Integrated Community Teams: a data-driven approach to moving the dial

In March 2024, Caroline Williams, Director of Adult Social Services (DASS), and Alex Robertson, Managing Partner, Consortium24 LLP, working with system partners, presented their data-driven approach to coordinated proactive and preventative care, to the International Technology Enabled Care Conference in Birmingham. This approach is currently being implemented in Warrington. Here, in a joint blog, Caroline and Alex detail how this approach is working so far.

Many systems are hindered by the lack of data consolidation and system interoperability, resulting in systemically late reactions to crises, wasted talent and increased pressure on staff, and ultimately, poorer outcomes for the most vulnerable members of the population.

In March 2024, working with system partners, we presented their data-driven approach to coordinated proactive and preventative care, to the International Technology Enabled Care Conference in Birmingham. This approach is currently being implemented in Warrington.

Warrington’s proactive and data-driven methodology focuses on the needs and wants of, and the intended outcomes for, the population. In this approach, care is “enabled by technology and driven by data.”

Using curated data, colleagues collaborate to intervene earlier when the patient’s risk of readmission is increasing. This approach is delivering a much-needed step change for the population and those who support them. Technology is a foundation for the care provided as the system works towards making the outcome of delivering the right support, in the right place, at the right time a reality.

What we did

We took a seven-step approach to our work together in Warrington:

Step 1

Develop a system-wide data privacy agreement, covering community and acute health providers, key voluntary, community and social enterprise (VCSE) partners, and Warrington Borough Council’s adult social care data sets, risk factors and patient caseloads. Without this, we would not have been able to create our aggregated, person-specific data set

Step 2

Identify a specific cohort of 1000 people at increased risk of potentially avoidable acute attendance and admission – specifically, those who had already attended urgent community response, the frailty assessment unit, or both

Step 3

Compare and contrast the aggregated data set to identify overlaps in caseload (often not visible to individual services), gaps in provision, and options to support more effectively to remain living well independently at home.

Step 4

Worked with those with lived experience, alongside health and social care professionals to challenge, validate, augment and enrich our understanding, with the data as the foundation blended with their insight to provide a full picture of wants and needs.

Step 5

Develop the eight fundamental frailty indicators (see below) informed by the data, which identified the eight key factors which, when they go wrong, can avoidably take away somebody’s independence.

Step 6

Trained 170 junior, middle and senior leaders in how to use this data-driven approach to make a fundamental shift away from individual service focus with the same people on multiple caseloads and waiting lists to a person-centred list based on their wants, needs and risk profile.

Step 7

Worked across locality community teams to work towards this fundamental change in mindset, approach, way of working, and deployment of talent to deliver the most benefit to the population we serve.

Introducing our eight fundamental frailty indicators

These indicators help in prioritising which members of the population require the most immediate early intervention. When one of these indicators goes wrong, it can result in a detrimental, and often very avoidable, impact on the patient.

Our eight fundamental indicators

home environment
hydration
memory
mobility
nutrition
medication
mental health and wellbeing
support network

Look for any indications of risk of losing independence.

These are the key things that when they go wrong, can avoidably take away someone's independence and increase the risk of avoidable admission.

Using the eight fundamental indicators we highlighted priority patients who required additional consideration in order to reduce the risk to current levels of independence.

Expanding our approach

Warrington: One system - one population - one purpose - one voice

Warrington’s data-driven approach to earlier intervention is underpinned by four foundations:

leadership and culture
data and evidence
workforce and training
enabling technology.

We begin with a simple single point of access: a ‘single front door’ to health and social care services. Regardless of how a patient contacts us, from different phone numbers, live chat, email, and so on, they all enter the system through the same ‘front door.’

Specialist colleagues take the time to understand the root cause of why this person may be reaching out, which isn’t necessarily based on which number they ring or even the first thing they say.

Getting to the bottom of why they’re calling in the very first conversation gives colleagues:

the opportunity to resolve the root cause immediately
a deeper understanding of their needs, ensuring that the most useful care is provided, and
knowledge of their preferences and wants, as a member of the public with escalated needs.

As we move forward through the model, the data from each contact is collected; from here, we proactively outbound contact those with the greatest needs, based on their risk of readmission. Earlier intervention can make a material difference to how likely they are to be readmitted and greatly reduces the risk of avoidable admissions.

This model can only function at its best when each health and social care community team are integrated, share a common caseload and their knowledge of patients’ history, especially those who may be receiving care from several different specialists.

The results of our test list show that early intervention provides the most vulnerable members of our population with an immediate benefit and gives them the best chance to retain their independence. Intervening earlier is only made possible by access to intersectoral data and emerging technology. The outcomes of this test implementation create a compelling case for a step change towards patient-centred outcomes, scalable across our whole population.

The fundamental aim of our approach is to work more collaboratively, to create the best outcomes for members of the population, so that they can continue to live well independently at home for longer.

By identifying gaps in services through integrating data sets and using this evidence to support integrated community team working, we can ensure that the care we provide is better administered based on skill, need, and priority.

What's next

To continue to provide the incredible care that we do, we must:

move towards a cohort-based way of thinking about our population based on the services they use
integrate our community teams to share our knowledge and talent most effectively. Implementing ICTs in turn joins up the data we have from health; social care; housing; technology-enabled care partners; the voluntary, community, and social enterprise sectors; and beyond. Sharing talent across sectors, and deploying it based on need and risk, ensures that it is a shared responsibility to maintain every vulnerable member of our population’s fundamental needs.

We can ensure that it is everybody’s business to act sooner, to continue to improve the outcomes for those we serve.