Quality Improvement Methodology – Next Steps
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Quality Improvement Methodology – Next Steps. Purpose of this Session. Consider the components of a learning system in your own improvement activity : 4. Sequential testing of new theories 6. Planning for spread at scale

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Quality improvement methodology next steps

Quality Improvement Methodology – Next Steps


Purpose of this session

Purpose of this Session

Consider the components of a learning system in your own improvement activity :

4. Sequential testing of new theories

6. Planning for spread at scale

What stage are you at in relation to these aspects of the improvement journey?

What do you need to do next to ensure that your tests are scaled up and spread correctly?


Quality improvement methodology next steps

Aim

Measures

Changes

Testing &

Implementation

The Improvement Guide, API


Cycles of tests build confidence

Cycles of Tests Build Confidence

Changes that will result in improvement

Learning from data

Proposals, theories, hunches, intuition


Quality improvement methodology next steps

Startsmall

  • 1 child

  • 1 day

  • 1 family

  • 1 setting

  • Move to 3,5,7…. as confidence grows


Quality improvement methodology next steps

Years

Quarters

Months

Weeks

Days

Hours

Minutes

You can only learn as quickly as you test!

Drop down next “two levels” to plan test cycle!


Components of a learning system

Components of a Learning System

  • System level measures

  • Explicit theory or rationale for system changes

  • Segmentation of the population

  • Learn by testing changes sequentially

  • Use informative cases: “Act for the individual learn for the population”

  • Learning during scale-up and spread with a production plan to go to scale

  • Periodic review

  • People to manage and oversee the learning system

    From Tom Nolan PhD, IHI


Sequential testing scale up

Sequential Testing & Scale Up

Aim

Achieve improved communication process for HV and SW handovers using standardised format

Sustain in practice and spread to other areas

Data/learning/adapting

Implement

Cycle 6: Test all handovers-1 week

Cycle 5: other team HVs/SWs- 1 day

Cycle 4:Test with all handovers-1 HV/1week

Cycle 3: Test with 5 more families/ same HV (Mon/Tu)

Hunch/Theory

A structured handover will ensure accurate information sharing between prof teams

Cycle 2: Test with 3 family handovers/ same HV (Wed)

Cycle 1: Test developed handover form 1 HV/1 SW 1 family (Mon)


Learning through sequential testing

Learning Through Sequential Testing

Where are you currently?

Can you describe an example of the following?

Multiple tests with different people/under different conditions?

Learning/data captured to describe your testing journey?


Testing v implementation

Testing v Implementation

Testing – Trying and adapting existing knowledge on small scale. Learning what works in your system. Multiple tests in a variety of conditions…………………

Implementation– Making the change a part of the day-to-day operation of the system. Permanent change

Would the change persist even if its champion were to leave the organisation?

Avoid implementation until confident that processes are robust


How manytests

How ManyTests?


Components of a learning system1

Components of a Learning System

  • System level measures

  • Explicit theory or rationale for system changes

  • Segmentation of the population

  • Learn by testing changes sequentially

  • Use informative cases: “Act for the individual learn for the population”

  • Learning during scale-up and spread with a production plan to go to scale

  • Periodic review

  • People to manage and oversee the learning system

    From Tom Nolan PhD, IHI


A framework for spread

A Framework for Spread

  • Leadership

  • Topic is a key strategic initiative

  • Goals and incentives aligned

  • Executive sponsor assigned

  • Day-to-day managers identified

Measurement and Feedback

  • Social System

  • Key messages

  • Communities

  • Technical support

  • Transition issues

  • Set-up

  • Target population

  • Adopter audiences

  • Successful sites

  • Key partners

  • Initial spread plan

  • Better Ideas

  • Develop the case

  • Describe the ideas

Communication (awareness & technical)

Knowledge Management

Institute for Healthcare Improvement


Things to consider

Things to Consider

  • Checklists For Spread

  • Leadership, Better Ideas & Set Up

  • General Communication & knowledge

  • transfer

  • Developing Measurement, Feedback

  • and Knowledge Management Systems


Are you ready for scale up spread

Are You Ready for Scale up & Spread?

In the context of your current improvement activity:

Have you been testing a theory so that it could be considered ready for implementation in the area you are working? and/or…

Do you have a strategy for moving to scale up and spread to other sites/teams?


The seven spreadly sins

The Seven Spreadly Sins

Step 1Start with large pilots

Step 2Find one person willing to do it all

Step 3 Expect vigilance and hard work to solve the problem

Step 4 If a pilot works then spread the pilot unchanged

Step 5 Require the person and team who drove the pilot to be responsible

for system-wide spread

Step 6 Look at process and outcome measures on a quarterly basis

Step 7 Early on expect marked improvement in outcomes without attention

to process reliability

Institute for Healthcare Improvement


Sustaining improvement

Sustaining Improvement

Having the correct measures to provide assurance that new processes are reliable

Measuring compliance or satisfaction through regular and random sampling of the population

Understanding the variation that exists in your data


What measures

What measures?

Outcome measures – directly relates to the overall aim what is the result? how is the system performing?

Process measures – are the processes that contribute to the aim performing as planned?

Balancingmeasures – assessing from different dimensions unanticipated consequences, other factors influencing the outcome


If we don t understand the variation that lives in our data we will be tempted to

N

T

V

R

If we don’t understand the variation that lives in our data, we will be tempted to…

O

I

A

A

I

  • Deny the data as it doesn’t fit with our view of reality

  • See trends where there are none

  • Try to explain natural variation as special events

  • Blame and give credit to people for things over which they have no control

  • Distort the process that produced the data

  • Kill the messenger!


Common cause variation

Common Cause Variation


Quality improvement methodology next steps

Measurement of Improvement

Define measures that will measure the impact of the

Improvement work over time

They will guide your progress through and beyond testing to implementation and monitoring for continuous improvement.

Different ways of measuring e.g.,

  • Percent compliance with process

  • A count of correct attempts/number of attendances

  • Verbal feedback /surveys


Quality improvement methodology next steps

Why a run chart and not just a graph or table?

Run Chart

Prompt sticker used on all referrals

Testing screening tool with 3 Families

Prompt sticker tested in case referral

Median = 84%

Testing screening tool with 5 families

Testing screening tool with 1 family

Testing with all Families

Month

HC Data Guide


Quality improvement methodology next steps

Non-Random Rules For Run Charts

A Shift:

6 or more

A Trend:

5 or more

Too many or too few runs

An astronomical data point

Source: The Data Guide by L. Provost and S. Murray, Austin, Texas, February, 2007:


Quality improvement methodology next steps

What is this data telling you?

Month

Data 11 1 3 4 5 9 10 4 11 7 10 10 7 6 22 4 2 2 1 3 4


Quality improvement methodology next steps

What is this data telling you?

Astronomical

Point

Shift

Median = 5

Trend

Shift

Month

Median 1 1 2 2 3 3 4 4 4 4 5 6 7 7 9 10 10 10 11 11 22


Measurement principles

Measurement Principles

  • Develop aims before measuring

  • Design measures around aims ‘How Good By When’

  • Be clear on your operational definitions

  • Establish a reliable baseline

  • Track progress over time using annotated run charts

  • Teams need measures to give them feedback that the changes they are making are resulting in improvement

  • Need to understand common cause and special cause variation to ensure we don’t over/under react to situations


Quality improvement methodology next steps

  • Appreciation of a System

  • Complex system of interaction between people, procedures and equipment

  • Success depends on integration, not performance of individual parts

  • Theory of Knowledge

  • Change is prediction of improvement

  • based on knowledge of the system

  • Learning from theory, experience

  • Operational definitions are the basis

  • for improvement with PDSA cycles for

  • learning

  • Psychology

  • Interaction of people with systems

  • Motivation & will of individuals & teams

  • Situation awareness/decision making

  • Managing stress and fatigue

  • Helps planning for change management

Improvement

  • Understanding Variation

  • Variation is to be expected – everything we measure varies

  • We make decisions based on interpretation

  • Data over time – data story of what has been happening

Aims & Values


What s the scope of change

What’s the Scope of Change?

System Targeted for Implementation(Defined by Aim)

Single-unit prototype: segments

As you move from pilot testing to implementation to spread, your population of interest will need to be adjusted.

Spread to Total System(Additional units, sites, organisations)


Thank you

Thank You


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