diabetes

This blog is part of the Early Diagnosis campaign #BeFirst Early diagnosis and care can prevent illness from developing and slow disease progression. Lab tests, genetic tests, tests for chronic diseases and modern lab diagnostics can help facilitate earlier intervention and improves outcomes for patients and are increasingly valuable in informing treatment choice. Read the other blogs here: Why should we prevent cervical cancer? Because we can , A smarter way to fight colorectal cancer , Can screening decrease lung cancer mortality rates? , For kidney disease patients, treatment education and choice are key to better outcomes , Diagnosing severe hearing loss and deafness ****************************************** Chronic kidney disease is a major concern for healthcare providers worldwide. Tests that allow efficient and accurate diagnosis are vital. We all know someone living with chronic kidney disease (CKD) – even if they have not yet been diagnosed: it is estimated that 10 percent of the global population is affected by CKD 1 . Between 1990 and 2010, kidney disease became one of the fastest-growing causes of death in the world, second only to HIV/AIDS. 1 Reviewing the data on CKD diagnosis, we were struck by how timely detection can impact patient outcomes. Catching kidney disease in the early stages is a challenge, since there are typically no overt signs or symptoms. However, if CKD is detected early and managed appropriately, the deterioration in kidney function can be slowed and the risk of associated cardiovascular complications reduced. 2 For patients, this can make all the difference, but we know too that there is a real impact for health systems where demand is rising and resources may be scarce. CKD also represents more than €1 trillion in healthcare costs over the next decade. 3 Key indicators of kidney function So, what are the tell-tale signs...
I would like you to think about the evolution of healthcare in Europe and how it is organised. What are healthcare systems generally good at? Imagine a road accident. Frantic emergency phone calls. Flashing blue lights. Within 8 minutes emergency vehicles arrive. You hit the hospital accident and emergency ward. A crash team is ready. Doors are rushed through. Staff is scrambled, and lifesaving interventions happen. It’s an efficient and wondrous system we should all be proud of. Acute and chronic A road accident is an example of acute care. An intensive but (relatively) time-limited intervention. Over time, healthcare systems have got extremely good at delivering acute care, in many forms. But there is an emerging issue. Care for chronic conditions is far behind. Diabetes is one of the most pressing examples of a chronic condition. In a perfect world, a person living with diabetes would have complete and timely information about their condition. They would be able to effectively self-treat easily and, if needed, have support from doctors, nurses and nutritionists at any time, day or night. In a perfect world, the condition could be managed minute-by-minute, and the person would never need to see those blue flashing lights or the inside of a hospital. Perfection and reality We are far from that perfect world. Two challenges arise from our acute-care focused traditional model. Firstly, purchasing and resource allocation mainly happen in short-term cycles. Acute care tends to be resource-intensive but time-limited. Secondly, acute care tends to happen in highly siloed structures. Car crashes go to A&E. Heart problems go to cardiovascular. But what if healthcare systems faced a pressing condition that was long-term and could not be neatly siloed? This is exactly the issue with diabetes, a condition that often lasts decades and can cause complications in the...
According to the latest estimates of the WHO, 422 million people suffer from diabetes worldwide, and the number is growing steadily. As someone who is passionate about using eHealth to solve the biggest challenges in modern healthcare, diabetes stands out as one of the defining problems of our era. Managing diabetes well is essential to the wellbeing of millions of people, to the sustainability of our health systems, and to the long-term durability of our economies. The scale of the problem is immense but technology can help us rise to the challenge. Cognitive Artificial Intelligence (AI), facilitated by analytical predictive-diagnostics and revolutionary medical devices are transforming the way healthcare is delivered and managed throughout the world. Or, in other words, today’s computers can use patient data from multiple sources, including genomic sequencing and sensors, to diagnose disease, inform treatment decisions, and predict outcomes. It is my objective to bring the AI revolution to diabetes. When it comes to diabetes care, Machine Learning and Artificial Intelligence can collect information from various devices to create personalized programmes that support medication adherence and blood glucose management. At my company, we have developed a Digital Connected Health Platform™ that works with all diabetes devices. Our goal is to facilitate the analysis of data so that we can help patients stay healthy, avoiding the severe complications that can accompany advanced or uncontrolled diabetes. The insights provided by systems such as ours allow physicians to consistently intervene with patients on a real-time basis, paving the way for a more dynamic kind of disease management. It enables the use of wearables, sensors, devices and home health monitoring systems to transmit data from a patient to their care providers. The system also delivers reminders to patients, prompting them to check their blood glucose levels, take their medication or...
A new report on Laboratory Medicine in Poland highlights the role of laboratory diagnostics in the timely treatment of chronic conditions. Not only can investment in early diagnosis save and improve lives, it can also save money on long-term care. ‘There is not enough data on how health budgets are spent,’ says Jozef Jakubiec, Director General of IPDDL which compiled the report with Deloitte. ‘We wanted to show hard evidence to illustrate to decision-makers that that situation in Poland is considerably worse than in neighbouring countries, such as the Czech Republic.’ Take diabetes, for example. Serious complications from the advanced stages of the condition can include chronic kidney disease (CKD). This, in turn, may lead to a life-long dialysis or kidney transplantation – both of which come at a considerable personal and economic cost. Some people live with diabetes mellitus without symptoms for many years. Indeed, it may not be until complications arise that their condition is diagnosed. However, by that stage considerable damage may have been done. Even small changes in blood glucose can begin the process of degeneration of blood vessels. In order to intervene early and with the right treatment, glucose testing is essential. If Poland were to increase glucose testing by 25% a year, savings of PLN 0.5 billion (€0.12 billion) would be made within six years. For patients with diabetes-related conditions, the annual cost was estimated at PLN 5 (€1.17) in pre-diabetes compared to PLN 9,269 (€2,168) in diabetes with complications (an over 1800-fold difference). ‘The earlier the treatment is taken and monitored regularly, the more effective and less expensive it is,’ the report says. Prevention is cheaper than cure For CKD, it’s a similar story: the disease may remain asymptomatic until the last stage of renal failure. ‘There’s a big shift towards CKD because...
Authors: this article was written by Hans Martens, Martha Emneus , Anders Green and Camilla Sortso . This is the first blog of the series presenting the economic value of being in good health and the broader consideration of cost of disease. Europe’s health systems are struggling to maintain sustainability. One of the major challenges is the exponential increase in the prevalence of chronic diseases and the number of patients in advanced and costly disease stages. A challenge, which is predicted to only increase in the years to come. Chronic diseases make high demands on health systems for continuous, quality care. For patients, chronic diseases are associated with shorter lifetime, reduced quality of life and economic as well as socio-economic burdens on the patients, their caregivers - formal or informal. For society, the burden is excess healthcare, pharmaceuticals, nursing, reduced labour market participation and ability to be socially and economically active and premature mortality. Altogether these costs underpin the major challenge of chronic diseases for our societies – not least in Europe where health is a collective rather than an individualised responsibility. This challenge must be dealt with by the health systems and perhaps by reconsidering where investments should be made in the future as with many of the chronical diseases onset and progression can be prevented if diagnosed early and precisely and if the process is well managed. Among chronic diseases, diabetes mellitus is one of the most burdensome with app. 371 million people diagnosed globally and evidence of rapidly increasing prevalence. In a recent study from Denmark it was estimated that costs of diabetes amounted to 14,349 Euro per person year. Of these, health care costs accounted 17% and pharmaceuticals 4%, while for example loss of productivity amounted to 42%. And this is not the whole story, because...
Consider this: about 60 million people in Europe have diabetes. Out of those who have it for more than 20 years, 75% will develop some form of diabetic retinopathy (DR). It’s a startling statistic. Early detection of DR can prevent blindness, which is why people with diabetes should be tested every year. But because so many people have diabetes – and the numbers are rising – screening everyone for this debilitating eye disease is a huge challenge. For one thing, we do not have enough ophthalmologists to check the millions of eyes at risk of DR. And even if we did, the cost would be significant. New approaches are urgently needed. Fortunately, there is a solution on the horizon. By combining sophisticated cameras with artificial intelligence (AI), we can make diabetic retinopathy screening more efficient and cheaper – helping to deal with the growing demand for this crucial service. ‘Deep learning’ is a powerful kind of AI that can detect specific features in an image of the eye with high sensitivity. It allows health professionals to diagnose the stages of retinopathy in milliseconds. At DreamUp Vision, we are using this technology as a SaaS platform, as well as integrating it into a fundus camera – the kind of camera that ophthalmologists use to scan the eye. The technology is so flexible that any healthcare professional could scan a patient’s eye and get an immediate answer if the patient has signs of the disease or not. This could go a long way to addressing the shortage of ophthalmologists, while bringing expert care to people who do not live near specialist health centres. Learn by doing The incredible thing about this kind of AI is that it learns : the more eye scans it sees, the more accurate it becomes. We are...