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What is the challenge your project is going to address and how does it connect to your chosen theme?

People with ARDL have complex care pathways and multiple morbidities, such as CVD, cancer, drug abuse and Mental Health. The average age of death is 59 years. Those with worse outcomes live in deprived areas. ARDL can also have other effects in wider society including domestic violence, road traffic accidents, worklessness and social care issues. Those with ARDL are frequent users of hospital services including A&E, inpatient and outpatient services. There are over 300,000 alcohol related admissions in England (16/17). As the disease progresses, in-hospital stays become longer and longer until death.

Our project focuses on using routinely collected data to identify how services and improvements can be deployed to intervene appropriately earlier in the pathway for these patients. Using data and behaviour patterns will help us track back, finding outcome predictors earlier in individual pathways. This ability to interpret data will provide insights into where and how to make improvements.

What does your project aim to achieve?

To better understand what works well where and for who in this complex area needs analysis. Care pathways can be chaotic especially as disease progresses. We have methods of linking data sets identifying characteristics and features of people who go onto develop ARLD and identified hot-spots where admissions are more prevalent. We have mapped services onto our hot-spots and can work with neighbourhoods in the north west coast to identify what services are most effective for which patients. We developed some interactive tools which allow clinicians to focus on their patients, including hidden patients who present at hospital with other conditions, but which have alcohol as an underlying condition. This work will embed improvements across professions, using QI techniques with local hospital and community teams and understanding which interventions are needed in which area and how these can be delivered to reduce emergency unplanned care. Communities may be different in different areas.

How will the project be delivered?

We will work with the north west advancing quality programme (AQuA), University of Liverpool and clinical leads locally including public health (PH), hospital and primary care. We will develop a governance structure with key stakeholders, to ensure agreements and review progress. Staff to work on the project – a clinical lead (0.2wte); analyst (0.2wte) who will provide the analytics and generate the reports and report back to the teams on progress and QI  (0.4wte) who will engage with the consultants and community teams to review data and develop local approaches project manager (PM)(0.4) Firstly, we will work with Liverpool, Blackpool and Wirral to refine our approach and ensure data we provide is meaningful, understandable and actionable. Community teams and the Cheshire and Merseyside PH team (ChaMPs) will ensure that improvements that improvements are supported by Local Authorities. Our PM and QI lead will support us in embedding – making the project sustainable, with data & action

What and how is your project going to share learning throughout?

We will generate and share valuable learning in: supporting embedding of methods; analysis across several, routinely collected data sets; working with a variety of different teams and environments. We will: make available and embed data extraction methods (clinical code extraction); develop visualisation tools to make sense of complex data; disseminate results; work with AQuA to include learning for potential liver bundle work . We will present and provide information to Qs through the Q platform along with “how to” guides/toolkit to help Qs and others work with their local teams, including AHSN Network. Having already developed some techniques we will have lots to share early in the process. We will highlight this work at a national alcohol conference in November, where Qs can attend free of charge. We hope to input into national work to develop “liver care bundles”, this work would prepare the ground for teams to implement and measure the impact of these, when they are developed.

How you can contribute

  • Discussion of this work with the community who work in ARLD in hospitals/public health/community settings
  • We would like your comments on our data, visuals and approaches - as well as the development of our tool-kit in terms of what works best for you.
  • Support to ensure that we provide usable solutions, accessible by non-analysts and frontline clinicians.
  • Breadth of perspective and alternate viewpoints to improve accessibility of end products/methodologies
  • We would seek to use the Network to disseminate and highlight work in this important area.
  • We would like to promote values of inclusion to help highlight the challenges of this area for the health service, local authorities and others.

Plan timeline

1 Oct 2019 Project initiation document circulated
1 Oct 2019 Training programme agreed and rolled out
31 Oct 2019 Engagement and improvement teams established
29 Nov 2019 Methods and processes agreed in first 3 sites
1 Jan 2020 Reports delivered with analysis and improvement cycle starts
30 Apr 2020 Review of first improvement cycle - data with feedback
15 May 2020 Engagement with further sites (2nd Wave)
25 Jul 2020 Feedback on 2nd cycle (1st wave)
1 Sep 2020 Development of tool-kit
25 Sep 2020 Report on 1st Improvement Cycle (wave 2)
31 Dec 2020 Project close and reports

Comments

  1. Great to see this idea and to hear your very well thought through plans David. Is there any focus on ARLD from other AHSNs?

    Warm wishes

    Anna

    1. Guest

      Julia Reynolds 2 years, 4 months ago

      Hi Anna,

      I'm not sure if any other AHSNs have a focus on ARDL. I think that one (possibly UCL) did some work on liver stiffness. We had an alcohol theme a couple of years ago at the IA. This work has arisen from findings from a programme we are concluding this year called Connected Health Cities - linking data sets and looking across care pathways, which lends itself well to supporting QI and a real-world application.

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