Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals

TL;DR

This paper describes the deployment of CogStack, an enhanced natural language processing platform, at a UK hospital to extract insights from unstructured electronic health records, supporting research and service improvement.

Contribution

It introduces an improved CogStack platform capable of processing legacy and current hospital records for healthcare data mining.

Findings

Processed over 18 million records

Enabled multiple clinical research use cases

Enhanced data ingestion and NLP tools

Abstract

As more healthcare organisations transition to using electronic health record (EHR) systems it is important for these organisations to maximise the secondary use of their data to support service improvement and clinical research. These organisations will find it challenging to have systems which can mine information from the unstructured data fields in the record (clinical notes, letters etc) and more practically have such systems interact with all of the hospitals data systems (legacy and current). To tackle this problem at University College London Hospitals, we have deployed an enhanced version of the CogStack platform; an information retrieval platform with natural language processing capabilities which we have configured to process the hospital's existing and legacy records. The platform has improved data ingestion capabilities as well as better tools for natural language processing. To date we have processed over 18 million records and the insights produced from CogStack have informed a number of clinical research use cases at the hospitals.