Meet the team: AQuA Flow
System Improvement Lead
NHS England & Improvement
- England - Greater Manchester
- England - North East and North Cumbria
- England - North West Coast
- England - Yorkshire and Humber
Director of Transformation and Delivery
Bury Local Care Organisation
- England - Greater Manchester
- Bernie O'Hare
- Scott Gregory
- Paul Greenwood
- Wendy Bell
- Carl O'Loughlin
Discussions with our membership led to the Advancing Quality Alliance (AQuA) identifying that poor flow across and within care systems was a major concern. Consequently in 2016, we began to explore how we could support organisations to understand flow in more detail and design an offer of support. Over 18 months the flow team at AQuA analysed and reviewed worldwide research, evidence and experience of trying to improve ‘patient flow’. Our findings are summarised in “The Challenge and Potential of Whole System Flow”, a report that was co-authored with The Health Foundation.
These ideas were developed over the 1st year including discussions at a series of workshops with AQuA members and partners. A definition of whole system flow was coproduced with members and partners and this shared definition will be the basis for future work and discussions: “The coordination of all resources across a locality to deliver effective, efficient, person-centred care in the right setting at the right time.”
Our 1st year discovery programme identified common themes, both challenges and opportunities for understanding and improving flow within care systems:
• Culture and system leadership
• Financial structures and contracting
• Capability and capacity to apply new learning and approaches
• The use and availability of information across systems
We used these themes to develop a model and supporting framework. AQuA tested this within the current NHS and Social Care context with 3 North West systems. Our model, in the image provided, shows the 4 key lines of enquiry “The 4 Arrows” that evolved over the early part of the programme as we learnt that to not intentionally explore and understand each element within a care system would prevent the generation of a shared system view of the current state.
By understanding these 4 elements of the system and their interdependencies: Risk, Leadership and Culture we were able to analyse the system comprehensively allowing us to develop the full picture before designing improvements.
We have used the Design Councils ‘Double Diamond’2 and Kreindler’s “6 Ways Not To Improve Flow” in order to develop a new model for testing within the diagnostic phase. This allowed us to remain focussed to understand the right problem we were trying to fix and not jump to solutions.
The diagnostic phase of the programme is crucial to understanding the local context and system challenges. The overarching aims for the diagnostic phase are listed below:
1. Make the system visible to itself and develop a shared purpose.
2. Create an environment for discussion and engagement across traditional professional or organisational boundaries.
3. Map the current state
4. Understand queues and waits
5. Ensure the lived experience perspective is sought and involved equally
6. Identify an optimal pathway for design and measures of success.
We identified key success measures including integrated system leadership ; understanding of organisational and system culture(s) and empowerment of staff and patients to work together on improving their care system.
The design phase of the programme has now been started with an improvement group comprising of staff different areas across the systems. This group will be using all of the information and analysis gathered during the diagnostic phase, and following the Model for Improvement to design PDSA cycles that would lead to system improvement.
These PDSA cycles will all have individual aims and a range of measures to ensure we can monitor improvement. Staff will be provided with ‘just in time’ QI and data analysis training to support this.
Simulation and modelling software will be used where possible. This software uses historic data to help test our assumptions and predict outcomes. This ensures we are implementing changes that we are confident will bring about improvement.
We are currently recruiting 5 new systems to consolidate our learning from the discovery phase and we continue to work on the design of the design phase with the original 3 systems.
We presented this work at the International Conference on Integrated Care (ICIC) on 23rd and 24th May this year and both the 4 arrows model and the impact of our approach to co-design with our Lived Experience colleagues was very well received. It would be great to have the evaluation to underpin this and bring to this conference next year.
The nature of this programme work means that we as improvement practitioners are very close to the teams and the work. We would appreciate and benefit from the objectivity and rigour of external evaluation on these key areas:
- Consolidation of the learning from the diagnostic phase- can we evaluate the model and the interdependencies within the phase?
- As we design the implementation phase with the 3 Discovery systems, will we see delivery of impact within the system as a direct result of our work?
- What has been the measurable impact of co-designing and delivering the programme with AQuA’s Lived Experience Panel and service users within the chosen systems?
How you can contribute
- We have used Lean principles - any support from the SIG would be great.
- Any learning that can be shared about applying QI to whole systems, including the problem identification process, would be really helpful.
Diagnostic Report for Health Foundation (PDF, 1MB)
This is a great project because…
It's good to see investment in evaluation. Improving flow across systems is key to many of the big challenges facing health and care and this should generate useful learning for the community.
By the time of the event we encourage the project team to think more about…
How to establish links with others working on flow and with the Q community - this might help inform what's going to be most useful to others and increase the chance the insight is used widely.