Publications

We have a number of papers currently being finalised, aiming to reflect on and share the lessons learned from the project

Jiang-Kells J, Brandreth J, Zhu L, Ross J, Jani Y, Costanza E et al. Design and implementation of a natural language processing system at the point of care: MiADE (Medical information AI Data Extractor). BMC Medical Informatics and Decision Making (under review). Pre-print available at: https://www.researchsquare.com/article/rs-4925228/v1

Abstract: Well-organised electronic health records (EHR) are essential for high quality patient care, but EHR user interfaces can be cumbersome for entry of structured information, resulting in the majority of information being in free text rather than a structured form. This makes it difficult to retrieve information for clinical purposes and limits the research potential of the data. Natural language processing (NLP) at the point of care has been suggested as a way of improving data quality and completeness, but there is little evidence as to its effectiveness. We sought to generate such evidence by developing an open source, modular, configurable NLP system called MiADE, which is designed to integrate with an EHR. This paper describes the design of MiADE and the deployment at University College London Hospitals (UCLH), and is intended to benefit those who may wish to develop or implement a similar system elsewhere.