Clinical coding automation using Natural Language Processing


30 Second Summary

The project aims to use Natural Language Processing (NLP) to automate the prediction of ICD-10 or OPCS-4 codes from doctor/patient notes, currently done manually. Initially focusing on 3-character ICD-10 chapters, it will eventually predict full 4-character codes. Collaborating with a provider, the project will streamline coding and improve accuracy.

Natural Language Processing (NLP)
Clinical Coding
NHS 10-year big bet: AI to drive productivity
NHS 10-year big bet: Data to Deliver Impact
Author
Affiliation

Sid Kumar

NHS South West London ICB

The aim of this project is to use Natural Language Processing (NLP) to predict ICD-10 or OPCS-4 codes from doctor/patient notes, automating a task currently done manually by the clinical coding team.

Initially, we’ll predict 3-character ICD-10 chapters, with the goal of eventually predicting full 4-character codes. Collaborating with a provider that has access to these notes, this project will streamline coding and improve accuracy.

Note10-year plan Alignment

“NHS 10-year big bet: AI to drive productivity”: using NLP to automate the prediction of ICD-10/OPCS-4 codes from clinical notes, a task currently performed manually, freeing up coding staff time and improving accuracy.

“NHS 10-year big bet: Data to Deliver Impact”: Enhancing held data with categories that can be used downstream for additional analysis or to support data products like machine learning algorithms