Call 5PDSA Cycles and SPC Software WebEx

Improvement Advisor Professional Development Program

Wave 42

Please have your SPC software open and ready to use,along with the Excel file containing our data.

If you need to download this file again it is on the Extranet under Resources...Action Period Call Assignments....SPC assignment.

AgendaTime Topic Leader

3:00 BST Welcome and Check-In (including project scores) Rebecca

3:10 Assignments:• Paired Leadership Report Review• Senior Leader Project Scoring• Project Presentations at WS42.2• 2-3 Volunteers Needed for Next WebEx Sharing

PDSA Cycles/Project Presentations

Jane

3:20 PDSA Cycle report Rajesh/Richard

3:30 Run Charts in Review Jane

3:55 P Charts on Parade Richard

4:20 Optional As Time Allows: Review of Extra Charts Jane

4:30-5:00 Close and office hours

Please Check In…

IA IA IA

Akhnuwkh Jones Harald Stordahl Rachael Leaton

Anna Smith Helen O'Kelly Rachel Fletcher

Barbara Grey Helle Bak Rajesh Pai

Blake Pritchard Iyoni Ranasinghe Sandra McConnell

Breid O'Brien Jimmy Noak Sian Martin

Cecilie Lund Murray Margaret Rennocks Stephen O'Connor

Emma Binley Mukesh Thakur Suzanne Morton

Geetika Singh Polly Ragoobar Suzie Bailey

Hanne Miang Tammy Naidu

Where are you?

IA Programme Faculty and Staff Team: Wave 425

Lloyd ProvostFaculty

Jane TaylorFaculty

Robert LloydFaculty

Brandon BennettFaculty

Sandy MurrayFaculty

Jerry LangleyLead Faculty

Richard ScovilleFaculty

Rebecca SteinfieldProgramme Director/

Faculty

Mark BradshawEvent Coordinator

James Innes

IA Grads

Amar Shah

Jo Inge Myhre

Purpose

Deepen our skills in running PDSA cycles

Learn from one another’s run and P charts

related to:

– Software skills

– Understanding what the charts are saying

– Good graphical display

August Assignment: Paired Reviews

Paired Leadership Report Assignment:Purpose: Strengthen one another’s Leadership Reports

How did it go? What

was your take away?

Monthly Reporting

• September Report due today

• Include your project sponsor and advocate

progress assessment scorePurpose: Raise awareness of project, remove barriers, gain leadership guidance and support

Step 1: Share leadership report, assessment scale and any other info with your Sponsor and

Advocate so they can assess project.

Step 2: Note their assessment score on your next Leadership Report (if you are using the

PowerPoint template, there is a space at the top of the first page).

October Report: Upload your WS2 presentation

Improvement Advisor Project Progress Assessment ScaleApply these criteria to your IA improvement Project. Select the definition that best describes the progress of your project.

Please note that assessments are progressive. All elements of a 3 must be satisfied before rating your project with an

assessment of a 3.5 or 4. Evidence for your assessment must be documented in your monthly report.

Project Progress Score Operational Definition of Project Progress Score

0.5 - Intent to Participate Project has been identified, but the charter has not been completed nor team formed.

1.0 -Charter and team established A charter has been completed and reviewed. Individuals or teams have been assigned, but no work

has been accomplished.

1.5 - Planning for the project has

begunOrganization of project structure has begun (such as: what resources or other support will likely be

needed, where will focus first, tools/materials needed gathered, meeting schedule developed).

2.0 - Activity, but no changes Initial cycles for team learning have begun (project planning, measurement, data collection, obtaining

baseline data, study of processes, surveys, etc.). 2.5 - Changes tested, but no

improvementInitial cycles for testing changes have begun. Most project goals have a measure established to track

progress. Measures are graphically displayed with targets included.

3.0 - Modest improvement Successful tests of changes have been completed for some components of the change package

related to the team’s charter. Some small scale implementation has been done. Anecdotal evidence

of improvement exists. Expected results are 20% complete. See note 1.

3.5 - Improvement Testing and implementation continues and additional improvement in project measures towards

goals is seen.4.0 - Significant improvement Expected results achieved for major subsystems. Implementation (training, communication, etc.) has

begun for the project. Project goals are 50% or more complete. See note 2.

4.5 - Sustainable improvement Data on key measures begin to indicate sustainability of impact of changes implemented in system.

5.0 - Outstanding sustainable results Implementation cycles have been completed and all project goals and expected results have been

accomplished. Organizational changes have been made to accommodate improvements and to

make the project changes permanent.

Note 1: This may mean either that a) 20% of project numeric goals have been met or b) each

measure is showing 20% improvement towards goal.

Note 2: This may mean either that a) 50% of your numeric goals have been met or b) each measure

is showing 50% improvement towards target

Testing! Measurement!

Workshop 2 Project Presentation Assignment

Workshop 2 is October 10-13; Bob and Jane are faculty.IA Project Presentation Guidelines: 20 min. for each IA for presentation and discussion

Purpose: to hone our skills related to designing and running PDSA cycles Start your presentation by sharing aim of your team (usually from DD) and your current project progress score (on 0.5 to 5 scale) and predicting what your PPS will be by WS 3. (Sept 2015) 30 seconds or less

Share your Family of Measures (One slide: List of Outcome, Process, and Balancing Measures, don’t need to show data here) (2 Min)

Show us your PDSA strategy (e.g. ramp of PDSA cycles planned/and or completed) One slide only (2 Min)

Present one or more completed PDSAs on your project using PDSA form (need 12 paper copies of completed PDSA form you are sharing) (10-15 Min)

– The PDSAs can focus on learning, developing, testing or implementing a change

– Testing a change preferred!

– Tell us which change concepts you used in your test(s) of change (IG page 359)

Faculty and other IAs will use a PDSA evaluation form to provide feedback to the presenter. PDSA Feedback Form is on the Extranet.

Project Presentation Example: 3 Slides and a PDSA

Form

1: Driver Diagram

(plus current and

predicted progress

scores)

2: Project Measures

(outcome, process,

balancing)

3: PDSA Strategy (a

ramp, for example)

4: Completed PDSA

Form (at least 1)

IHI IA Development Program - PDSA CYCLE FEEDBACK

PURPOSE: To provide helpful feedback on Workshop 2 project presentations focusing on use of PDSA cycles.

Presenter: ______________________ Reviewer: _______________________ Date ____________

Project (short aim): ________________________________________________________________________

Project (0-5 scale) Assessment: Now: ______ at Workshop 3______

Family of Measures for the project

Was the total number of measures appropriate?

Suggestions on balance between outcome, process, and balancing measures

Do these measures make the project aim tangible?

Linking Series of PDSA Cycles

What is the strategy for this series of linked, multiple cycles (replication, scale-up, wide-scale testing, multiple

changes, etc.)?

Comment on the time frame for the series of PDSA cycles.

What other suggestions do you have on the series of PDSA Cycles planned for the project?

See specific PDSA Cycle on back

Specific PDSA presented (please add suggestions in the appropriate step of PDSA)

PLAN: Was the objective for this PDSA cycle clear to you? Is this cycle designed to build knowledge, develop a change, test a

change, or implement a change?

Were the questions they were trying to answer stated clearly? How could the predictions be improved?

What change concepts were used in the plan for the PDSA?

What would you suggest they do to strengthen their plan for this cycle?

Will the planned data collection (qualitative and quantitative) answer the questions for the cycle?

Suggestions about the scale/scope of this PDSA?

DO: Did they attempt to carry out their plan?

Did they document any problems or unexpected events?

Were they able to collect the data they planned?

STUDY: Did they complete the analysis of the data (including qualitative feedback and observations)?

Did they compare the results to their prediction and summarize what they learned?

Did they update their theories for this project?

ACT: Did they say what will happen in the next PDSA cycle (develop change further, test, implement?)

What suggestions do you have for scale, scope, sequencing of their next PDSA cycle(s)?

Subject Matter knowledge: Do you have an ideas they should test in this project?

Next WebEx: October 6, 2016

Looking for 2 volunteers to present Project

Presentation PDSA cycle(s) early.

– These volunteers will not present at Workshop 2.

– Will have 20 minutes

All IAs should download the PDSA Feedback

Form prior to the call so we can use it as a guide

to asking good questions and providing

feedback (Resource Tab “Forms”).

Rajesh Pai, MD

Deputy Medical Superindendent

Amrita Institute of Medical Sciences

Project: proper medication reconciliation to reduce readmission (and hence cost of care) caused by drug-related problems

SPC Exercise Review

While we are talking about this if question occurs to you …

– Ask it please…

– Or- type it in chat box…

Pe

rce

nt

Percent Unplanned Returns to OR

27

984

20

982

25

996

23

998

31

1070

17

1031

21

886

28

964

24

1128

22

960

19

1193

24

998

30

1070

22

895

15

852

18

963

12

956

22

1001

8

956

2

995

9

987

6

943

20

965

6

980

2

923

6

1106

# Pts Return

# Surgeries

Run chart

Median line = 2.05

Goal = 0.5

Chg 1

Chg 2 & 3

Chg 4 & 5

Chg 7 & 8

Chg 9

Chg 10 & 11

Chg 12 & 13

Chg 14

Implement

F 04 M A M J J A S O N D J 05 F M A M J J A S O N D J 06 F M A M

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Note from Rebecca:

I was only able to put the graphs

into the slide deck that were

posted on-time; if anyone has a

question about their particular

homework, you can ask in the

“office hours” (or any other time)

Run Charts in Review!!

Run Charts

Graphical display of data over time

First means of analysis is visual

– What is our degree of belief that we see evidence of

improvement

Can be analyzed using probability-based rules

to detect non-random patterns called “signals”

– Signals can be evidence of Improvement or

degradation

– DG Chapter 3

0

0.5

1

1.5

2

2.5

3

3.5

% Unplanned Returns

Median

Akhnuwkh

1. Run chart

0

0.5

1

1.5

2

2.5

3

3.5

1/1

/12

2/1

/12

3/1

/12

4/1

/12

5/1

/12

6/1

/12

7/1

/12

8/1

/12

9/1

/12

10/1

/12

11/1

/12

12/1

/12

1/1

/13

2/1

/13

3/1

/13

4/1

/13

5/1

/13

6/1

/13

7/1

/13

8/1

/13

9/1

/13

10/1

/13

11/1

/13

12/1

/13

1/1

/14

2/1

/14

3/1

/14

4/1

/14

Run ChartMedian

Measure

Blake

1/1/12 2/1/12 3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14 2/1/14

Subgroup 2.74 2.04 2.51 2.30 2.90 1.65 2.37 2.90 2.13 2.29 1.59 2.40 2.80 2.46 1.76 1.87 1.26 2.20 0.84 0.20 0.91 0.64 2.07 0.61 0.22 0.54

Median 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1

0

0.5

1

1.5

2

2.5

3

3.5

Percentage

Percentage unplanned returns to OR

Median

Stephen

August homework – SPC assignment

1/1/12 2/1/12 3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14 2/1/14

Subgroup 27 20 25 23 31 17 21 28 24 22 19 24 30 22 15 18 12 22 8 2 9 6 20 6 2 6

Median 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0

27

20

25

23

31

17

21

28

24

22

19

24

30

22

15

18

12

22

8

2

9

6

20

6

2

6

20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0

Change implemented

20.0 20.0 20.0

0

5

10

15

20

25

30

35

Num

ber

of patie

nts

Time

Run Chart - Unplanned return to ORMedian

Measure

Suzanne

Chg 1

Chg 2,3Chg 7,8

Chg 4,5,6

Chg 9

Chg 10,11

Chg 12,13Chg 14

Change implemented

0

0.5

1

1.5

2

2.5

3

3.5

Jan

-12

Feb

-12

Mar

-12

Ap

r-1

2

May

-12

Jun

-12

Jul-

12

Au

g-1

2

Sep

-12

Oct

-12

No

v-1

2

De

c-1

2

Jan

-13

Feb

-13

Mar

-13

Ap

r-1

3

May

-13

Jun

-13

Jul-

13

Au

g-1

3

Sep

-13

Oct

-13

No

v-1

3

De

c-1

3

Jan

-14

Feb

-14

Pe

rce

nt

Un

pla

nn

ed

Re

turn

Percent unplanned return to OR - Run chart

median

Hanne

-0.07

0.43

0.93

1.43

1.93

2.43

2.93

3.43

Jan

-12

Feb

-12

Mar

-12

Ap

r-1

2

May

-12

Jun

-12

Jul-

12

Au

g-1

2

Sep

-12

Oct

-12

No

v-1

2

De

c-1

2

Jan

-13

Feb

-13

Mar

-13

Ap

r-1

3

May

-13

Jun

-13

Jul-

13

Au

g-1

3

Sep

-13

Oct

-13

No

v-1

3

De

c-1

3

Jan

-14

Feb

-14

Un

pla

nn

ed

Re

turn

s (%

)

Months

Percent Unplanned Returns

Percent Unplanned Returns

Median

RUN CHART

Months

Percent Unplanned

Returns

Jan-12 2.74

Feb-12 2.04

Mar-12 2.51

Apr-12 2.30

May-12 2.90

Jun-12 1.65

Jul-12 2.37

Aug-12 2.90

Sep-12 2.13

Oct-12 2.29

Nov-12 1.59

Dec-12 2.40

Jan-13 2.80

Feb-13 2.46

Mar-13 1.76

Apr-13 1.87

May-13 1.26

Jun-13 2.20

Jul-13 0.84

Aug-13 0.20

Sep-13 0.91

Oct-13 0.64

Nov-13 2.07

Dec-13 0.61

Jan-14 0.22

Feb-14 0.54

Rachel L and Iyoni

Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14

Subgroup 2.74 2.04 2.51 2.30 2.90 1.65 2.37 2.90 2.13 2.29 1.59 2.40 2.80 2.46 1.76 1.87 1.26 2.20 0.84 0.20 0.91 0.64 2.07 0.61 0.22 0.54

Median 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1

Chg 1

Chg 2, 3

Chg 4, 5, 6

Chg 7, 8

Chg 9

Chg 10, 11

Chg 12, 13

Chg 14

Implementation Start

0

0.5

1

1.5

2

2.5

3

3.5

Month and year

Percentage Unplanned Return to OR (Run Chart)

Median

Perc

enta

ge o

f patients

unpla

nned r

etu

rn

to O

R

Geetika

Run Chart with Changes and Data Table

Sandra

2.1

0

0.5

1

1.5

2

2.5

3

3.5

Ja

nua

ry 2

01

2

Feb

ruary

20

12

Ma

rch

201

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er

20

12

Octo

be

r 2

01

2

No

ve

mb

er

20

12

De

ce

mb

er

20

12

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er

20

13

Octo

be

r 2

01

3

No

ve

mb

er

20

13

De

ce

mb

er

20

13

Ja

nua

ry 2

01

4

Feb

ruary

20

14

Run Chart - Percent Unplanned Returns (monthly)Percent unplanned returns

Change 9

Change 2 & 3

Change 4, 5 & 6

Change 7 & 8

Change 10 & 11

Change 12 & 13

Change 14

Implementation starts

Change 1

Emma

2.1

0

0.5

1

1.5

2

2.5

3

3.5

Jan

-12

Fe

b-1

2

Ma

r-12

Ap

r-12

Ma

y-1

2

Jun

-12

Jul-1

2

Au

g-1

2

Se

p-1

2

Oct-

12

Nov-1

2

Dec-1

2

Jan

-13

Fe

b-1

3

Ma

r-13

Ap

r-13

Ma

y-1

3

Jun

-13

Jul-1

3

Au

g-1

3

Se

p-1

3

Oct-

13

Nov-1

3

Dec-1

3

Jan

-14

Fe

b-1

4

Ma

r-14

Ap

r-14

Run Chart - Percent unplanned returns to OR

Median

Unplanned returnsas a percentage of number of surgeries

Chg4,5,6

Unplanned returnsas a percentage of number of surgeries

Chg7,8

Chg 9

Chg10,11

Chg12.13

Unplanned returnsas a percentage of number of surgeries

Chg 14Chg2,3

Implementation start

Chg 1

Cecilie

A. Run chart using the column labelled "Percent" as your measure (your data). See if you can place a median on the run chart.

Rachel Fletcher

Some things to explore….

Labeling median

Add empty rows at start to be able to add new

data to the chart.

P Charts on Parade

Shewhart P-charts

Uses numerator and denominator and lets computer

figure our percent

Center line is weighted average of the percents

Upper and lower limits very important

Enables us to detect special cause in data

– More on that in WS 2!

Are a number of different kinds of Shewhart charts

– We just build the P chart for this exercise

– Will use wide range of Shewhart charts in WS 2

CL 0.0178

UCL 0.0309

LCL 0.0047

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

# P

ts U

np

lan

ned

Retu

rn t

o O

R -

# S

urg

eri

es

Months

# Pts Unplanned Return to OR / # Surgeries p Chart

Akhnuwkh

2. P chart

UCL

LCL

0%

1%

1%

2%

2%

3%

3%

4%

1/1

/12

2/1

/12

3/1

/12

4/1

/12

5/1

/12

6/1

/12

7/1

/12

8/1

/12

9/1

/12

10/1

/12

11/1

/12

12/1

/12

1/1

/13

2/1

/13

3/1

/13

4/1

/13

5/1

/13

6/1

/13

7/1

/13

8/1

/13

9/1

/13

10/1

/13

11/1

/13

12/1

/13

1/1

/14

2/1

/14

P ChartPercent

Blake

1/1/12 2/1/12 3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14 2/1/14

Subgroup 2.74% 2.04% 2.51% 2.30% 2.90% 1.65% 2.37% 2.90% 2.13% 2.29% 1.59% 2.40% 2.80% 2.46% 1.76% 1.87% 1.26% 2.20% 0.84% 0.20% 0.91% 0.64% 2.07% 0.61% 0.22% 0.54%

Center 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78%

UCL 3.04% 3.05% 3.04% 3.04% 2.99% 3.02% 3.11% 3.06% 2.96% 3.06% 2.93% 3.04% 2.99% 3.11% 3.14% 3.06% 3.06% 3.03% 3.06% 3.04% 3.04% 3.07% 3.06% 3.05% 3.09% 2.97%

LCL 0.52% 0.51% 0.52% 0.52% 0.57% 0.54% 0.45% 0.50% 0.60% 0.50% 0.63% 0.52% 0.57% 0.45% 0.42% 0.50% 0.50% 0.53% 0.50% 0.52% 0.52% 0.49% 0.50% 0.51% 0.47% 0.59%

UCL

LCL

0%

1%

1%

2%

2%

3%

3%

4%

Unplanned Returns to OR - P Chart

Percent

chg1

chg2,3

chg4,5,6

Stephen

1/1/12 2/1/12 3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14 2/1/14

Subgroup 2.74% 2.04% 2.51% 2.30% 2.90% 1.65% 2.37% 2.90% 2.13% 2.29% 1.59% 2.40% 2.80% 2.46% 1.76% 1.87% 1.26% 2.20% 0.84% 0.20% 0.91% 0.64% 2.07% 0.61% 0.22% 0.54%

Center 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78%

UCL 3.04% 3.05% 3.04% 3.04% 2.99% 3.02% 3.11% 3.06% 2.96% 3.06% 2.93% 3.04% 2.99% 3.11% 3.14% 3.06% 3.06% 3.03% 3.06% 3.04% 3.04% 3.07% 3.06% 3.05% 3.09% 2.97%

LCL 0.52% 0.51% 0.52% 0.52% 0.57% 0.54% 0.45% 0.50% 0.60% 0.50% 0.63% 0.52% 0.57% 0.45% 0.42% 0.50% 0.50% 0.53% 0.50% 0.52% 0.52% 0.49% 0.50% 0.51% 0.47% 0.59%

2.51%

1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78%

Change implemented

1.78% 1.78% 1.78%

UCL

LCL

0%

1%

1%

2%

2%

3%

3%

4%P

erc

eta

ge o

f R

etu

rned p

atie

nts

Time

Unplanned return to OR - P Chart

Percent

Suzanne

Chg 1

Chg 2,3 Chg 7,8

Chg 4,5,6

Chg 9

Chg 10,11

Chg 12,13

Chg 14

Change implemented

0

5

10

15

20

25

30

35

Nu

mb

er

og

pat

ien

tsP Chart - Unplanned return to OR

Average

Hanne

Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14

Subgroup 2.74% 2.04% 2.51% 2.30% 2.90% 1.65% 2.37% 2.90% 2.13% 2.29% 1.59% 2.40% 2.80% 2.46% 1.76% 1.87% 1.26% 2.20% 0.84% 0.20% 0.91% 0.64% 2.07% 0.61% 0.22% 0.54% 0.00% 0.00%

Center 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78% 1.78%

UCL 3.04% 3.05% 3.04% 3.04% 2.99% 3.02% 3.11% 3.06% 2.96% 3.06% 2.93% 3.04% 2.99% 3.11% 3.14% 3.06% 3.06% 3.03% 3.06% 3.04% 3.04% 3.07% 3.06% 3.05% 3.09% 2.97%

LCL 0.52% 0.51% 0.52% 0.52% 0.57% 0.54% 0.45% 0.50% 0.60% 0.50% 0.63% 0.52% 0.57% 0.45% 0.42% 0.50% 0.50% 0.53% 0.50% 0.52% 0.52% 0.49% 0.50% 0.51% 0.47% 0.59%

Chg 1

Chg 2,3

Chg 4, 5, 6

Chg 7, 8

Chg 9

Chg 10, 11

Chg 12, 13

Chg 14

Implementation Start

UCL

LCL

0%

1%

2%

3%

4%

Month and Year

Patients unplanned return to OR(P Chart)

Perc

enta

ge o

f patients

unpla

nned r

etu

rn to O

R

Geetika

“P” Chart with Changes and Data Table

Sandra

CL 0.0178

UCL0.0297

LCL0.0059

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

Jan

-12

Feb

-12

Mar

-12

Ap

r-1

2

May

-12

Jun

-12

Jul-

12

Au

g-1

2

Sep

-12

Oct

-12

No

v-1

2

De

c-1

2

Jan

-13

Feb

-13

Mar

-13

Ap

r-1

3

May

-13

Jun

-13

Jul-

13

Au

g-1

3

Sep

-13

Oct

-13

No

v-1

3

De

c-1

3

Jan

-14

Feb

-14

# P

ts U

np

lan

ne

d R

etu

rn t

o O

R -

# Su

rge

rie

s

Months

# Pts Unplanned Return to OR / # Surgeries p Chart

P CHART

Months

# Pts Unplanned Return to

OR # Surgeries

Jan-12 27 984

Feb-12 20 982

Mar-12 25 996

Apr-12 23 998

May-12 31 1070

Jun-12 17 1031

Jul-12 21 886

Aug-12 28 964

Sep-12 24 1128

Oct-12 22 960

Nov-12 19 1193

Dec-12 24 998

Jan-13 30 1070

Feb-13 22 895

Mar-13 15 852

Apr-13 18 963

May-13 12 956

Jun-13 22 1001

Jul-13 8 956

Aug-13 2 995

Sep-13 9 987

Oct-13 6 943

Nov-13 20 965

Dec-13 6 980

Jan-14 2 923

Feb-14 6 1106

Rachel L and Iyoni

1.78%

UCL

LCL

0%

1%

2%

3%

4% J

an

ua

ry 2

01

2

Feb

ruary

20

12

Ma

rch

201

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er

20

12

Octo

be

r 2

01

2

No

ve

mb

er

20

12

De

ce

mb

er

20

12

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er

20

13

Octo

be

r 2

01

3

No

ve

mb

er

20

13

De

ce

mb

er

20

13

Ja

nua

ry 2

01

4

Feb

ruary

20

14

P Chart - Percent Unplanned Returns (Monthly)Percent unplanned returns

Change 2 & 3

Change 4, 5 & 6

Change 7 & 8

Change 10 & 11

Change 12 & 13

Change 14

Implementation starts

Change 1Change 9

Emma

1.8 %

UCL

LCL

0.0 %

0.5 %

1.0 %

1.5 %

2.0 %

2.5 %

3.0 %

3.5 %Jan

-12

Fe

b-1

2

Ma

r-1

2

Ap

r-12

Ma

y-1

2

Jun

-12

Jul-

12

Au

g-1

2

Se

p-1

2

Oct-

12

Nov-1

2

Dec-1

2

Jan

-13

Fe

b-1

3

Ma

r-1

3

Ap

r-13

Ma

y-1

3

Jun

-13

Jul-

13

Au

g-1

3

Se

p-1

3

Oct-

13

Nov-1

3

Dec-1

3

Jan

-14

Fe

b-1

4

P Chart - Unplanned returns to ORPercent

Chg

4,5,6 Chg

7,8Chg

9

Chg

10,11

Chg

12.13 Chg 14Chg

2,3

Implementatio

n start

Chg

1

Cecilie

B. A "P"chart (a type of control chart for attribute data) with # patients returning to OR as the numerator (often called count of errors) and the # surgeries as the denominator (often called # inspected).

Rachel Fletcher

Pe

rce

nt

Percent Unplanned Returns to OR P chart

984

27

982

20

996

25

998

23

1070

31

1031

17

886

21

964

28

1128

24

960

22

1193

19

998

24

1070

30

895

22

852

15

963

18

956

12

1001

22

956

8

995

2

987

9

943

6

965

20

980

6

923

2

1106

6

# Surgeries

# Pts Return

p chart

UCL = 3.54

Mean = 2.16

LCL = 0.78

Goal = 0.5

Chg 1

Chg 2 & 3

Chg 4 & 5

Chg 7 & 8

Chg 9

Chg 10 & 11

Chg 12 & 13

Chg 14

Implement

F 04 M A M J J A S O N D J 05 F M A M J J A S O N D J 06 F M A M

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

The way I’d handle it

Other Charts…thank you!!!

Month Revenue $k Margin $k

Mar-12 213 160

Apr-12 174 160

May-12 190 163

Jun-12 220 172

Jul-12 182 174

Aug-12 208 180

Sep-12 210 182

Oct-12 163 190

Nov-12 160 197

Dec-12 230 200

Jan-13 180 208

Feb-13 197 210

Mar-13 225 210

Apr-13 160 213

May-13 172 220

Jun-13 210 225

Jul-13 227 227

Aug-13 200 230

Sep-13 232 232

Oct-13 241 240

Nov-13 260 241

Dec-13 263 243

Jan-14 247 247

Feb-14 252 250

Mar-14 250 252

Apr-14 261 256

May-14 240 258

Jun-14 258 260

Jul-14 270 260

Aug-14 243 261

Sep-14 256 263

Oct-14 260 270

Nov-14

Dec-14

Jan-15

Feb-15

I

Chart

Data

Profit Margin I chart(Not convinced I understand this)

Sandra

Individual (xmr) charts

3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14 2/1/14 3/1/14 4/1/14 5/1/14 6/1/14 7/1/14 8/1/14 9/1/14 10/1/14

Subgroup 31 54 60 55 78 42 35 56 36 25 34 14 56 57 22 12 31 22 17 24 16 26 35 28 69 64 95 83 64 73 61 78

Center 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4 45.4

UCL 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4 87.4

LCL 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

UCL

LCL

0

10

20

30

40

50

60

70

80

90

100

Pro

fit M

arg

in $

K

Profit Margin $KMeasure

Stephen

3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/1210/1/1

211/1/1

212/1/1

21/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13

10/1/13

11/1/13

12/1/13

1/1/14 2/1/14 3/1/14 4/1/14 5/1/14 6/1/14 7/1/14 8/1/14 9/1/1410/1/1

4

Subgroup 23.0 6.0 5.0 23.0 36.0 7.0 21.0 20.0 11.0 9.0 20.0 42.0 1.0 35.0 10.0 19.0 9.0 5.0 7.0 8.0 10.0 9.0 7.0 41.0 5.0 31.0 12.0 19.0 9.0 12.0 17.0

Center 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8

UCL 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5 51.5

LCL 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Change in p

rofit m

arg

in $

K

Monthly change in profit margin $K

Stephen

3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/1210/1/1

211/1/1

212/1/1

21/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13

10/1/13

11/1/13

12/1/13

1/1/14 2/1/14 3/1/14 4/1/14 5/1/14 6/1/14 7/1/14 8/1/14 9/1/1410/1/1

4

Subgroup 213 174 190 220 182 208 210 163 160 230 180 197 225 160 172 210 227 200 232 241 260 263 247 252 250 261 240 258 270 243 256 260

Center 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4 220.4

UCL 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0 282.0

LCL 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9 158.9

UCL

LCL

0

50

100

150

200

250

300

Revenue $kMeasure

Stephen

3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/1210/1/1

211/1/1

212/1/1

21/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13

10/1/13

11/1/13

12/1/13

1/1/14 2/1/14 3/1/14 4/1/14 5/1/14 6/1/14 7/1/14 8/1/14 9/1/1410/1/1

4

Subgroup 39.0 16.0 30.0 38.0 26.0 2.0 47.0 3.0 70.0 50.0 17.0 28.0 65.0 12.0 38.0 17.0 27.0 32.0 9.0 19.0 3.0 16.0 5.0 2.0 11.0 21.0 18.0 12.0 27.0 13.0 4.0

Center 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1 23.1

UCL 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6

LCL 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0Monthly Change in Revenue $K

Stephen

UCL

0

20

40

60

80

100

120

Ma

rch,

201

2

Ap

ril, 2

01

2

Ma

y, 2

012

Jun

e, 2

012

July

, 2

01

2

Au

gu

st, 2

012

Se

pte

mb

er,

20

12

Octo

be

r, 2

01

2

Nove

mbe

r, 2

01

2

Dece

mbe

r, 2

01

2

Jan

uary

, 2

01

3

Fe

bru

ary

, 20

13

Ma

rch,

201

3

Ap

ril, 2

01

3

Ma

y, 2

013

Jun

e, 2

013

July

, 2

01

3

Au

gu

st, 2

013

Se

pte

mb

er,

20

13

Octo

be

r, 2

01

3

Nove

mbe

r, 2

01

3

Dece

mbe

r, 2

01

3

Jan

uary

, 2

01

4

Fe

bru

ary

, 20

14

Ma

rch,

201

4

Ap

ril, 2

01

4

Ma

y, 2

014

Jun

e, 2

014

July

, 2

01

4

Au

gu

st, 2

014

Se

pte

mb

er,

20

14

Octo

be

r, 2

01

4

XMR Chart - Margin $KMargin

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Ma

rch

201

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er…

Octo

be

r 2

01

2

No

ve

mb

er

20

12

De

ce

mb

er

20

12

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er…

Octo

be

r 2

01

3

No

ve

mb

er

20

13

De

ce

mb

er

20

13

Ja

nua

ry 2

01

4

Feb

ruary

20

14

Ma

rch

201

4

Ap

ril 20

14

Ma

y 2

014

Ju

ne 2

014

Ju

ly 2

01

4

Au

gu

st 2

014

Se

pte

mb

er…

Octo

be

r 2

01

4

Moving Range

Emma

UCL

LCL

100

120

140

160

180

200

220

240

260

280

300

Ma

rch

201

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er…

Octo

be

r 2

01

2

No

ve

mb

er…

De

ce

mb

er…

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er…

Octo

be

r 2

01

3

No

ve

mb

er…

De

ce

mb

er…

Ja

nua

ry 2

01

4

Feb

ruary

20

14

Ma

rch

201

4

Ap

ril 20

14

Ma

y 2

014

Ju

ne 2

014

Ju

ly 2

01

4

Au

gu

st 2

014

Se

pte

mb

er…

Octo

be

r 2

01

4

XMR Chart - Revenue $KRevenue

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Ma

rch

201

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er…

Octo

be

r 2

01

2

No

ve

mb

er

20

12

De

ce

mb

er

20

12

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er…

Octo

be

r 2

01

3

No

ve

mb

er

20

13

De

ce

mb

er

20

13

Ja

nua

ry 2

01

4

Feb

ruary

20

14

Ma

rch

201

4

Ap

ril 20

14

Ma

y 2

014

Ju

ne 2

014

Ju

ly 2

01

4

Au

gu

st 2

014

Se

pte

mb

er…

Octo

be

r 2

01

4

Moving Range

Emma

"Individual (xmr)"Rachel Fletcher

Month # ADEs Doses Doses/1000 Note

3/1/2012 50 17110 17.11

4/1/2012 44 12140 12.14

5/1/2012 47 17990 17.99

6/1/2012 32 14980 14.98xxx

7/1/2012 51 21980 21.98

8/1/2012 57 15320 15.32

9/1/2012 43 12990 12.99

10/1/2012 61 19760 19.76

11/1/2012 30 8670 8.67

12/1/2012 32 12680 12.68

1/1/2013 41 20330 20.33yyy

2/1/2013 47 18550 18.55

3/1/2013 31 14310 14.31

4/1/2013 11 9730 9.73

5/1/2013 3 11470 11.47

6/1/2013 11 21390 21.39

7/1/2013 9 13370 13.37

8/1/2013 3 6370 6.37

9/1/2013 10 10300 10.3

10/1/2013 8 11170 11.17

11/1/2013 9 10910 10.91

12/1/2013 4 8760 8.76

1/1/2014 9 11140 11.14

2/1/2014

3/1/2014

4/1/2014

U

Chart

Data

"U -revising Limits" Rachel Fletcher

UCL

LCL

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5 M

arc

h 2

01

2

Ap

ril 20

12

Ma

y 2

012

Ju

ne 2

012

Ju

ly 2

01

2

Au

gu

st 2

012

Se

pte

mb

er

20

12

Octo

be

r 2

01

2

No

ve

mb

er

20

12

De

ce

mb

er

20

12

Ja

nua

ry 2

01

3

Feb

ruary

20

13

Ma

rch

201

3

Ap

ril 20

13

Ma

y 2

013

Ju

ne 2

013

Ju

ly 2

01

3

Au

gu

st 2

013

Se

pte

mb

er

20

13

Octo

be

r 2

01

3

No

ve

mb

er

20

13

De

ce

mb

er

20

13

Ja

nua

ry 2

01

4

U chart - No of ADE per 1000 doses Rate

Emma

U chart with phasingI have assumed (maybe incorrectly) that XXX and YYY mark the initiation of a successful change

phase 1 3/2/12 – 6/1/12phase 2 7/1/12 – 1/1/13phase 3 2/1/13 – 1/1/14

3/1/12 4/1/12 5/1/12 6/1/12 7/1/12 8/1/12 9/1/12 10/1/12 11/1/12 12/1/12 1/1/13 2/1/13 3/1/13 4/1/13 5/1/13 6/1/13 7/1/13 8/1/13 9/1/13 10/1/13 11/1/13 12/1/13 1/1/14

Subgroup 2.9 3.6 2.6 2.1 2.3 3.7 3.3 3.1 3.5 2.5 2.0 2.5 2.2 1.1 0.3 0.5 0.7 0.5 1.0 0.7 0.8 0.5 0.8

Center 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1

UCL 4.0 4.2 4.0 4.1 3.9 4.1 4.2 4.0 4.5 4.2 3.9 1.8 1.9 2.0 2.0 1.7 1.9 2.3 2.0 2.0 2.0 2.1 2.0

LCL 1.6 1.3 1.6 1.5 1.7 1.5 1.4 1.7 1.1 1.4 1.7 0.3 0.2 0.1 0.1 0.4 0.2 0.0 0.1 0.1 0.1 0.0 0.1

UCL

LCL

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

AD

E's

/ 1

000 d

oses

ADE's / 1000 doses - U Chart with phasingRate

Stephen

?With PhasingSandra

Software Heads-Up….In Workshop 2 you will have case studies or real data and be asked to

jump in to building appropriate graphs:

•Run charts

•Shewhart control charts—5 types (individuals, X bar S, P, C, U charts)

•Pareto charts

•Histograms (frequency plot)

•Scatter plots

Use the excel database (SPC Exercises

2016) posted on the Extranet for practice.

If you are using QI charts, the Pareto,

Histogram and Scatter Plot are built

using Excel so you will need to know

how to create those charts using basic

Excel functions.

Load add in: Data Analysis Toolpack

Instructional Video:

• Richard Scoville walks through creating a P Chart in QI Charts –

including how to add a useful data table:

https://www.youtube.com/watch?v=H3m3QCeec1M

Other Useful Resources

Next Call

October 6, 2016

PDSA Presentations – Prep for Workshop 2

3:00-4:30 pm BST