How Local Data Can Help Us Address Health Inequalities

• data for local policy

• Selin Zelili

This article forms part of our Data for Policy series. As part of IPPO and UCL’s Department of Information Studies’ Building Local Data Capabilities project, five Data for Policy Fellows are currently embedded in partner local government bodies across the United Kingdom and will write about their experiences and insights on the challenges of using data in policymaking.

Selin Zileli

Health inequalities are a persistent concern to local government bodies across the UK. To tackle this challenge, Rhondda Cynon Taf (RCT) Council is developing a data-driven approach to understand how local authorities can use data to make informed decisions that address these inequalities and improve public health outcomes.

Health inequalities play out in many ways, with factors such as the quality of air and water, housing, employment opportunities, access to education, social inclusion, food security, availability of green spaces, transport, and climate change, significantly shaping communities’ health needs and outcomes.

Health Determinants Research Collaboration in Rhondda Cynon Taf

Rhondda Cynon Taf (RCT) is one of the 30 local authorities participating in the National Institute for Health and Care Research (NIHR)’s Health Determinants Research Collaborations (HDRCs). These collaborations are funded to connect local governments with academia and empower local authorities with research capabilities that enable evidence-based decisions.

Historically known for its coal mining industry, RCT faces high levels of deprivation, economic inactivity, and a lack of opportunities for enhancing local qualifications. The COVID-19 pandemic exacerbated existing inequalities, highlighting issues such as poverty, overall life expectancy and limited physical activity, among others. In response, the RCT HDRC initiative, led by RCT and the Wales Centre for Public Policy (WCPP), seeks to enhance the evidence base for driving positive policy change within the region using data on local health determinants, including lower educational attainment, higher alcohol consumption and obesity levels, to address six priorities:

1. Social Welfare: Reducing child poverty and improving services for children and young people.   
2. Employment: Facilitating job opportunities and promoting better-paid employment. 
3. Housing: Increasing availability of quality and affordable homes and providing greater housing choices for residents 
4. Education: Improving pupils’ achievement, narrowing the attainment gap, and enhancing the early years system and childcare offer.  
5. Health and Wellbeing: Encouraging active lifestyles and promoting mental wellbeing.  
6. Community Development: Supporting voluntary, community and faith sectors to build active communities to meet local needs.

The initiative involves coordinating multiple teams to understand data-evidence relationships and the subsequent possible interventions. As part of the preliminary steps for this project, I am working with RCT to support the trajectory of the HDRC initiative by capturing insights and perspectives as part of my Data Policy Fellowship at the Department of Information Studies, which is part of the Building Local Capabilities co-led by Dr Bonnie Buyuklieva and Jeremy Williams from IPPO.

Exploring Prevention Services to Enhance Family Resilience

My collaboration with RCT explores one of the six priorities outlined by RCT HDRC, concentrating on prevention services. Prevention services refer to a range of support for families in RCT with needs greater than early intervention but not yet requiring statutory intervention. These services play an important role in bridging the gap between early intervention and more intensive care, aiming to provide timely support to prevent escalation to crisis levels. By providing support at the right time, these services significantly impact the wellbeing of families and communities. One example of such a service is Resilient Families Services, which offers support and tailored programs to help families navigate challenges and strengthen their ability to cope with future difficulties. My work involves mapping out existing processes, identifying gaps in existing evidence and enhancing these through research.

Local authorities often face challenges in managing the demand for acute services, highlighting the need to identify supportive measures and other prevention interventions. By examining demand, service usage, community and family demographics, and family needs, we can gain insights into patterns and trends to better prepare prevention service options. These insights can help us map and monitor potentially impactful interventions that address the specific needs of family groups and communities. 

The outcome of my research is twofold: first, to understand effective support for preventive families’ services and second, to build a broader understanding of the role of data in informing interventions. Using evidence-based policy and practice, our research aims to provide policymakers and practitioners with the framework for thinking about and applying targeted and impactful interventions through data-driven decision-making.

How to Integrate Data into Supporting Better Outcomes

One of the key challenges for this project is operationalising the implementation scope based on the broader HDRC plans. This includes understanding various stakeholders within RCT, the context-specific data-evidence relationships, and existing interventions. Engaging with stakeholders to refine the scope and identify insights for navigating the early stages of RCT HDRC has been successful. During these conversations, we have identified research priorities and the narrower focus area – prevention strategies – by discussing the most pressing health concerns and community needs. A subsequent challenge was differentiating between early intervention and prevention support within the broader context of children’s services. For example, Resilient Families Services are designed to meet the non-statutory care needs of children by focusing on needs identified through an Initial Assessment. This service sets goals and actions tailored to the family, providing quick support to build resilience. The service is available for all age groups and families with various needs, and it offers flexible intervention duration based on the family’s specific needs. The differentiation of early help and prevention support would be useful as it can allow for a more targeted and effective allocation of resources, ensuring families receive the most appropriate level of support. 

Although RCT has access to a wide range of data and reports, using this information effectively for decision-making remains a significant challenge, because it requires understanding the diverse data sources essential for informing the HDRC framework. This includes exploring the connection between the existing data repositories the council has access to and the evidence they generate for informing intervention strategies. Proactively identifying and tackling health challenges hinges on a comprehensive understanding of data utilisation: the available sources, the evidence they produce and the resulting interventions. 

After this initial step, we explored ways to optimise data utilisation and maximise its impact on intervention outcomes. The first step was to survey the types of data available and the evidence they generate, which informs the development of targeted intervention strategies. Additionally, we discussed the value of using data insights from socioeconomically similar areas to expand the current approaches and intervention targets in RCT. By conducting a literature review and analysing data-driven interventions from similar contexts, we can gain valuable insights to refine and expand the scope of HDRC RCT initiatives. This includes accessing relevant evaluations to adapt the interventions to local needs for knowledge-sharing and dissemination practices.

Initial Insights on the Use of Local Data for Policy

Initially, my approach was from a more analytical perspective, shaping my focus on assessing the existing data and understanding its types and qualities to identify any gaps. However, as the collaboration progressed, my perspective on data changed. I began to see data not just as a resource but as a tool to inform and be re-informed by interventions and decision-making. Identifying actionable interventions and tracing them back to their data origins can lead to active engagement with producing new information rather than just passive analysis. This iterative process between data and intervention leads to more informed decision-making, with interventions serving as valuable data sources. In a nutshell, it’s not only about data leading to interventions but also about interventions contributing to the data pool.

Selin Zileli is a Data for Policy Fellow at  UCL’s Department of Information Studies, working with Rhondda Cynon Taf (RCT) Council on addressing health inequalities to support RCT’s Health Determinants Research Collaboration (RCT HDRC).  Selin’s previous research includes crowdsourcing journey experiences, Rebooting Democracy and close the data gap. Her interdisciplinary work has focused on combining design and technology to develop data collection and experimentation tools that explore innovations for societal challenges.