Understanding location
This test provided a consistent method for mapping residents' postcodes and locations to NHS geographies.
Our aim is to consistently link postcodes to appropriate geography layers—GP Practice, PCN, ICB, Region, and local structures such as Neighbourhood, Locality, and Place. This enables us to analyse inequalities, deprivation, and service accessibility while supporting commissioning and delivery functions.
NHS geography operates from two distinct perspectives: where people live (residence path) and where they are registered (registration path). We model these as two parallel hierarchies, connected only by the NHS Number at patient level. This separation prevents confusion between population health analysis and service delivery analysis.
Creating a model for Ethnicity
In the LDP, we aim to represent Ethnicity as a hierarchical structure to enable aggregate-level population health analysis with ethnicity-linked data.
Instead of creating our own model, we are adopting an established one. We evaluated two existing models: ONS 2021 England & Wales Census Ethnic group classifications and NHS England Data Dictionary Ethnic Category Code 2001a. We compared them using these criteria:
- Coverage & granularity – detail level captured
- Interoperability and Integration – alignment with NHS standards and external compatibility
- Usability for Data Consumers – analyst-friendly design and clarity for public reporting
Height, Weight & BMI
In this test we aim to set a single, enforceable standard for height, weight, and BMI in the Somerset LDP so data from GP/PCN, Trusts, Councils, Hospices, Ambulance, and ICBs have comparable, reproducible, and safe data for PHM and inequalities analysis.
- Standardise inputs, codes, and storage using UK Core FHIR and SNOMED.
- Define selection rules for multiple measures and handling of missing or non-reproducible BMI.
- Enable analysis though common validation, provenance, and recency rules.