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Addressing health inequalities with data

Case study

Understanding our communities enables us to understand the factors that affect health outcomes.

Now we are one Trust, we are consolidating our datasets. Datasets include patient populations, service usage and outcomes. This allows us to paint a broader and more detailed picture of the needs of the population across the region.

With this enhanced dataset, we can identify patterns that were harder to see before the merge. This includes differences linked to:

  • geography
  • deprivation
  • ethnicity
  • age
  • disability
  • other relevant characteristics

By bringing teams together, we are bringing together our systems and processes. It allows teams to:

  • compare approaches
  • share learning
  • focus improvement where the evidence shows it is most needed

Consolidating our data improves how we link insights across clinical and operational services. We can combine clinical expertise, operational knowledge and engagement with local communities. Our future service improvements will use this deeper understanding of local needs.

Over time, this will help us to develop better services. By providing a baseline of evidence, we can address health inequalities and unwarranted differences in care. We will use the deeper understanding of local needs for future service improvements. Enabling services to be more consistent, accessible and responsive to local need.

For our patients and communities, this will ensure our care is is fair, accessible and responsive to their needs.

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