Hamad Medical Corporation Launch Event Navigating the Quality...

Navigating theQuality Measurement Journey

2 October 2013

Prepared and presented byRobert Lloyd, PhDExecutive Director Performance Improvement

Hamad Medical Corporation Launch Event

©Copyright 2013 Institute for Healthcare Improvement/R. Lloyd

The Improvement Guide, API, 2009

The Model for Learning and Change

When you combine

the 3 questions with the…

…the Model

for Improvement.

PDSA cycle, you get…

©Copyright 2013 Institute for Healthcare Improvement/R. Lloyd3

“You can’t fatten a cow by weighing it”- Palestinian Proverb

Improvement is NOT just about measurement!

However, without measurement you will never be able to connect the dots and

answer question #2 in the MFI.

The Role of Measurement


• The purpose of measurement in QI work is for learning not

judgment!

• All measurement has limitations, but the limitations do not negate

its value for learning.

• Build a balanced set of measures that reflect the VOC and VOP.

• All measurement should be linked to the team’s Aim.

• Measurement should be used to guide improvement and test

changes.

• Measurement should be integrated into the team’s daily routine.

• Data should be plotted over time on annotate graphs.

• Focus on the Vital Few!

Measurement is Central to the Team’s Ability to Improve


1. By understanding the variation that lives within your data

2. By making good management decisions about this variation (i.e.,

don’t overreact to a special cause and don’t think that random movement of your data up

and down is a signal of improvement).

How will we know that achange is an improvement?


The Role of Measurement: Connect the Dots!


What is this? (dots 1 – 25)


Any idea? (dots 1 – 50)


How about now? (dots 1 – 100)


Ahhh…now I see it! (dots 1 – 150)


It was so obvious wasn’t it?


So, where do we start to connect the dots?


Improvement?(improving the effectiveness or

efficiency of a process)

Accountability Judgment?(making comparisons;

no change focus)

Research?(testing theory and building

new knowledge)

Why are you measuring?


The Three Faces ofPerformance Measurement

Aspect Improvement Accountability Research

Aim Improvement of care

(efficiency & effectiveness)

Comparison, choice,

reassurance, motivation

for change

New knowledge

(efficacy)

Methods:

• Test ObservabilityTest observable

No test, evaluate current

performance Test blinded or controlled

• Bias Accept consistent bias Measure and adjust to

reduce bias

Design to eliminate bias

• Sample Size “Just enough” data, small

sequential samples

Obtain 100% of available,

relevant data

“Just in case” data

• Flexibility of

Hypothesis

Flexible hypotheses,

changes as learning takes

place

No hypothesis

Fixed hypothesis

(null hypothesis)

• Testing Strategy Sequential tests No tests One large test

• Determining if achange is animprovement

Analytic Statistics

(statistical process control) Run & Control

charts

No change focus

(maybe compute a

percent change or rank

order the results)

Enumerative Statistics(t-test, F-test,

chi square,

p-values)

• Confidentiality ofthe data

Data used only by those

involved with improvement

Data available for public

consumption and review

Research subjects’

identities protected

Adapted from: Lief Solberg, Gordon Mosser and Sharon McDonald,Journal

on Quality Improvement vol. 23, no. 3, (March 1997), 135-147.


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Control Chart (p-chart)Percent Primary Cesarean Section

Data for

Improvement

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Data for Judgment

These data points are all common cause (random) variation


So, how do you view the Three Faces of Performance Measurement?

Or,

As… As a…

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Relating the Three Faces ofPerformance Measurement to your work

The three faces of performance measurement should not be seen as mutually exclusive silos. This is not an either/or situation.

All three areas must be understood as a system. Individuals need to build skills in all three areas.

Organizations need translators who and be able to speak the language of each approach.

The problem is that individuals identify with one of the approaches and dismiss the value of the other two.


Even with this thing, I have no

idea where we’re headed!Do you have a plan to

guide your quality measurement

journey?


AIM (How good? By when?)

Concept

Measure

Operational Definitions

Data Collection Plan

Data Collection

Analysis ACTION

The Quality Measurement Journey

Source: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett Publishers, 2004.


AIM (Why are you measuring?)

Concept

Measures



Data Collection

Analysis


Source: R. Lloyd. Quality Health Care: A Guide to Developing and Using

Indicators. Jones and Bartlett, 2004.

ACTION


Moving from a Concept to a Measure

“Hmmmm…how do I move from a concept

to an actual measure?

Every concept can have MANY

measures.

Which one is most appropriate?


Concept Potential Measures

Hand Hygiene Ounces of hand gel used each day

Ounces of gel used per staff

Percent of staff washing their hands (before & after visiting a patient)

Medication Errors Percent of errors

Number of errors

Medication error rate

VAPs Percent of patients with a VAP

Number of VAPs in a month

The number of days without a VAP

Every concept can have many measuresSource: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett, 2004.


• Outcome Measures: Voice of the customer or patient. How is the system performing? What is the result?

• Process Measures: Voice of the workings of the system. Are the parts/steps in the system performing as planned?

• Balancing Measures: Looking at a system from different directions/dimensions. What happened to the system as we improved the outcome and process measures (e.g. unanticipated consequences, other factors influencing outcome)?

Three Types of Measures


Balancing Measures: Paying Attention to Unintended Consequences

• Outcome (quality, time)

• Transaction (volume, number of patients)

• Productivity (cycle time, efficiency, utilisation, flow,

capacity, demand)

• Financial (money, staff hours, materials)

• Appropriateness (validity, usefulness)

• Patient satisfaction

• Staff satisfaction


Potential Set of Measures for Improvement in the ED

Topic

Outcome Measures

Process Measures

Balancing Measures

Improve waiting time and patient satisfaction in the ED

Total Length of Stay in the ED

Patient Satisfaction Scores

Time to registration

Patient / staff comments on flow

% patient receiving discharge materials

Availability of antibiotics

Volumes

% Leaving without being seen

Staff satisfaction

Financials



Concept

Measures



Data Collection

Analysis




ACTION


An Operational Definition...

… is a description, in quantifiable terms, of what to measure and the steps to follow to measure it consistently.

• It gives communicable meaning to a concept

• Is clear and unambiguous

• Specifies measurement methods and equipment

• Identifies criteria

Source: R. Lloyd. Quality Health Care: A Guide to Developing and

Using Indicators. Jones and Bartlett Publishers, 2004.


What is a goal?The whole ball or half the ball?

?


How do you define the following healthcare concepts?

• World Class Performance

• Unplanned readmissions

• Teenage pregnancy

• Cancer waiting times

• Health inequalities

• Asthma admissions

• Childhood obesity

• Patient education

• Health and wellbeing

• Adding life to years and years to life

• Children's palliative care

• Safe services

• Smoking cessation

• Urgent care

• Delayed discharges

• End of life care

• Falls (with/without injuries)

• Childhood immunizations

• Complete maternity service

• Patient engagement

• Moving services closer to home

• Successful breastfeeding

• Ambulatory care

• Access to health in deprived areas

• Diagnostics in the community

• Productive community services

• Vascular inequalities

• Breakthrough priorities


The Good News!We already have measures and definitions

30

Outcome Measures Data Collection Guidance

VAP rate

(CCO1)

• Numerator: The total

number of ventilator

acquired pneumonia

episodes in the month

• Denominator: The total

ventilator days in the month

• The VAP rate is calculated

by dividing the total number

of VAPs occurring in the

month (the numerator) by

the total number of

ventilator days in the month

(the denominator) and then

multiplying the result by

1000 to create a VAP rate

per 1000 ventilator days

• Report monthly infection rate for the months of

October – December 2013. This serves as your

baseline. Continue to report monthly data over the life

of the Campaign into the Extranet. Provide

numerators and denominators when entering the data.

The annotation section should be used to reflect any

interventions that were made to reduce the VAP rate.

• There should be no sampling for this measure. If an

infection control practitioner reports data quarterly,

please disaggregate and report the VAP data by

month.


You will need to develop measures specific to the

change concepts and ideas you plan to test in your

workstreams.

31

But, you will need to develop additional measures!

©Copyright 2010 IHI Improvement Advisor Professional Development Program

• Use the Driver Diagram for your workstream as a reference and guide to build measures.

• Make sure you identify a balanced set of measures (outcome, process and balancing measures).

• Use the Measurement Plan Worksheet to record your work

• Then select several of your identified measures and develop a clear operational definition for each measure.

• Use the Operational Definition Worksheet© to record your work.

• The Questions for Building Operational Definitions© will provide guidance on the specific issues which need to be addressed if you want to develop clear and concise operational definitions.

Developing a Set of Measures andOperational Definitions (prep for LS1)


Measure NameType

(Process, Outcome or Balancing)

Driver addressed bythis measure

1.

2.

3.

4.

5.

6.

7.

8.

9.

Measurement Plan Worksheet

Source: R. Lloyd 2013


Measure Name(Be sure to indicate if it

is a count, percent, rate, days between, etc.)

Operational Definition(Define the measure in very specific terms.

Provide the numerator and the denominator if a percentage or rate.

Be as clear and unambiguous as possible)

Data Collection Plan(How will the data be collected?

Who will do it? Frequency? Duration? What is to be excluded?)

Operational Definition Worksheet

Name of team:______________________________ Date:__________

Source: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett, 2004.


Example of a Complete Operational Definition

Measure Name: Percent of inpatient medication orders with an error

Numerator: Number of inpatient medication orders with one or more errors

Denominator: Number of inpatient medication orders received by the pharmacy

Data Collection Plan:

• This measure applies to all inpatient units

• The data will be stratified by shift and by type of order (stat versus routine)

• The data will be tracked daily and grouped by week

• The data will be pulled from the pharmacy computer system

• Initially all medication orders will be reviewed. A stratified proportional random

sample will be considered once the variation in the process is fully understood and the volume of orders is analyzed.


Team name: _____________________________________________________________________________

Date: __________________ Contact person: ____________________________________

WHAT PROCESS DID YOU SELECT?

WHAT SPECIFIC MEASURE DID YOU SELECT FOR THIS PROCESS?

OPERATIONAL DEFINITIONDefine the specific components of this measure. Specify the numerator and denominator if it is a percent or a rate. If it is an average, identify the calculation for deriving the average. Include any special equipment needed to capture the data. If it is a score (such as a patient satisfaction score) describe how the score is derived. When a measure reflects concepts such as accuracy, complete, timely, or an error, describe the criteria to be used to determine “accuracy.”

Questions for Building Operational Definitions©Source: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett, 2004.


DATA COLLECTION PLANWho is responsible for actually collecting the data?How often will the data be collected? (e.g., hourly, daily, weekly or monthly?)What are the data sources (be specific)?What is to be included or excluded (e.g., only inpatients are to be included in this measure or only stat lab requests should be tracked).How will these data be collected?Manually ______ From a log ______ From an automated systemAre these data:

Attributes data? ______ or Variables data? ______

BASELINE MEASUREMENTWhat is the actual baseline number? ______________________________________________What time period was used to collect the baseline? ___________________________________

TARGET(S) OR GOAL(S) FOR THIS MEASUREDo you have target(s) or goal(s) for this measure?Yes ___ No ___

Specify the External target(s) or Goal(s) (specify the number, rate or volume, etc., as well as the source of the target/goal.)

Specify the Internal target(s) or Goal(s) (specify the number, rate or volume, etc., as well as the source of the target/goal.)

Questions for Building Operational Definitions© (continued)



DATA COLLECTION PLANWho is responsible for actually collecting the data?How often will the data be collected? (e.g., hourly, daily, weekly or monthly?)What are the data sources (be specific)?What is to be included or excluded (e.g., only inpatients are to be included in this measure or only stat lab requests should be tracked).How will these data be collected?Manually ______ From a log ______ From an automated system

BASELINE MEASUREMENTWhat is the actual baseline number? ______________________________________________What time period was used to collect the baseline? ___________________________________

TARGET(S) OR GOAL(S) FOR THIS MEASUREDo you have target(s) or goal(s) for this measure?Yes ___ No ___

Specify the External target(s) or Goal(s) (specify the number, rate or volume, etc., as well as the source of the target/goal.)

Specify the Internal target(s) or Goal(s) (specify the number, rate or volume, etc., as well as the source of the target/goal.)

Questions for Building Operational Definitions© (continued)




Concept

Measures



Data Collection

Analysis




ACTION

We will address data collection topics in the Foundations Program


Now that you have selected and defined your measures, it is time to head out, cast your net and actually gather some data!


Key Data Collection Strategies

Stratification• Separation & classification

of data according to predetermined categories

• Designed to discover patterns in the data

• For example, are there differences by shift, time of day, day of week, severity of patients, age, gender or type of procedure?

• Consider stratification BEFORE you collect the data


Non-probability Sampling Methods

• Convenience sampling

• Quota sampling

• Judgment sampling

Probability Sampling Methods

• Simple random sampling

• Stratified random sampling

• Stratified proportional random sampling

• Systematic sampling

• Cluster sampling

Sampling MethodsSource: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett Publishers, 2004.


Sampling Options

Simple Random Sampling

Population Sample

Stratified proportional Random Sampling

Population Sample

Medical Surgical OB Peds

Judgment Sampling

Jan March April May JuneFeb

S S M PM M MOB OB S


44

Judgment Sampling

• Include a wide range of

conditions

• Selection criteria may change

as understanding increases

• Successive small samples

instead of one large sample

Especially useful for PDSA testing. Someone with

process knowledge selects items to be sampled.

Characteristics of a Judgment Sample:


We are absolutely crazy around here between 9

and 11 AM!

But, things are pretty quiet after 3 PM.

Judgment Sampling takes advantage of the knowledge of those who own the process

What do I know? I usually work

afternoon shift and that is a different

process altogether!


You have performance data.Now what the heck do you do with it?


“If I had to reduce my message for

management to just a few words, I’d say it

all had to do with reducing variation.”

W. Edwards Deming


Variation Exists!

48

Variation exists in all that we do, even in the simplest of activities. For example,

consider writing your name. This is a simple activity that you probably do each day.

What if your annual performance review, however, was based on being able to write

the first letter of your first name three times with no variation in the form, structure or overall appearance of the letter. If you are able to perform this simple task, you will

receive a 50 percent increase in your salary. Remember that there can be no

variation in the letters. Give it a try.

Now here is the second part of the your performance evaluation. Place your pen or

pencil in your opposite hand and write the same letter three times. How many of you passed the performance evaluation test? If you are like me your results look

something like this:

Source: R. Carey & R. Lloyd. Measuring Quality Improvement in Healthcare, ASQ Press, 2001.


Variation Exists!

49

Variation exists in all that we do, even in the simplest of activities. For example,

consider writing your name. This is a simple activity that you probably do each day.

What if your annual performance review, however, was based on being able to write

the first letter of your first name three times with no variation in the form, structure or overall appearance of the letter. If you are able to perform this simple task, you will

receive a 50 percent increase in your salary. Remember that there can be no

variation in the letters. Give it a try.

Now here is the second part of the your performance evaluation. Place your pen or

pencil in your opposite hand and write the same letter three times. How many of you passed the performance evaluation test? If you are like me your results look

something like this:

Bob’s left hand Bob’s right hand

Source: R. Carey & R. Lloyd. Measuring Quality Improvement in Healthcare, ASQ Press, 2001.


QualityBetter

Old Way(Quality Assurance)

QualityBetter Worse

New Way(Quality Improvement)

Action taken on all

occurrences

Reject defectives

Old Way versus New Way

Source: Robert Lloyd, Ph.D.

Requirement,Specification or Target

No

action

taken

here

Worse


The Problem

Performance against a target or the use of aggregated data presented in

tabular formats with summary statistics, will not help you measure

the impact of process improvement/redesign efforts.

Aggregated data can only lead to judgment, not to improvement!


Average CABG MortalityBefore and After the Implementation of a New Protocol

54

Perc

ent

Mort

alit

y

Time 1 Time 2

3.8

5.2

5.0%

4.0%

WOW!

A “significant drop”

from 5% to 4%

Conclusion -The protocol was a success! A 20% drop in the average mortality!


Average CABG MortalityBefore and After the Implementation of a New Protocol A Second

Look at the Data

55

Perc

ent

Mort

alit

y

24 Months

1.0

9.0

Now what do you conclude about the impact of the protocol?

5.0

UCL= 6.0

LCL = 2.0

CL = 4.0

Protocol implemented here


The average of a set of numbers can be created by many different distributions

X (CL)

Me

as

ure

Time


If you don’t understand the variation that lives in your data, you will be tempted to ...

• Deny the data (It doesn’t fit my view of reality!)

• See trends where there are no trends

• 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

• Discredit the messenger!


“What is the variation in one system over time?” Walter A. Shewhart - early 1920’s, Bell Laboratories

time

UCL

Every process displays variation:• Controlled variation

stable, consistent pattern of variation“chance”, constant causes

• Special cause variation“assignable”

pattern changes over time

LCL

Static ViewS

tatic

Vie

w

Dynamic View


Types of Variation

Common Cause Variation• Is inherent in the design of the

process

• Is due to regular, natural or ordinary causes

• Affects all the outcomes of a process

• Results in a “stable” process that is predictable

• Also known as random or unassignable variation

Special Cause Variation

• Is due to irregular or unnatural causes that are not inherent in the design of the process

• Affect some, but not necessarily all aspects of the process

• Results in an “unstable” process that is not predictable

• Also known as non-random or assignable variation


Good versus Bad Variation

Common Cause does not mean “Good Variation.” It only means that the process is stable and predictable.

For example, if a patient’s systolic blood pressure averaged around 165 and was usually between 160 and

170 mmHg, this might be stable and predictable but completely unacceptable.

Similarly Special Cause variation should not be viewed as “Bad Variation.” You could have a special cause that

represents a very good result (e.g., a low turnaround time), which you would want to emulate. Special Cause

merely means that the process is unstable and unpredictable.


3 Questions …

1. Is the process stable?

2. Is the process predictable?

3. Is the process capable?

The chart will tell you if the process is stable and predictable.

You have to decide if the output of the process is acceptable!


12/9

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0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

UCL=27.7018

CL=18.0246

LCL=8.3473

Percent of Cesarean Sections Performed Dec 95 - Jun 99

Common Cause Variation

Normal Sinus Rhythm (a.k.a. Common Cause Variation)

Week

Nu

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of M

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ica

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rro

rs p

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10

00

Pa

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nt D

ays

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

UCL=13.39461

CL=4.42048

LCL=0.00000

Medication Error Rate

Atrial Flutter Rhythm (a.k.a. Special Cause Variation)

Special Cause Variation


Attributes of a Leader WhoUnderstands Variation

Leaders understand the different ways that variation is viewed.

They explain changes in terms of common causes and special causes.

They use graphical methods to learn from data and expect others to consider variation in their decisions and actions.

They understand the concept of stable and unstable processes and the potential losses due to tampering.

Capability of a process or system is understood before changes are attempted.


Question Response Options1. The Board evaluates our data using

criteria for common and special cause

variation

Strongly Agree Agree

Not Sure

Disagree Strongly Disagree

2. Senior Management evaluates our data

using criteria for common and special cause

variation


Not Sure


3. Front-line Managers evaluate our data

using criteria for common and special cause

variation


Not Sure


4. Staff Members evaluate our data using

criteria for common and special cause

variation


Not Sure


If you responded Disagree or Strongly Disagree to any question, what criteria are used by this group to determine if data or improving or

getting worse?

Attributes of a Leader WhoUnderstands Variation



Concept

Measures



Data Collection

Analysis




ACTION


How can I depict variation?

STATIC VIEW

Descriptive StatisticsMean, Median & Mode

Minimum/Maximum/RangeStandard Deviation

Bar graphs/Pie charts

DYNAMIC VIEWRun Chart

Control Chart

(plot data over time)

Statistical Process Control (SPC)

Ra

te p

er

100

ED

Pa

tients

Unplanned Returns to Ed w/in 72 Hours

M41.78

17

A43.89

26

M39.86

13

J40.03

16

J38.01

24

A43.43

27

S39.21

19

O41.90

14

N41.78

33

D43.00

20

J39.66

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F40.03

22

M48.21

29

A43.89

17

M39.86

36

J36.21

19

J41.78

22

A43.89

24

S31.45

22

Month

ED/100

Returns

u chartu chartu chartu chart

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

0.0

0.2

0.4

0.6

0.8

1.0

1.2

UCL = 0.88

Mean = 0.54

LC L = 0.19


How do we analyze variation for quality improvement?

Run and Shewhart Charts

are the best tools to

determine if our

improvement strategies

have had the desired effect.


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Point Number

Po

un

ds o

f R

ed

Ba

g W

aste

3.25

3.50

3.75

4.00

4.25

4.50

4.75

5.00

5.25

5.50

5.75

6.00

Median=4.610

Measu

re

Time

Four simple run rules are used to determine if non-random data patterns are present

X (CL)~

Elements of a Run Chart

The centerline (CL) on a Run Chart is the Median


Jan01 Mar01 May01 July01 Sept01 Nov01 Jan02 Mar02 May02 July02 Sept02 Nov02

Month

Nu

mb

er

of

Co

mp

lain

ts

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

A

B

C

C

B

A

UCL=44.855

CL=29.250

LCL=13.645

Elements of a Shewhart Chart

X (Mean)

Me

as

ure

Time

An indication of a

special cause

(Upper Control Limit)

(Lower Control Limit)


February April

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16 Patients in February and 16 Patients in April

Min

ute

s

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

27.5

30.0

A

B

C

C

B

A

UCL=15.3

CL=10.7

LCL=6.1

XmR Chart

How all this works:Wait Time to See the Doctor

Baseline Period

Intervention

Where will the

process go?

Freeze the Control Limits and Centerline, extend them

and compare the new process performance to these

reference lines to determine if a special cause has been

introduced as a result of the intervention.


February April

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Min

ute

s

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

27.5

30.0

A

B

C

C

B

A

UCL=15.3

CL=10.7

LCL=6.1

XmR Chart

Freeze the Control Limits and compare the

new process performance to the baseline

using the UCL, LCL and CL from the

baseline period as reference lines

A Special Cause is detected

A run of 8 or more data points on one side of the centerline reflecting a sift in the process

Baseline Period

Intervention

How it works:Wait Time to See the Doctor


February April

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27

28

29

30

31

32


Min

ute

s

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

27.5

30.0

A

B

C

C

B

A

UCL=15.3

CL=10.7

LCL=6.1

XmR Chart

Intervention Make new control limits for

the process to show the

improvement

Baseline Period

How it works:Wait Time to See the Doctor


Run and Control Charts don’t tell you

• The reasons(s) for a Special Cause

• Whether or not a Common Cause process should be improved (Is the performance of the process acceptable?)

• How the process should actually be improved or redesigned


1. Which process do you want to improve or redesign?

2. Does the process contain non-random patterns or special causes?

3. How do you plan on actually making improvements? What strategies do you plan to follow to make things better?

4. What effect (if any) did your plan have on the process performance?

Run & Control Charts will help you answer Questions 2 & 4.

YOU need to figure out the answers to Questions 1 & 3.

A Simple Improvement Plan


Sustaining improvements and Spreading changes to other locations

Developing a change

Implementing a change

Testing a change

Act Plan

Study Do

Theory and Prediction

Test under a variety of conditions

Make part of routine operations

The Sequence of Improvement requires Measurement


AIM (How good? By when?)

Concept

Measure



Data Collection

Analysis ACTION


Source: R. Lloyd. Quality Health Care: A Guide to Developing and Using Indicators. Jones and Bartlett Publishers, 2004.


ExerciseMeasurement Self-Assessment

This self-assessment is designed to help quality facilitators gain a better understanding of where

they personally stand with respect to the milestones in the Quality Journey. What would your

reaction be if you had to explain the PDSA cycle to your colleagues? Why is it preferable to plot

data over time rather than use aggregated statistics and tests of significance? Can you construct a

run chart or help a team decide which control is most appropriate for their data?

You may not be asked to do all of the things listed below today or even next week. But, if you are

facilitating a QI team or expect to achieve the goals o our collaborative, sooner or later these

questions will be posed. How will you deal with them?

The place to start is to be honest with yourself and see how much you know about QI concepts and

methods. Once you have had this period of self-reflection, you will be ready to develop a learning

plan for yourself and those on your improvement team.

Use the following Response Scale. Select the one response which best captures your opinion.

1 I could teach this topic to others!

2 I could do this by myself right now but would not want to teach it!

3 I could do this but I would have to study first!

4 I could do this with a little help from my friends!

5 I'm not sure I could do this!

6 I'd have to call in an outside expert!

Source: R. Lloyd, Quality Health Care:

A Guide to Developing and Using

Indicators. Jones & Bartlett

Publishers, 2004: 301-304.


Exercise: Measurement Self-AssessmentSource: R. Lloyd, Quality Health Care: A Guide to Developing and Using Indicators.

Jones & Bartlett Publishers, 2004: 301-304.

Measurement Topic or SkillResponse Scale

1 2 3 4 5 6

1. Build clear aim statements for our work

2. Move my team from concepts to specific quantifiable measures

3. Building clear and unambiguous operational definitions for our measures

4. Develop data collection plans (including sampling strategies and stratification)

5. Explain why plotting data over time is preferable to using aggregated data and summary statistics

6. Describe the differences between common and special causes of variation

7. Construct and interpret run and control charts

8. Identify specific ideas that we believe will achieve the results we desire

9. Set up and run PDSA tests on the ideas we have for improvement

10. Apply the sequence of improvement (testing, implementing and spreading) to the specific workstreams we are working on


It must be remembered that there is nothing more difficult to plan, more doubtful of success, nor more dangerous to manage than the creation of a new system.

For the initiator has the enmity of all who would profit by the preservation of the old institution and merely lukewarm defenders in those who would gain by the new one.

A closing thought…

Machiavelli, The Prince, 1513Machiavelli, The Prince, 1513Machiavelli, The Prince, 1513Machiavelli, The Prince, 1513

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