The iCARE team delivers customisable reports and dashboards that present patient-level data to the healthcare professionals and administrators, enabling informed decision-making and improved patients’ outcomes.
Furthermore, our Translational Analytics facilitates real-time data feeds and the integration of quality, safety, experience, and effectiveness datasets. This supports the translation of research findings into clinical practice. For example, the ongoing insightFALLS work we are doing with ICHT described below showcases the importance of Clinical Decision Support:
Hospital falls are the most common reported incident, costing the NHS £1.5 million daily. Acute trusts lack effective information systems for actionable insights on falls prevention. This project aims to develop a semi-automated, near-realtime informatics platform, combining healthcare and data science expertise. The platform will reduce time spent manually reviewing falls documentation and enable teams to respond to fall trends. A co-produced case study video will highlight underserved patients to address inequities in falls prevention
Examples
Every day the NHS spends around £6 million on falls; falls occurring in hospitals account for 25% of this expenditure. The human cost of falls ranges from distress and loss of confidence to head injuries, bone fractures, and even death. Our research will use routine data from electronic patient records and incident reporting systems to better understand why patients fall in hospitals, with a particular emphasis on under-represented groups (e.g. patients with English as a second language). We will develop and evaluate an integrated informatics platform that applies Natural Language Processing to falls documentation to provide semi-automated, near-real-time reports to Imperial College Healthcare NHS Trust for coordinated safety monitoring and improvement.
Ovarian cancer is a devastating disease with most patients presenting at an advanced, incurable stage. There is a wealth of data held across NHS systems that could help improve outcomes for such patients but it is often written in clinical notes across the electronic health record, and not held in a single location. This makes finding all the relevant information quickly challenging, with the potential for some aspects to be missed.
Our team of healthcare professionals, researchers, and data scientists have built a new system using advanced text analysis called natural language processing bringing important and relevant clinical facts together into a single location such that it can be easily accessed by the multi-disciplinary cancer team. We are now evaluating the impact of the system on delivering benefits for patients and their outcomes, improving data quality, and saving money through improved processes and time savings.
Contact us
For general enquiries email: imperial.dcs@nhs.net
For data access enquiries email: imperial.dataaccessrequest@nhs.net
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