In two case studies, we highlight examples of how care systems in the East of England overcame identified obstacles to improving the quality of their data that relate to health inequalities. The changes these systems introduced suggest that, despite known barriers to data quality improvement, practices such as data linkage and a team-wide focus on capturing ethnicity information can support anyone working in the health and care sector whose work deals with data to effectively combat health inequality — down to the individual level.
Prior to the covid-19 pandemic, the Suffolk and North East Essex (SNEE) Integrated Care System (ICS) initiated a PHM Strategy to link data across the local ICS population. This initiative involved members of the local health and care system across leadership, information governance and analytics workforces (Figure 1) [3]. The ICS’s aim is to reduce inequalities by involving members of the NHS, local authorities and the public to aid targeting interventions within the region, which has a population of approximately one million people.
A critical focus of the PHM plan was and continues to be improving completion of ethnicity data within any centralised dataset in the system. One specific project involved linking existing data across datasets using the currently accepted 16 ethnicity codes used within the NHS.
Working with a private healthcare consultancy focused on population health — Optum — the ICS linked data (such as demographic data, from multiple sources, such as Trusts and General Practitioner services) from across the region to develop models that allowed for the effective focus of analytics projects.
Read the full case study here.
