Assisting clinical decision-making with best-of-breed text analytics

CogStack is an information retrieval and extraction platform developed by researchers at the NIHR Maudsley Biomedical Research Centre.  It implements best-of-breed enterprise search, natural language processing, analytics and visualisation technologies to unlock the health record and assist in clinical decision making and research.

Electronic health record systems are often closed, proprietary and contain incomplete and unstructured data.  The result is that the wealth of information potentially available within health records is often inaccessible and underused.

CogStack implements new data mining techniques within NHS Trusts – specifically, the ability to search any clinical data source (unstructured and structured), and natural language processing (NLP) applications developed to automate information extraction of medical concepts.

These tools allow clinical text to be searched for specific terms using simple or complex syntax, rapidly retrieving the data needed to answer complex queries such as “has this patient received any high cost treatments that have not been captured in their discharge summary?” or “provide me with patients with early onset Parkinson’s disease”.

So far, over 9 million free text documents and over 250 million diagnostic results and reports have been processed within CogStack.  The speed at which queries can be developed and results returned and refined is very powerful, for example allowing clinical trials to find and recruit patients who would otherwise have been difficult to locate.

We are currently working with three NHS Foundation Trusts (South London and Maudsley, King’s College Hospital, and University College London Hospitals) to implement this platform, resulting in lasting improvements to recruitment, business intelligence and research capabilities.