes

• Running calorie total

• % of Substitute opportunities used

low calorie foods

Avoid alcohol drives

Track Calories

Limit daily intake

plan/week

Drink H2O Not Soda

• Avg drinks/ week

• Sodas/ week

drives

drives

Work out 5 • Days between days workouts drives

Walk to

Plan Mealsoff• Meals

Etc...

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) Total Joint Team Med-Psych Workgroup VAP Prevention Team Perioperative Care Medication Reconciliation Team Perinatal Impact Team Office Practice Team

Clinical Informatics ED Safety Central Line Infection Team Multidisciplinary Rounds Rapid Response Team

OPERATIONS/ QUALITY DRIVERS

Primary Drivers

Leadership and Culture

Care that is; safe, effective, patient centered, timely, efficient and equitable

Deliver the Program

Measurement

Communication

Capacity and Infrastructure

Secondary Drivers •

Ownership of agreed upon set of outcomes

•

Review of outcomes at each meeting

•

Quality and safety comprises 25% of agenda

•

Involve p atients in safety

•

Visible on all senior leader agenda

•

Culture of Safety/Fair and Just

•

Mortality -RRT, Sepsis

•

Medication safety

•

Falls

•

Pressure Ulcers

•

Re-admissions – Transitions

•

Harm/Adverse events

•

Infection-SSI,UTI,V AP,MRSA

•

Infrastructure supports improvement measurement

•

Clear, shared measurement set

•

Inventory national programs and measurements

•

Recov ery plans for unmet outcomes

•

Strengthen IT infrastructure

•

Shared meaningful vision from Board to the patient

•

Expert at communication and marketing methods coaching

•

Program design and str ucture

•

Staff satisfaction

•

Involve Patients in all improvement teams

•

Involve ethics in all improvement and operations

•

Culture of contin uous quality improvement

•

Build Innovation engine

System Level Aims

System Level Aims Planned System Level Aims to begin by 2010 Additional System Level Aims Zero Hospital acquired infections Primary System Aims

Patient overall satisfaction to be >90% Readmission rate to decrease by 30%

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 14 12

Ventilator Days were 777 in 2006 and 645 in 2007

11.6 10.8

10 8 6 4 2 0

1.5

1

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, CEO Contra Costa Regional Medical Center [email protected] safetynethospital.blogspot.com