CEG researchers develop algorithm to study how health is impacted by where we live
Researchers from Queen Mary’s Clinical Effectiveness Group have developed an address-matching algorithm to link patient health records to geospatial information.
The algorithm, known as ASSIGN (AddreSS MatchInG to Unique Property Reference Numbers), allocates a Unique Property Reference Number (UPRN) to patient records. Every property in the UK already has a UPRN, which is allocated by local authorities and made nationally available by Ordnance Survey. This gives every address a standardised format that enables pseudonymised linkage to other sources of data.
As addresses are typically entered into patient records as free text, ASSIGN compares addresses in the NHS record with Ordnance Survey's 'Address Base Premium' UPRN database, one element at a time, and decides whether there is a match. The algorithm, developed in partnership with David Stables of Endeavour Health, mirrors human pattern recognition, so it allows for certain character swaps, spelling mistakes and abbreviations. It also includes patients’ past addresses, making it possible to study changes of address across the life span.
This innovative approach will enable accurate research into the effects of a person’s household and surroundings on their health. The research team are using the pseudonymised UPRNs to study:
- how the health of household members impacts childhood obesity
- whether overcrowded or multi-generational households are at greater risk from Covid-19
- how to support GPs to identify people living in care homes so they can provide more effective care.
The team have published an evaluation of the algorithm in the International Journal of Population Data Science. As ASSIGN is open source, it is hoped that it will be used by other researchers to link data and help inform policy decisions and improve population health across England.
Dr Gill Harper, UKRI Rutherford Innovation Fellow at Queen Mary, said: “Linking places to people is a core element of the UK government’s geospatial strategy. We’ve shown that ASSIGN is a highly accurate technique which enables linking health records to geospatial data. The algorithm will enable researchers across the country to conduct innovative studies into the effects of a person’s household, location and surroundings on their health.”
- Research paper: ‘Evaluation of the ASSIGN open-source deterministic address-matching algorithm for allocating Unique Property Reference Numbers to general practitioner-recorded patient addresses.’ Gill Harper, David Stables, Paul Simon, Zaheer Ahmed, Kelvin Smith, John Robson and Carol Dezateux. International Journal of Population Data Science.
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