[PPT] - CMS Quality Improvement Workshop Series QI 101 Webinar 3: Measuring PowerPoint Presentation

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CMS Quality Improvement Workshop Series QI 101

Webinar 3: Measuring and Monitoring Improvement

Karen LLanos, Center for Medicaid and CHIP Services Kamala D. Allen, MHS, Center for Health Care Strategies Jane Taylor, MBA, MHA, Ed.D., National Initiative for Children’s Healthcare Quality

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Agenda

Welcome and Introductions
Purpose and Learning Objectives
Recap of Webinar 2: Developing Aims and Selecting

Change Strategies

Linking Driver Diagrams to the Plan-Do-Study-Act (PDSA)

Cycle

Using Data and Measuring Improvement
Question and Answer

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Learning Objectives for Webinar 3

Purpose: Enable state Medicaid and CHIP staff to

improve child and adult health care outcomes using the Model for Improvement

Participants will learn how to:
Link driver diagrams to the Plan-Do-Study-Act cycle
Incorporate measures for improvement into a QI project to

address the final question of the Model for Improvement

How will we know a change is an improvement?

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Recap from Webinar 2: Developing Aims and Selecting Change Strategies

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The Improvement Guide, API, 2009

Model for Improvement

What are we trying to accomplish? ' How will we know that a change is an improvement? What change can we make that will resuit in improvement?

Act Plan

Do

Medicaid/CHIP

Health Care Quality Measures

The Model for Improvement

Model for Improvement

What are we trying to accomplish? ' How will we know that a change is an improvement? What change can we make that will resuit in improvement?

Act Plan

Do

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From Aim… to Changes… to Results

Linking together the components of the Model for Improvement

Aim: For whom, how much, by when?
Changes: Driver diagrams and testing changes
Results: Using data related to the driver diagram to measure

results

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Aim Statement Example

By May 1, 2015, we will create medical homes in at least half the pediatric primary care clinics in the state so that:

At least 95 percent of children have well child visits that are up to date
At least 95 percent of children have a medication allergy check upon

receiving a new prescription

At least 95 percent of visits have

a medication reconciliation if the child is on medication(s)

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Medical Home Learning Collaborative Driver Diagram

Secondary Drivers Primary Drivers Outcomes

Create Pediatric Medical Home

Improved: 1) Clinical outcomes 2) Family experience 3) Team experience 4) Efficiency & reduced costs

Family Centered Care Continuous Medical Home Care Team Comprehensive Coordinated Care Community Systems Improvement Engaged Leadership

Treat family as equal partner in care
Co-create care plan
Provide access to information
Include family members on improvement team
Develop cultural competency
Define roles & responsibilities for each member of the care team
Enhance internal communication
Prepare in advance for visits
Streamline office flow
Ensure continuous care team
Provide preventive care and anticipatory guidance
Coordinate primary care, specialty care & other services
Support timely transition into adult life planning
Link family to community support
Create support systems with community programs, service

agencies, and public organizations including Title V, schools, AAP & AAFP chapters, Family Voices

Implement quality improvement methods and training
Leverage HIT: use registry, visit management, EBC at point of care
Improve access
Secure appropriate payment
Set the direction and display curiosity about Medical Home
Plan for sustainability and spread
Foster a culture of partnerships
Develop alliances and cooperative relationships, advocacy
Align policy and procedure
Use data transparently

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Linking Driver Diagrams to The Plan-Do-Study-Act Cycle

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Four Steps of the PDSA Cycle

Tradition of the scientific

method

Made pragmatic
Assumes that

improvement is continual, never ending

Act Plan Study Do

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Please Complete the Poll on the Right Side of Your Screen

Question: Have you ever used PDSA cycles for

improvement?

Responses (choose one):
a. Yes, I have used PDSA cycles for improvement
b. No, I have not used PDSA cycles but I am planning to
c. No, I have not used PDSA cycles

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Example of PDSA Cycles

zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA Aim: Create continuous care team

Purpose of test: Improve

Improved

communication within care team

communication and preparation

Will huddles improve communication?

A P S D A P S D Cycle 1: Define a time to meet and share info about day Cycle 2: Cycle 4: Standardize time and script Cycle 5: Test for 1 week; then add other care teams Change time, introduce script Cycle 3: Test both sessions

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Testing in Parallel Speeds Up Improvement: Practice Level

Family Continuous Community Care Coordination Centered Care Team Support Care

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Testing in Parallel Speeds Up Improvement: State Level

Payment Medical Home Learning Evidence-based Reform Certification Community Care

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Data Collection During PDSA Cycles

Collect useful data, not perfect data
The purpose of the data is learning, not evaluation
Qualitative data counts
What are providers, health plans, families, and patients saying?
What are staff and other stakeholders saying?
Qualitative data is a leading indicator; it is available before quantitative

data and serves as an early herald

Keep all data collection simple: measurement is important but in

service of improvement

Paper and pencil still work
For improvement, a simple sample works
Collect and make use of baseline data before starting improvement

work

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PDSA Worksheet: What Changes Are We Testing and Why?

PLAN: What questions does this test seek to answer? (If I do x, will y happen?) What is your plan for this test or change? Who? What? When? Where? What is your plan for data collection? Who? What? When? Where? What do you predict the result will be? DO: Carry out the change or test, collect data, and begin analysis. STUDY: Compare what happened to the prediction. Complete analysis of data, summarize what was learned. ACT: Are we ready to make a change? Plan for the next cycle.

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Questions?

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Using Data and Measuring Improvement

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How Do We Know that a Change is an Improvement?

Improvement is about making changes to systems, not

measurement

Measurement plays an important role
Key measures are required to assess progress toward

the aim

Specific measures can be used for learning during PDSA

cycles

Map your measures to your driver diagram

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Quality Improvement Uses Three Types of Measures

Outcome measures
Results or aim of the project
Usually relate to an overall system improvement or a clinical outcome
Process measures
Reflect how the improvements are done
They are more sensitive to change than the outcome measures
Balancing measures
May reflect volume
May include staff and constituent experience
Reflect unintended consequences of change to other parts of the

system or other systems

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Family of Measures: Medical Home

Outcome
Percentage of patients with well child visits up to date
Percentage of patients with appropriate asthma care
Percentage of patients with ADHD care elements in place
Process
Percentage of patients with medication reconciled every visit
Percentage of patients with medication allergies checked each visit
Percentage of patients assigned to a care team
Balancing
Family experience data (CAHPS survey)

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Measurement is Central to Understanding Improvement

The purpose of measurement is for learning, not judgment
Measures should be linked directly to the improvement

aim statement

Process measures should also be used to guide

improvement and show if testing is working

Stratification can help understand and assess

improvement

By physician or practice
By location (e.g., county)
By patient population (e.g., specific problem, demographics, health

plan)

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Using Data to Drive Improvement

Establish baselines
Monitor changes
Analyze data to determine if there is

improvement

Identify which changes contributed to

improvement and which changes may be ineffective

Are we ‘holding the gain’ (i.e., keeping improvement

going)?

Compare performance across providers,

practices, plans, communities

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Gathering and Using Baseline Data

Use whatever baseline data you can find
If you can’t find the exact measure you want,

use a surrogate measure that reveals information about the system

Use as much data as you can find before the

interventions or changes

If you don’t have data before the interventions or

changes, use the first data points that are available; they will be close to the baseline

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How to Create a Baseline and Monitor Changes

100 90 80 70 60 50 40 30 20 10

Baseline

Extend the median into the future - this makes improvement visible

Interventions began

Virtual

120 100 80 60 40 20

Changed payment Introduced learning community protocol

Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Week 12 Week 13 Week 14 Week 15 Week 16 Week 17 Week 18 Week 19 Week 20 Week 21 Week 22 Week 23 Week 24 Week 25

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Please Complete the Poll on the Right Side of Your Screen Question: Your state has identified a high-priority improvement project and you don’t have baseline data. What would you recommend?

Responses (choose one):

a. Select another project
b. Wait until we can collect some data and then start the

project

c. Trust that the early data points are a surrogate baseline

and begin the project without historic data

d. Use data from a similar population (such as a sample of

medical records) to help benchmark current performance

e. Both c and d

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First test of

100 90 80

How is the process

performing?

70

Are we improving?

60 50

Are we holding the

40 30 20

gains?

10

change

Using Run Charts to Measure Improvement

First test of

100 90 80

How is the process

performing?

70

Are we improving?

60 50

Are we holding the

40 30 20

gains?

10

change

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Example of How to Annotate Changes on a Run Chart

Baseline Testing Successful Testing Begin implementation

n pilot unit

Evidence of improvement during implementation

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Plot small samples frequently over time

Observed Data Value (e.g., Readmission Rate)

Annotate change 1 tested Annotate change 2 tested

Time Order (e.g., Month)

Tracking Changes on an Annotated Run Chart

Plot small samples frequently over time

Observed Data Value (e.g., Readmission Rate)

Annotate change 1 tested Annotate change 2 tested

Time Order (e.g., Month)

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Thank you to IHI and API for this slide presented at the Office Practice Summit 04/07/13 Phoenix

Rules for Run Charts

A Shift: 6 or more An astronomical data point Too many or too few runs A Trend: 5 or more

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Using Run Chart Rules to Understand Improvement

*Data from Ohio Perinatal Quality Collaborative, CMS Neonatal Outcomes Improvement Project

Percent distribution of Ohio full term and near term births, by month

10 20 30 40 50 60 70

Percent

January 2006 to May 2010

Medians were calculated from the initial 24 months, January 2006 to December 2007. OPQC inception Since OPQC inception, 9,000 expected near-term births statewide were delayed to f ull-term.

Near term (36-38 wks) Full term (39-41 wks) Median, near term Median, full term

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Please Complete the Poll on the Right Side of Your Screen

*Data from Ohio Perinatal Quality Collaborative, CMS Neonatal Outcomes Improvement Project

Percent distribution of Ohio near term births, by month January 2006 to May 2010

Percent

40 35 30 25 20 15 10 5

OPQC inception Since OPQC inception, 9,000 expected near-term births statewide were delayed to f ull-term.

Near term (36-38 wks) Median, near term

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Poll Question and Responses

Question: Looking at the blue data in the run chart, what do you see? Responses (choose one):

a. Evidence of a shift in the data (6 points in a row above or

below the median)

b. Evidence of a trend in the data (5 points steadily

ascending or descending)

c. Astronomical point
d. Evidence of both a shift and a trend in the data

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SLIDE 34

How a Summary Statistic May Mask Trends

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Source: Institute for Healthcare Improvement & API, The Improvement Guide,2nd ed. pp 149-150

10 20 30 40 50 60 70 80 90 100

date Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Change Made

Cycle Time (min.)

10 20 30 40 50 60 70 80 90 100

date Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Change Made

Cycle Time (min.)

10 20 30 40 50 60 70 80 90 100

date Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Change Made

Cycle Time (min.)

Practice 1 Practice 2 Practice 3

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Questions?

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Examples of Using Data for Asthma Care

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~

70

60

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50 40

100

90

Emergency Department for Asthma

Goal Jan- Feb- Mar-

Apr-

May- Jun- Jul- 00 Aug- Sep- Oct- Nov- Dec- Jan- Feb- Mar- 00 00 00 00 00

00 00 00 00 00 00

0 1 0 1 0 1

+-
+-
+-
+-
+-
+-
+-

Symptom-free days

Goal

----- --- -- - -- - - - - ------ --- --------------·

..- _..

Jan- Feb- Mar-

Apr-

May- Jun- Ju l-00 A ug- Sep- Oct- Nov- Dec- Jan- Feb- Mar- 00 00 00 00 00 00 00 00 00 00 00 0 1 0 1 01

Treatment with maintenance anti-inflammatory medication

Goal Apr- 0 1 Apr- 0 1 f- f- f- f- f- f- f- f- f- ~ 80 2L

70 60

._____...---

50

~+~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-. r-

Jan- Feb- Mar-

Apr-

May- Jun- Ju l-00 Aug- Sep- Oct- Nov- Dec- Jan- Feb- Mar-

Apr- r-

00

00 00 00 00 00 00 00 00 00 01 0 1 0 1 0 1

r-

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Dashboards and Transparency

Dashboards

Assess progress
Early warning
Avoid red/yellow/green –

may lead to wrong action because it is only a snap shot of the data, not the voice of the process or system

Use small run charts to

reflect changes in the system

Transparency

Emphasize that data is for

learning

Motivation to change

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Recap

PDSA Cycles

Changes derive from driver

diagram

Increases the belief that the

change will result in improvement

Test on a small scale
Build knowledge sequentially

with multiple PDSA cycles for each change idea

Include a wide range of

conditions in the sequence of tests

Measurement

Look at data over time
Keep measures simple,

actionable

Data are for learning not

judging

Be transparent
Use run chart rules to

understand improvement

Annotate run charts with

changes

Other tools help analyze data

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Questions?

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Continuing Education

Continuing education (CE) is provided jointly through Tufts

University School of Medicine Office of Continuing Education and the National Initiative for Children’s Healthcare Quality

CE credit available for this three-part webinar series includes:
2.25 AMA PRA Category 1 Credits™
2.25 Contact Hours for nurses
Certificate of participation
Attendance at all three webinars is required to receive full

credit

Sign in for Webinar 3: http://www.cvent.com/d/hcqvtd
Completion of a CE evaluation survey is required and a link

will be circulated to all those who signed in for the three surveys

Certificates will be available electronically 6 to 8 weeks after

completion of the CE evaluation survey

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Preview of the QI 201 Action Learning Series

Purpose
Enable states to undertake a QI project with technical

assistance and support

Next Steps
Your input will help us shape the QI 201 Track
Please complete the evaluation as you exit the webinar to

let us know what would be helpful

Topics
Format
Intensity
Your state’s level of interest

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Thank you for participating in today’s webinar!

Please complete the evaluation as you exit the webinar.

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Appendix

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Jointly Sponsored by Tufts University School of Medicine and National Initiative for Children’s Healthcare Quality

Accreditation Physicians

This activity has been planned and implemented in accordance with the Essential Areas and

policies of the Accreditation Council for Continuing Medical Education through the joint sponsorship of Tufts University School of Medicine (TUSM) and National Initiative for Children’s Healthcare Quality. TUSM is accredited by the ACCME to provide continuing medical education for physicians.

TUSM designates this enduring material for a maximum of 2.25 AMA PRA Category 1

Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Nurses

Tufts University School of Medicine Office of Continuing Education is accredited as a provider
f continuing nursing education by the American Nurses Credentialing Center’s COA.
This activity provides 2.25 Contact Hours for nurses.

Requirements for Successful Completion

To receive CE credit, participants must register, view the content and complete the evaluation.

Certificates will be available electronically 6-8 weeks after successful completion of the activity.

Disclosure of Relevant Financial Relationships with Commercial Interests

All faculty course directors, planning committee members and others in a position to control

the content of an educational activity are required to disclose to the audience any relevant financial relationships with commercial interests. Conflicts of interest resulting from a relevant financial relationship are resolved prior to the activity during the content review.

No relevant financial relationships are held by any of the planners, presenters or TUSM OCE staff.

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Building a Measurement Plan

For each measure:

How is it operationally defined? (e.g., numerator,

denominator)

What data will be collected?
On which population?
What is your sample size?
How will the data be collected?
Who will collect the data?
When will you collect the data? (Tip: begin immediately)

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Other Analytic Tools for Understanding Improvement

Traditional method is with run charts
Other (selected) analytic tools
Pareto diagrams – 80/20 rule
Scatter diagrams –shows relationship between two changes
Histograms – frequency distribution of a process

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Pareto Diagrams

Best used when you want to see where to start to study or

improve a process

Use with categorical (count) data
Frequently you have a large population in the area you want

to study or improve and need to break it down to something manageable

This is where the 80/20 rule applies:
80% of your problems come from 20% of the data/bars
If you focus on the areas where you can make the biggest

difference, you can solve most of your issues/problems faster

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Use of Pareto Diagrams in Real Life

Reasons for patient dissatisfaction
Unplanned readmission rates
Reasons for no care plan in chart
Types of medication errors
Missing documentation in the medical record

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The Pareto chart and analysis is used when dealing with chronic problems and helps identify which of the many chronic problems to attack first. The chronic problem with the highest number of events will show up on the Pareto chart with the tallest bar, which represents the most frequent occurring problem.

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15 13.125 11.25 9.375 7.5 5.625 3.75 1.875 1 2 3 4 5 100% 100% 100% 100% 93% 80% 60% 33% 3 PM 11 PM 4 PM

Number of Falls

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 7 PM 8 PM 5 PM 6 PM 9 PM 10 PM Time

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Use of Scatter Diagrams

Can be used to answer the question: Is variable A

possibly related to variable B?

An indication of the relationship between independent

and dependent variables

Does NOT prove causation
Does suggest further investigation

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Example of a Scatter Diagram

Calories Consumer/Weight Gain

0.2

0.2 0.4 0.6 0.8 1 1.2 500 1000 1500 2000 2500 3000 3500 4000 4500 Calories Consumed Weight Gained in Pound Weight Gained y=mx+b n=14 51

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Interpreting Scatter Plots

Narrow band of points extending from the lower left to the

upper right suggests a positive correlation

Means that as one factor increases so does the other
Possible to predict the approximate value of one factor

when you know the value of the other

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SLIDE 53

Source: KnowWare International, Inc.

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Medicaid/CHIP

Health Care Quality Measures

Example of a Histogram

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SLIDE 54

Commonly Used Quality Tools

Affinity Diagram – categorize

data

Interrelationship Digraph –

classify cause and effect, relationships; ascertain key drivers

Cause and Effect Diagram –

identify causes creating an effect

5 Why’s Flow Chart – expose

needless complexity, rework, delays

Swim Lane Chart
Value Stream Chart
Force Field Analysis – identify

forces acting for or against a change

Brainstorming – idea generation
Nominal Group Technique –

brainstorming technique

Multi-voting – reduce large list

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zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA Additional Resources

The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. G. Langley, K. Nolan, T. Nolan, C. Norman, and L. Provost. San Francisco: Jossey-Bass Publishers, 1996. Quality Improvement Through Planned Experimentation. 2nd

edition. R. Moen, T. Nolan, and L. Provost. New York, NY:

McGraw-Hill, 1998. “Understanding Variation,” T. W. Nolan and L. P. Provost. Quality Progress, Vol. 13, No. 5, May 1990. The Memory Jogger. M. Brassard and D. Ritter. Salem, NH: GOAL/QPC, 1985.

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2013 Core Set of Children’s Health Care Quality Measures

Prevention and Health Promotion Timeliness of Prenatal Care Frequency of Ongoing Prenatal Care Behavioral Health Risk Assessment (for Pregnant Women) – NEW IN 2013 Percentage of Live Births Weighing less than 2,500 Grams Cesarean Rate for Nulliparous Singleton Vertex Childhood Immunization Status Adolescent Immunization Status Human Papillomavirus (HPV) Vaccine for Female Adolescents – NEW IN 2013 Weight Assessment and Counseling for Nutrition and Physical Activity for Children/Adolescents: Body Mass Index Assessment Developmental Screening in the First Three Years of Life Chlamydia Screening in Women Well-Child Visits in First 15 Months of Life Well-Child Visits in the 3rd, 4th, 5th, and 6th Years of Life Adolescent Well-Care Visit Percentage of Eligibles Who Received Preventive Dental Services Availability Child and Adolescent Access to Primary Care Practitioners Management of Acute Conditions Appropriate Testing for Children with Pharyngitis Percentage of Eligibles who Received Dental Treatment Services Ambulatory Care: Emergency Department Visits Pediatric Central-line Associated Bloodstream Infections – Neonatal Intensive Care Unit and Pediatric Intensive Care Unit Management of Chronic Conditions Annual Percentage of Asthma Patients with One or More Asthma-related Emergency Room Visits Medication Management for People with Asthma – NEW IN 2013 Follow-Up Care for Children Prescribed Attention Deficit-Hyperactivity Disorder (ADHD) Medication Annual Pediatric Hemoglobin A1C Testing Follow-up After Hospitalization for Mental Illness Family Experiences of Care Consumer Assessment of Healthcare Providers and Systems 5.0H (child version including children with chronic conditions supplemental items)

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Initial Core Set of Health Care Quality Measures for Adults Enrolled in Medicaid

Prevention and Health Promotion Flu Shots for Adults Ages 50-64 Adult BMI Assessment Breast Cancer Screening Cervical Cancer Screening Medical Assistance With Smoking and Tobacco Use Cessation Screening for Clinical Depression and Follow-Up Plan Plan All-Cause Readmission Diabetes, Short-term Complications Admission Rate Chronic Obstructive Pulmonary Disease (COPD) Admission Rate Congestive Heart Failure Admission Rate Adult Asthma Admission Rate Chlamydia Screening in Women age 21-24 Availability Initiation and Engagement of Alcohol and Other Drug Dependence Treatment Prenatal and Postpartum Care: Postpartum Care Rate Management of Acute Conditions Follow-Up After Hospitalization for Mental Illness Elective Delivery Antenatal Steroids Management of Chronic Conditions Annual HIV/AIDS Medical Visit Controlling High Blood Pressure Comprehensive Diabetes Care: LDL-C Screening Comprehensive Diabetes Care: Hemoglobin A1c Testing Antidepressant Medication Management Adherence to Antipsychotics for Individuals with Schizophrenia Annual Monitoring for Patients on Persistent Medications Family Experiences of Care CAHPS Health Plan Survey – Adult Questionnaire with CAHPS Health Plan Survey v. 5.0H Care Coordination Care Transition – Transition Record Transmitted to Health care Professional

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