Ai enabled managemement of patients at risk of diabetic foot ulcer
Diabetic foot ulcers (DFU) lead to approximately 150,000 amputations and €23 billion in costs in Europe each year. Of the
60 million diabetics in Europe , 1.5 million currently have a diabetic foot ulcer and 15 million will develop on at some point in
their life . Each ulcer takes 3-6 months to heal and costs upwards of €14,000 to treat, however, if hospitalisation or
amputation is required these costs can be as high as €100,000 . Diabetic foot ulcers pose a significant burden on healthcare
systems around the world. The NHS in England spends almost 1% of its entire annual budget (£1.13 billion) on the diabetic
foot. Almost all of these ulcers and amputations are preventable through early identification and proper care. Bluedrop
Medical are developing a remote monitoring system that uses computer vision and machine learning to predict and prevent
diabetic foot ulcers (DFUs). The home-based device, taking the form of a bathroom scales, performs a daily scan of the
patient’s feet. In 10 seconds, thermal and photographic data is collected and sent to the cloud. Advanced algorithms monitor
daily foot scans to detect DFUs before they develop, providing actionable alerts to both patient and healthcare provider. The
technique of temperature monitoring has been proven to prevent 70% of DFUs and Bluedrop Medical are building this
technique into an easy and quick to use device enabled by advanced sensor technology, computer vision algorithms and
machine learning. By preventing ulcers, the technology can prevent hundreds of thousands of amputations, improving lives
and saving healthcare systems millions of euro each year. Bluedrop Medical is targeting the highest risk patients who
currently have a 30-40% annual incidence of ulceration by preventing ulcers in this group a potential average saving of
€3,000 per patient can be achieve