![]() ![]() ![]() This project will demonstrate the scalability of this approach across UCLH so genomics can be used to understand the aetiology and prognosis of diseases, drug discovery and electronic health record (EHR)-based clinical trials.ĬRIU will support data integration from AboutMe multi-omic, clinical phenotype and imaging outputs. For the first time, investigators will carry out genotyping or whole genome sequencing embedded in routine care with the potential to aid management of ‘clinically actionable’ common conditions, such as high blood pressure and diabetes, as well as creating a conduit to develop personalised medicine services across specialties. ![]() Combined with available structured data at CRIU, the models can be further refined to improve diagnostic accuracy.ĪboutMe investigators are currently working on a Demonstration Project to outline the logistics of embedding multi-omic research into routine clinical care for the Healthcare Informatics, Genomics/Omics, and Data Science (HIGODS) BRC Theme. Imaging data can be used, for example, to build predictive machine-learning models to support diagnosis or detect early signs of disease, such as breast cancer. These include radiography, CT, MRI and ultrasound scans and collected through systems such as XNAT, an open-source imaging informatics software. To answer UCLH’s requirements, CRIU has been developing capabilities for processing and analysing free text data, by adapting and extending the software components provided within the CogStack platform. Some of these components will be integrated with existing modules in Epic, such as NoteReader, as part of the MiADE project.ĬRIU has been further expanding its data sources with the integration of imaging datasets. This structured information can then be further used for data analytics, to improve clinical documentation and to assist in clinical trials recruitment. The application of natural language processing (NLP) algorithms to free text data, such as medical notes coming from Epic or previous legacy systems, can transform the data into structured information. Clinicians and researchers can use it to investigate hunches and explore trends, as well as enhance trial recruitment. SlicerDicer is a self-service data exploration tool within Epic hyperspace. The introduction of EHRS consolidated the move to digital maturity at UCLH. As part of the transition, Clarity and Caboodle, Epic's own "data warehouses" (large stores of data from many different sources) were chosen to be the main vehicle for operational and external reporting. In April 2019, UCLH introduced Epic, an integrated hospital-wide electronic health record system (EHRS). ![]()
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