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Using data to measure, understand and improve service delivery

An introduction to Variation and Statistical Process Control (SPC)

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What is SPC?

S = Statistical, because we use some statistical concepts to help understand processes

P = Process, because we deliver our work through processes i.e. how we do things

C = Control, by this we mean predictable

• Continuous and dynamic – to give a better story over time, as opposed comparative and static – used for judgements

• A way of demonstrating and thinking about variation• A simple tool for analysing data – Measurement for

improvement • A tool to help make better decisions• Easy and sustainable to use

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What can it do for me?• Help you really understand the data• Identify the special causes in a process, not just guess what they are• Identify the levels of variation in a system, not just the average• Identify if a process is sustainable - i.e are your improvements

sustaining over time• Identify if a process can meet a target• Identify when an implemented improvement has changed a process -

i.e. it has not just occurred by chance• Help you make better predictions about your service and thus

improve decision making• Help you prove/disprove assumptions and trends about patient

services• Help drive improvement by monitoring the system – and used to test

the stability of a process prior to redesign work, such as Demand and Capacity

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SPC is great, but…It will not:

• Solve your process issues – you will need background intelligence in order to understand the process for potential redesign

• Provide all the answers – SPC analysis is a tool to compliment all other methodologies i.e. process mapping and discovery interviews

• Validate data – SPC is only as valid as the data used• Define operational definitions when collecting data –

this in itself can introduce more variation i.e. ‘measure my left arm’

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Unacceptable decision-making

We need to challenge:

• guesswork - single figure decision making• decisions based on special cause variation• anecdotal data • “known” solutions or assumptions• arbitrary targets – national and local – is the process

really capable of achieving the target?

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Remember…Variation is the key to redesign

Variation exists in all processes around us:- Every patient’s needs are different- Similar patient pathways are normally very different

in each hospital- The way we measure the same things can also be

very different

“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”

Deming

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Variation in a system is normal

• The variation is caused by factors that are inherent in the system over time

• They affect all outcomes

• This is ‘common cause’ variation

• The causes are ‘unassignable’

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Some variation may not be normal

• The factors are not present in the process all the time

• They do not affect everybody

• They arise because of specific circumstances

• This is ‘special’ or ‘assignable’ cause variation.

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Two types of variation

Natural (common cause) variation• Is inherent in the design of the process• Results in a stable – IN CONTROL – process because the

variation is predictable• Is due to random or chance causes of variation

Special cause variation• Is due to irregular or unnatural causes that are not inherent in a

process – i.e. extrinsic• Results in an unstable – OUT OF CONTROL – process

because variation is not predictable• Is due to non-random or assignable causes of variation (i.e. a

signal that the process has ‘changed’)

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Special Cause Variation

• These are flags that tell you something is not right with the system…they need further investigation

• They are usually attributed to bottlenecks or unusual events – but may also be a signal that the service has been changed through redesign!

• They need to be eliminated from the process (where they can be) before the system is changed

• Changing a system that has special cause variation can actually make it worse

• You are striving for a system that displays only common cause variation

• And then reducing that variation to increase the flow, efficiency and predictability

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Natural (common cause) variation - a stable process in control

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F M A M J J A S O N D J F M A M J J A S O N D

Upper process limit

Mean

Lower process

limit

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Special cause variation- an unstable process out of control

0102030405060708090

F M A M J J A S O N D J F M A M J J A S O N D

Upper process limit

Mean

Lower process

limit

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Consecutive trips

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Mean

Upper Process Limit

Lower Process Limit

Accident on motorway - Special Cause

Tyre had puncture – Special Cause

Borrowed helicopter – Special Cause

Stopped by police for speeding – Special Cause

School holidays – Special Cause

COMMON CAUSE VARIATION - Points within the yellow lines is variation you would expect - normal variation of the process (my trip to work) E.G. traffic lights, pedestrians, rush hour

My trip to work…

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Management of variationIs the initial process stable?

Type of variation Natural (common) Special + natural

Right Choice Change the process

Investigate the origin of the special

cause(s)

Wrong Choice Treat normal variation as a special

cause (tampering)

Change the process

Consequences of making the wrong

choice

Increased variation

Wasted resources

Yes No

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In Summary…

Process unclear

Create an SPC chart

Is process stable and ‘IN CONTROL’?

If YES – Reduce Variation by redesign

If, NO – Identify special causes and restart

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Why not just use averages?

‘If I stick my right foot in a bucket of boiling water and my left foot in a bucket of ice water, on average, I’d feel pretty comfortable.’

Davis Balestracci

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• Pause for questions

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Rules for special causes RULE 1 Any point outside one of the control limits

RULE 2 A run of seven points all above or all below the centre line, or all increasing or all decreasing.

RULE 3 Any unusual pattern or trends within the control limits.

RULE 4 The number of points within the middle third ofthe region between the control limits differs markedly from two-thirds of the total number of points.

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Rules for special causes RULE 1 Any point outside one of the control limits

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MEAN

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Point above UCL

Point below LCL

SPECIAL CAUSES - RULE 1

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Rules for special causes

RULE 2 A run of seven points all above or all below the centre line, or all increasing or all decreasing.

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MEAN MEAN

Seven points above centre line

SPECIAL CAUSES - RULE 2

LCL

UCL

LCL

UCL

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Seven points below centre line

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MEAN MEAN

Seven points in a upward direction

SPECIAL CAUSES - RULE 2

LCL

UCL

LCL

UCL

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Seven points in an downward direction

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Rules for special causes

RULE 3 Any unusual pattern or trends within the control limits.

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SPECIAL CAUSES - RULE 3

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Cyclic pattern

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Trend pattern

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Rules for special causes

RULE 4 The number of points within the middle third ofthe region between the control limits differs markedly from two-thirds of the total number of points.

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SPECIAL CAUSES - RULE 4Considerably less than 2/3 of all the points fall in this zone

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UCL

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Considerably more than 2/3 of all the points fall in this zone

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http://www.7daysat.nhs.uk

How to access the SPC charts on the 7DSAT

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05/01/2023

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05/01/2023