The need
The organisation serves patients speaking more than 100 languages. Free-text recording made it hard to identify consistently who needed an interpreter or another adjustment.
What I did
I developed EMIS searches and a data-cleansing process to find information already recorded in notes, then supported structured language coding. A reception check-in template helped teams capture interpreter needs, digital access and reasonable adjustments as part of normal work.
What changed
The project added 8,355 language-specific interpreter codes. The number of patients with a recorded interpreter need increased from 9,961 to 12,086, giving teams a better basis for planning communication and access.
Recognition
I received the 2026 APNA NHS Exceptional Contribution award for Digital Innovation for Inclusion. The work also contributed to an EMIS NUG Rising Star finalist nomination.