Quality Improvement Try it – you might like it!

Dr Emma Donaldson

@E_arnotsmith

Emma.donaldson@srft.nhs.uk

What is Quality Improvement?• Research:

– Provides the evidence– Tells us the RIGHT THING TO DO

• Quality Improvement:– Helps us develop systems to deliver care– Ensures we are DOING THE THING RIGHT

• Audit:– Provides assurance of excellent care– CONFIRMS WE ARE DOING THE RIGHT

THING, RIGHT

Every system is perfectly designed to get the results that it gets

Model for Improvement

A coat hanger for improvement projects!

Model for Improvement

Start with the aim…

• The solutions come last• Let solutions come from the team• If you have a good idea, the team will have

it too (then they’ll own it!)• If they have a bad idea, let them test it

A Good Aim

• S pecific

• M easurable

• A chievable

• R elevant

• T ime limited

Stre-e-e-e-e-e-e-e-e-e-etch

Aim statements

• 1 – provide adequate pain control to all patients.

• 2 – 90% of patients who report that they had pain will respond “yes” to “did staff do all they could to control your pain” by June 2012

Types of Aim Statement

Absolute:95% of eligible patients should achieve all the measures in the acute stroke care bundle by…………

Relative:50% reduction in delays starting the morning operating list by…………..

“The greatest danger for most of us is not that our aim is too high and we miss it, but

that it is too low and we reach it.”Michelangelo

A Driver Diagram

• Reinforces the aim statement as the goal • Clarifies the big picture • Identifies primary system components• Aids in development of measurement

Most importantly: Helps teams to articulate their contribution to the overall aim and avoid missing important system components

50% reduction in acute central line infections in ICU, MHDU and Renal (G3/Renal Unit) by June 2009

• Nominate 2 clinical leads from your ward• Introduce systems for:

• competency training• quality assurance • encouraging reporting for learning

Leadership, Governance & Staff Education

Process Standardisation

Patient Involvement

• Introduce system of assessment for most appropriate line

• Paired insertion of central lines mandatory throughout

• Mandatory use of care pathways• Daily review for removal

• Consider recruiting patient champion• Introduce system of appropriate

communications• Involve patients in early identification of

infection

Measurement

• Present data in ward area• Introduce reporting system• Celebrate success• Develop system for measuring catheter

days

Central Lines

Limitations of drivers

• Not a perfect science• Will require ongoing amendment• Interplay between drivers • Contribution of each driver is unlikely to be

equally distributed

Model for Improvement

Stroke MeasuresAim: To achieve a score of 95% on the Sentinel audit by October

2008

• Outcome Measures– Audit score– The mortality rate of stroke patients

• Process Measures– The % of patients receiving a brain scan within 24hrs

• Balancing Measures– Time spent by ward staff completing forms – Wait time for other patients requiring

brain scan

The 3 reasons for measurement

Source: Robert Lloyd IHI 2006

Before AFTERThe project

Did we achieve anything?

Are things better?

Ways to display data: Static View…

Ways to display data: Dynamic View…

Run Charts

• Viewing TIME ORDERED DATA is a powerful way of detecting change

• It can tells us when a real change has occurred

• The pattern contains additional useful information

Average Before=8 hours delayAverage After=3 hours delay

DG 1-11/12

So in Quality Improvement we are concerned with plotting data over time in order to

understand variation in processes

“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.E.Deming

Types of Variation

Common Cause

• Is due to natural and regular causes

• Results in a ‘stable’ process

• Also known as random variation

Special Cause

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

• Results in an ‘unstable’ process that is not predictable

• Also know as non-random variation

Understanding variation

• The outcome of every process is affected by lots of little things

• Each of these little things varies naturally• All these little variances add up• This makes the process vary over time

1 2 3 4 5 6 7 80

50

100

150

200

250

Antibiotic drawn up

Antibiotic prescribed

Xray seen

Xray

Porters

Order Xray

Clerk/exam

See doc

Min

Patients

1 2 3 4 5 6 7 80

50

100

150

200

250

Antibiotic drawn up

Antibiotic prescribed

Xray seen

Xray

Porters

Order Xray

Clerk/exam

See doc

Patients

Min

Common Cause Variation

1 2 3 4 5 6 7 8 9 10 11 12 1350

70

90

110

130

150

170

190

210

230

Min

• A system can also be affected by a big, unusual influence

• The size of the change produced is BIG in relation to the common cause variances

• It happens much less frequently than the common cause variances

1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

50

100

150

200

250

300

350

400

Antibiotic drawn up

Antibiotic prescribed

Xray seen

Xray

Porters

Order Xray

Clerk/exam

See doc

Major Incident

Patients

Min

Special Cause Variation

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 260

50

100

150

200

250

300

350

400

450

Major Incident in A&E

Patients

Min

Statistical Process Control

• Engineering science uses a robust approach to detect deviations from the usual pattern

• This can tell you if you have really achieved an improvement,

• or if a stable process has deteriorated

% O

f P

atie

nts

% Of Patients Receiving Swallow Screen Within 24hrs

Month

Mean

LCL

0

10

20

30

40

50

60

70

80

90

100

8 datapoints above the baseline mean = special cause variation

Examples – Length of Stay

“All improvement will require change,

but not all change will result in improvement”

Why test change before implementing it?

• It involves less time, money and risk • The process is a powerful tool for learning;

from both ideas that work and those that don't

• It is safer and less disruptive for patients and staff

• Because people have been involved in testing and developing the ideas, there is often less resistance

Hunch

Workable solution

The PDSA Cycle

Plan• What are you going

to test?• What do you predict

will happen? • Develop the test

(Who? What? When? Where? Data?)

Do• Try out the test on a small

scale • Observe & document results

Study• Analyse data • Study the results• Compare results &

predictions

ActWhat will you do next?• Adapt• Adopt• Abandon

You already do this every day!!

Int J STD AIDS. 2010 Jul;21(7):521-3

Successful PDSA Cycles

• Think ahead• Small scale• Predict• Test with willing staff• Don’t ask permission or for consensus• Data and documentation

What PDSAs Are Not…

• A radical change to a system /process• Full blown trust-wide implementation • Mini projects• Top down directives

‘PDSA’s ‘test’ a proposed change

PDSA principles

• Initial ideas usually don’t work• If a PDSA “fails”, then the idea would not

work reliably• But lots can be learnt during the process

Conclusion - 1

• Always start with the aim• Spend time working out measures• Gather information, set up measurement

system• Drivers, cause effects, theory of change• Only then solutions

Conclusion - 2

• Test solutions with PDSA cycles

• Monitor effect with run charts

• Start small, very small

Thank you.