AI could help identify patients with high
- An AI system called Optimise analyzed health records of over two million people to identify high-risk patients.
- The study found that many patients had undiagnosed conditions or were not receiving necessary medications.
- The research aims to improve early treatment and reduce pressure on the NHS.
Researchers from the University of Leeds have developed an AI system named Optimise, which analyzed health records of over two million individuals to identify those at high risk for serious heart conditions. The study revealed that many patients had undiagnosed health issues or were not receiving appropriate medications to mitigate their risks. Among the analyzed records, more than 400,000 individuals were flagged as high risk for conditions such as heart failure, stroke, and diabetes, accounting for 74% of heart-related deaths. In a pilot study involving 82 high-risk patients, the AI identified that one in five had undiagnosed chronic kidney disease, while over half of those with high blood pressure were prescribed new medications to better manage their heart health. This proactive approach aims to enable healthcare professionals to intervene earlier, potentially preventing the progression of these conditions and reducing the burden on the NHS. Dr. Ramesh Nadarajah emphasized the importance of using readily available data to gain insights that can lead to timely patient care. The findings were presented at the European Society of Cardiology Congress in London, highlighting the potential of AI in transforming patient management strategies. Plans for a larger clinical trial are underway, with hopes that this research will not only benefit patients suffering from heart and circulatory diseases but also alleviate pressure on the NHS. The British Heart Foundation, which funded the study, underscored the significance of early diagnosis in reducing hospital admissions related to heart diseases.