We can see variation everywhere: different cars, buildings, animals, people with different height and weight, and so on.
In healthcare we can see variation everywhere in processes, procedures, equipment, ward layouts, patient symptoms and outcomes.
When assessing the elective patient pathway, for example, there are many sources of variation and these can affect the flow of patients through healthcare systems. Much of the variation is caused by the way we organise and provide services
Understanding variation is critical to managing systems effectively. Understanding the source of variation is important as this determines what we should do next.
Natural variation is an inevitable feature of healthcare systems. Sources include:
- Differences in symptoms and diseases that patients present with
- The times of day that emergency patients arrive
- The socio-economic or demographic differences between patients
- Staff skills, motivation etc.
Artificial variation is created by the way the system is set up and managed. Sources relevant to reducing waiting times include:
- The way we schedule services
- The working hours of staff and how staff leave is planned
- The order in which we see and treat patients
- How much work we group and deal with in batches
- How we manage clinics to deal with priority or urgent cases.
Natural and artificial sources of variation are different from ‘common cause’ and ‘special cause’ variation. See Deming’s Profound Knowledge. Common cause describes variation that is predictable and expected. Special cause describes variation that is unusual or unexpected. Examples of special cause variation include a large-scale change creating a peak in demand, unexpected weather conditions and flu epidemics. On a small scale, an exceptionally obese or underweight child could trigger a ‘special cause event’ in a clinic due to possible social welfare concerns which would involve third parties.
There is a complementary tool, Statistical Process Control (SPC), which looks at variation using a statistical methodology to help you to identify predictable and unpredictable variation and know how to tackle both.
Linking natural and artificial sources of variation to the way variation behaves (ie whether we expect it or not) (source: NHSIQ)
Source of variation is natural
Patient’s age, gender, disease, condition, personal circumstances.
An exceptionally underweight child turns up at a health clinic triggering social welfare concerns. It’s the first time the clinic has seen this child.
Source of variation is artificial (comes from the systems we develop)
Some doctors make decisions weekly while others do this daily.
Ordering different tests for the same clinical presentation.
Different systems to manage consultant to consultant referrals from referrals from GPs.
Patients or tests being seen/dealt with out of turn.
A series of things ‘go wrong’:
Example of use: reducing delays
Reducing and managing variation are essential approaches to reducing delays in services. There are two reasons:
- Waiting lists build up because sometimes demand for work exceeds our capacity to do deal with our work. See Demand & Capacity. The mismatch is due to variation in both demand for work and variation in our capacity to deal with work. There’s a lot of evidence that suggests that our capacity to deal with work varies more than our demand
- Variation in the way we work and do work, such as the way we deal with paperwork, the timing of decision making along a clinical pathway, the decisions we make, how we organise and manage work, all impact the pace that patients progress and the number and length of unnecessary delays patients experience
This graph from NHSIQ illustrates the impact of both natural and artificial sources of variation on how long it takes individual patients to receive treatment after a referral.
The dotted black line is the average referral to treatment time. If you look at the chart there are a number of patients waiting longer than average waiting times due to the amount of variation. Looking at a chart like this, a natural question is to wonder “What is the cause of the variation?” and “What can I do about it?”