Dr. Chris Tackaberry, CEO of health tech AI pioneers Clinithink, discusses the NHS problem and the significance of Diabetes Week, which runs from June 12 to June 18.
Diabetes causes around 180 amputations, 590 heart attacks, and 2,300 episodes of heart failure per week. The financial burden on the NHS is staggering. Diabetes costs health care more than £10 billion each year, or more than £25,000 every minute, or 10% of its overall budget.
Diabetes affects about 5 million individuals in the United Kingdom, and millions more are at risk of getting the illness due to the rising frequency of risk factors such as obesity and physical inactivity. Diabetes is a life-altering disease that puts sufferers at risk of major health problems such as kidney failure, stroke, amputation, and blindness.
Early detection and treatment can control the disease and perhaps put it into remission. However, it is believed that over 850,000 individuals in the UK are living unknowingly with type 2 diabetes, the most common form of the condition, leaving them without access to critical medical treatment and assistance and putting them at danger of catastrophic health complications.
Furthermore, even people who have a diagnosis are frequently ignorant of danger signs, such as a lack of feeling, that might indicate a serious problem, and hence do not change their behaviors or seek medical assistance when necessary.
Technology that will change your life
Diabetes-related health issues are mostly avoidable via disease management – regulating blood sugar levels, blood pressure, and cholesterol – and a growing number of diabetics are turning to technology to help them do so.
Diabetes technology ranges from smart insulin pens that automatically record when and how much insulin a person injects to continuous glucose monitors that allow patients to check their blood sugar levels without extracting blood. Diabetes patients can use an increasing variety of applications and smart technologies to monitor their weight, food consumption, and physical activity in order to better manage the illness.
Locating a needle in a haystack
Technology is also being employed to aid in the early detection of diabetic problems in individuals. Diabetic foot disease (DFD), for example, is a frequent health condition that affects around 15-20% of diabetes patients and can lead to amputation if not treated early and carefully. Concerningly, a considerable percentage of persons in the UK have undiagnosed DFD. Without an early diagnosis, the disorder has the potential to harm patient health outcomes and raise the load on the NHS at a time when the service is already under enormous strain.
The issue is that the vital healthcare data required to assist physicians in determining if a patient has DFD – or is in danger of getting the illness – is hidden away inside thick, unstructured medical data that is not computable by standard methods and hence goes unanalyzed.
So, how might technology assist in resolving this data challenge? AI-driven data analysis technologies, on the other hand, can now analyze and understand medical information, including unstructured data, with unprecedented speed and precision, identifying susceptible groups of patients at risk of DFD.
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The technology has already been used at Barts Health NHS Trust, one of the largest NHS trusts in the UK, which creates millions of papers a year providing critical patient insights but lacks the clinical time to study them all. Barts Health was able to detect 350% more at-risk patients by using AI than prior approaches permitted. This allows treatments, such as an urgent referral to a podiatrist or vascular surgeon, to take place while a patient is still in the hospital, lowering the risk of amputation or other significant health concerns and saving the trust valuable clinical time.
Diabetic retinopathy is another serious problem that, if left untreated, can result in blindness. Recent research published in Nature Medicine by DeepMind (now Google Health) and Moorfields Eye Hospital demonstrated the ability of AI to accurately identify Age-related macular degeneration (AMD) from retinal scans, demonstrating that AI can also be used to improve diagnostic speed and accuracy for diabetic retinopathy.
In type 2 diabetes, a low-carb breakfast reduces glucose increases.
A rising public health crisis
Type 2 diabetes cases are increasing as the number of overweight or obese persons in the UK increases. As we approach this year’s Diabetes Week, a UK-wide initiative to raise awareness of the disease and increase funding for future research, it’s critical that we communicate the critical need for more NHS organizations to investigate the benefits of implementing AI technologies to accelerate the diabetes diagnosis pathway.
Using artificial intelligence to identify patients with diabetic problems or at risk of developing complications is critical for the NHS to address this increasing health concern before it becomes an emergency.
