From the two million health records it scanned, Optimise identified over 400,000 people at high risk for serious conditions such as heart failure, stroke, and diabetes. This group represented 74% of patients who ultimately died from heart-related complications, underscoring the critical need for early detection and timely medical intervention. In a pilot study involving 82 high-risk patients, the AI found that one in five individuals had undiagnosed moderate to high-risk chronic kidney disease.
Moreover, more than half of the patients with high blood pressure were prescribed new medications to better manage their risk of heart problems.
Dr. Ramesh Nadarajah, a health data research fellow from the University of Leeds, noted that deaths related to heart conditions are often caused by a constellation of factors. According to him, Optimise leverages readily available data to generate insights that could assist healthcare professionals in delivering more effective and timely care to their patients. Early intervention is often more cost-effective than treating advanced diseases, making the use of AI a valuable tool for both improving patient outcomes and optimizing healthcare resources.
The study’s findings suggest that using AI in this way could allow doctors to treat patients earlier, potentially reducing the strain on the NHS. Researchers plan to carry out a larger clinical trial to further test the system’s capabilities. The results were presented at the European Society of Cardiology Congress in London. It was pointed out by Professor Bryan Williams that a quarter of all deaths in the UK are due to heart and circulatory diseases. This innovative study harnesses the power of evolving AI technology to detect a range of conditions that contribute to these diseases, offering a promising new direction in medical care.
