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The Royal College of Psychiatrists Improving the lives of people with mental illness

Spotlight on quality

Spotlight on quality

Last month the college’s Quality Improvement lead Amar Shah brought you the first of a series of QI case studies, which we hope will inspire ideas for quality improvement in your areas of work.

The first one focused on Durham and Darlington Child and Adolescent Mental Health Services Senior Management Team, which is part of Tees Esk and Wear Valleys NHS Trust.

This month, we’re looking at work done by the East London NHS Foundation Trust.


Case study: East London Memory Clinics

Memory Clinics have been set up around the UK in order to increase levels of diagnosis of dementia.

A Prime Minister’s challenge was set that each CCG area in the UK would achieve a diagnosis rate of 66% of the expected population and the two main performance indicators are that

  • first appointments happen within 6 weeks of referral and

  • diagnosis happens within 18 weeks of referral.

It is expected that this is achieved in 95% of all cases.

The three memory clinics in East London were achieving the Prime Minister’s Challenge, but performance against the 2 KPIs was slipping badly.


How did QI help?

The three memory clinics met with the QI team and the Deputy Director and through the use of QI tools including flow-charting, nominal group technique and affinity diagrams, the services identified a number of key themes:

  • Lack of central management

  • Lack of Admin process

  • High levels of inappropriate referrals (25% of all referrals coming from people under the age of 65)

A number of change ideas were implemented –

  • Weekly tracking of wait lists against the KPIs

  • 2 weekly meeting of Memory Clinic leads

  • Admin leadership enhanced

  • Better recording of “Do Not Attends”

  • Text messaging reminder service


Revealing clear areas to improve

The initial focus of the group had been on the inappropriate referrals cohort, but it quickly became clear that the key to addressing the issue was tracking the patient pathway and ensuring systems were robust.

The effect of the QI approach has meant that within 6 months, waiting times for referral to 1st appointment had dropped to below 6 weeks, and over 95% of patients are now receiving their diagnosis within 18 weeks. This was achieved despite a 30% increase in referrals during the same period.

In early discussions with the staff team, it became clear that there was a mismatch between how they were doing and how they believed they were doing.

The common belief was that they were working as hard and as fast as possible – that patients were getting seen, and that if further improvement was expected then extra staffing would be required.

However, frontline staff were unable to say how many patients were waiting to be seen and how long they were waiting.

We resolved this by making performance visible to all, through a weekly report that showed how many patients were waiting to be seen for a first appointment and for diagnosis, and what was the longest wait against these two measures.

It became clear that there was a lack of standardised process and we were able to identify patients who had slipped through the net. We resolved this by redeploying resource to create an administrative lead to monitor the admin processes.

Because admin staff were being accommodating to patient requests, there was often very long waits and multiple failed appointments.

Non-attendance was not getting recorded properly and consequently we were losing control of when to discharge patients who were disengaging from the process.

We implemented a robust non-attendance protocol that ensured only one further appointment was offered after two non-attendances, with discharge following three non-attendances.

In order to support service users and carers to be aware of upcoming appointments, we also introduced a text messaging reminder service.


‘Model for Improvement’

The entire work used the Model for Improvement as the quality improvement method, with a range of tools being used at different stages. Flow-charting, nominal group technique and affinity diagrams were utilised to understand the system, and involve the whole multidisciplinary team in developing change ideas.

PDSA cycles were used to test and then implement new ideas ie the text messaging reminder service was prototyped in Tower Hamlets, embedded into daily practice, monitored for a month, shown to have a substantial impact on “Did Not Attend” rates and then scaled up and spread to the other two Memory Clinics across East London.

Data was shared through a dashboard of measures, including the two key performance indicators. These were visualised as run charts, and over the course of the project, it is possible to show sustained improvement in waiting times.


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