JMIR Publications

ABSTRACT

Background:

As more healthcare organizations transition to using electronic health record (EHR) systems it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have systems capable of harnessing 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).

Objective:

We describe the deployment of the EHR interfacing information extraction and retrieval platform Cogstack at University College London Hospital (UCLH).

Methods:

At UCLH we have deployed the CogStack platform; an information retrieval platform with natural language processing capabilities. The platform addresses the problem of data ingestion and harmonization from multiple data sources using Apache Nifi module for managing complex data flows. The platform also facilitates the extraction of structured data from the free text records through use of the MedCAT natural language processing library. Finally data science tools are made available to support data scientists and /or development of downstream applications dependent upon Cogstack ingested and analyzed data.

Results:

The platform has been deployed at the hospital and in particular how it has facilitated a number of research and service evaluation projects. To date we have processed over 30 million records and the insights produced from CogStack have informed a number of clinical research use cases at the hospitals.

Conclusions:

The CogStack platform can be configured to handle the data ingestion and harmonization challenges faced by a hospital. More importantly the platform enables the hospital to unlock important clinical information from the unstructured portion of the record using NLP technology.