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Coaching change through data driven team work

Jay Ford

University of Wisconsin-Madison

UTI Toolkit – Module 5Narration by:

Jay Ford, PhD, FACHE, LFHIMSSAssistant Professor

School of Pharmacy, University of Wisconsin-Madison

Content developed in partnership with the WisconsinHealthcare-Associated Infections in Long-Term Care Coalition

Funding for this project was provided by the Wisconsin Partnership Program at the UW School of Medicine and Public Health

Objectives

• Learn why it is important to track data in organizational change.

• Identify seven rules of the road related to using data to inform organizational change

• Discuss elements of the seven rules of the road.

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POWERFUL DATA, POWERFUL CHANGE: Why is it important to track data?

• If you want to change something, measure it.

• Answers the question: “How will we know a change is an improvement?”

• Measuring change enhances process improvement by• Identifying which changes worked.

• Learning which changes resulted in improvement and

• Understanding which changes resulted in the most significant improvement

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Using Data toward greater Connectedness & Understanding

Connectedness

UnderstandingDATA

INFO.Understanding Relationships

KnowledgeUnderstanding Patterns

WisdomUnderstanding Principles

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DIKW Pyramid

Efforts to improve antibiotic prescribing resulted in reduced urine cultures and resulting antibiotic orders which resulted in improved patient care.

Based on review, 20% of urine cultures were unnecessary.

80 urine cultures ordered.

100 residents identified with suspected UTI symptoms.

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

No: ↓ Fluoroquinolone starts/1000 resident days by 40%

Yes: ↓ Fluoroquinolone starts/1000 resident days from 3.60 to 2.16

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Rule 3: Establishing an aim

• Be flexible• Information suggests changing the aim, change it

• Aim is too ambitious, set a realistic aim that still challenges the agency to improve

• Aim is easily achieved, set a more ambitious aim that stretches the agency’s capacity to improve

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

No: ↓ Fluoroquinolone starts/1000 resident days by 40%

Yes: ↓ Fluoroquinolone starts/1000 resident days from 3.60 to 2.16 Establish a process

to consistently collect and record data using agreed upon definition

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

No: ↓ Fluoroquinolone starts/1000 resident days by 40%

Yes: ↓ Fluoroquinolone starts/1000 resident days from 3.60 to 2.16

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

Establish a process to consistently collect and record data using agreed upon definition

Stay out of the Quicksand• Don’t collect too much data• Don’t focus on too many

measures• Don’t get trapped in analysis

paralysis

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7 Simple Rules of the Road

Define Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

No: ↓ Fluoroquinolone starts/1000 resident days by 40%

Yes: ↓ Fluoroquinolone starts/1000 resident days from 3.60 to 2.16

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

Establish a process to consistently collect and record data using agreed upon definition

Stay out of the Quicksand• Don’t collect too much data• Don’t focus on too many

measures• Don’t get trapped in analysis

paralysis

Time from First Contact to First Treatment

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Changes Implemented ChangesSustained

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Rule 6: Report and Chart Progress• A Simple Axiom: One chart, one message

• Charts can be used to: • Highlight the baseline (pre-change) data

• Identify when a change was introduced

• Visually represent the impact of individual changes over time, and

• Inform your agency about sustaining change over time.

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Guidance for Providing Feedback

1. Ensure staff has sufficient background and/or familiarity to adequately interpret data.

2. Display numbers so that others can understand them.

3. Interpret numbers to make the correct decisions based on them.

4. Relate the numbers to people getting better.

5. Link the numbers to success stories to motivate others towards improvement.

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0

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

Qtr4 Qtr1 Qtr2 Qtr3 Qtr4 Qtr1 Qtr2 Qtr3 Qtr4 Qtr1 Qtr2 Qtr3 Qtr4

2014 2015 2016 2017

Antibiotic Ordered vs. Urinalysis Ordered

ABX for UTI Ordered Culture done 48 Hours of ABX (Urine)

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Use of trend lines can show how the data is changing

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

Qtr4 Qtr1 Qtr2 Qtr3 Qtr4 Qtr1 Qtr2 Qtr3 Qtr4 Qtr1 Qtr2 Qtr3 Qtr4

2014 2015 2016 2017

Antibiotic Ordered vs. Culture Done in 48 Hours Ordered

ABX for UTI Ordered Culture done 48 Hours of ABX (Urine) Linear (ABX for UTI Ordered) Linear (Culture done 48 Hours of ABX (Urine))

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Days to Treatment and No-Show Rates

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Timeliness No-Shows

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Providing Feedback: Questions to Consider

• How will the measures be reported?• Only to leadership• Quality Assurance/Quality Improvement (QAPI) meeting

• How often will the measures be reported and the charts updated?

• What else – besides the measures on these simple line charts –should be reported?• Information about process changes• Changes in resident acuity• Impact of staffing on outcomes

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7 Simple Rules of the RoadDefine

Measures

Collect Baseline

Data

Define a clear aim

Consistent data

collection

Avoid common pitfalls

Report and chart progress

Ask questions

No: ↓ Fluoroquinolone starts/1000 resident days by 40%

Yes: ↓ Fluoroquinolone starts/1000 resident days from 3.60 to 2.16

• Do not accept results at face value

• Do the results look right?

• What is the data telling us?

• Unsuccessful changes afford the opportunity to ask why?

Antibiotic start time: Time when ABX ordered to 1st

dose administered.

1. Use agree upon definition

2. Defines clear starting point

3. Essential to successful change

Establish a process to consistently collect and record data using agreed upon definition

Stay out of the Quicksand• Don’t collect too much data• Don’t focus on too many

measures• Don’t get trapped in analysis

paralysisTime from First Contact to First Treatment

0.00

2.00

4.00

6.00

8.00

10.00

12.00

Jun-

03

Jul-

03

Aug-

03

Sep-

03

Oct-

03

Nov-

03

Dec-

03

Jan-

04

Feb-

04

Mar-

04

Apr-

04

May-

04

Jun-

04

Jul-

04

Aug-

04

Sep-

04

Oct-

04

Nov-

04

Changes Implemented ChangesSustained

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POWERFUL DATA, POWERFUL CHANGE: Why is it important to track data?

• If you want to change something, measure it.

• Answers the question: “How will we know a change is an improvement?”

• Measuring change enhances process improvement by• Identifying which changes worked.

• Learning which changes resulted in improvement and

• Understanding which changes resulted in the most significant improvement

What did this module accomplish?

• Learned the importance of data in organizational change.

• Identified seven simple rules of the road for using data in organizational change• Discussed the importance of defining measures and collecting data consistently

based on the measure definition.

• Emphasized the importance of a clear aim that allows the organization to experience a real impact of change efforts

• Highlighted the importance of simple and focused feedback

• Identified the power of questions in exploring the impact of change.

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