Hospital Alerting Via Electronic Noticeboard (HAVEN)
In plain English
AI plain-English summaryEvery year, roughly 40,000 ward patients in UK hospitals deteriorate unnoticed until they need intensive care. A new hospital-wide surveillance system aims to spot these patients earlier by pulling together all the electronic data already collected on them—demographics, lab results, and vital signs—into a single, continuously updated risk score. Current early warning systems rely only on vital signs and often miss deterioration. The problem is that different types of patient data sit in separate digital silos, so clinicians cannot see the full picture. This project will mine the electronic records of patients who have already deteriorated to the point of ICU admission, using that data to build and validate algorithms that predict risk from all available information. The result will be a prototype system that ranks patients by risk, allowing clinical teams to quickly identify, review, and treat those most likely to decline. If the system cuts the number of ward patients reaching ICU by just 10 percent, nearly £40 million in ICU bed capacity would be freed up each year. More importantly, many of those patients would receive life-saving treatment before they ever reach that point. The research is applied, not fundamental—its success hinges on integrating existing data and presenting it in a way that supports real-time clinical decisions.
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