Health resources worldwide are becoming increasingly strained as the burden of chronic diseases continues to grow alongside a rapidly aging population. With doctors in short supply, we need to look to digital technologies for a sustainable future for healthcare.
Kristian Hart-Hansen, CEO, LEO Innovation Lab
Rapid innovation is catalysing more efficient and scalable solutions to take on global healthcare challenges. The true potential of emerging technologies remains to be seen as they struggle to be implemented into our health systems. Meanwhile, traditional healthcare is growing increasingly unsustainable. We have to ask ourselves: What do we do when the system fails because there aren’t enough doctors to help us when we’re most vulnerable?
Is there a doctor in the house?
One of the UN’s sustainable development goals is centred around good health with the mission to ensure healthy lives and promote well-being for all at all ages.
A major roadblock for this goal is the growing shortage of healthcare workers, predicted by the World Health Organisation to reach 13 million by 2035. There simply aren’t enough doctors in the world. As a consequence, healthcare professionals work under extreme pressure, and access to ongoing clinical support is waning.
Many countries already feel the tension. In the UK, general practitioners see more than 41 patients a day on average, a survey revealed. 1 in 10 reported dealing with as many as 60 patients with the safe limit being 30. Combined with an average working day that comprises a staggering 11 hours, it comes as no surprise that more than half believe they’re working beyond safe levels. Psychological burnout is another consequence. 27% of doctors and medical students have received a psychiatric diagnosis. One in three has admitted to resorting to alcohol, drugs, or self-prescribing to get through their shifts.
Meanwhile on the patient side, the burden of chronic diseases continues to grow alongside an aging population, and a rise in health costs.
One in three adults worldwide is living with multiple chronic conditions.
In 2015, 12.3% of the global population were aged 60 years and over, which will increase to 21.3% by 2050. In other words, we’re getting older – and more costly. The average 65-year-old costs the National Health Service in the UK 2.5 times more than the average 30-year-old. An 85-year-old costs more than five times as much.
As a consequence, our health systems won’t be able to keep up with the traditional model of healthcare. We need to rethink disease management to maintain a sustainable healthcare model with more efficient and scalable solutions.
We need digital technologies.
Fortunately, we’re now seeing a rapid development in healthtech. Patients can now manage their health through digital platforms or consult their doctor online. There’s a growing potential for artificial intelligence to support doctors with AI-powered diagnosis and precision medicine.
There are three core areas where healthtech could do some heavy lifting for a more sustainable future for healthcare. They include triaging patients, providing new pathways for more equal care, and improving the quality of health services.
Triage: Your smartphone is ready to see you
First of all, AI can assist in triaging patients by providing an initial assessment of a patient’s condition, needs, and level of urgency. Today, when a patient goes to see a doctor, they often arrive as a blank slate. Your doctor has to gather information and make decisions relating to your symptoms, diagnosis, treatment, and whether there’s a need for a referral – all within a matter of minutes. In fact, primary care consultations last less than five minutes for half of the world’s population.
With so little time to spare, how do we optimise the consultation and free up resources?
If we put healthtech to work, in the future patients could be triaged from the comfort of their home. AI-powered health platforms can deliver a preliminary diagnosis and suggested treatment based on an analysis of your own data, which you can bring to your primary care physician. In textbook cases, treatment can be initiated with minimal involvement from a doctor. This leaves more time to focus on other patient needs.
The app Ada is a step in this direction. Combining medical knowledge with intelligent technology, it provides users with a preliminary assessment through a series of questions relating to symptoms, medical history, etc. Ada then suggests what you should do next – whether it be a trip to the pharmacy, a consultation with a specialist, or a day under the covers.
Equality: New digital pathways for clinical support
Equality should be a cornerstone of a sustainable healthcare model. We want everybody to be able to get the help they need regardless of income or location.
By introducing AI and digital platforms to the patient journey, we can generate new, diverse pathways in disease management thereby promoting equality in healthcare. Equality shouldn’t entail that everybody is treated the same way but that everybody has access to the support they need. For some, it’s the traditional, physical patient-doctor interaction. For others, it might be an app, a video consultation, or an online programme. What they all have in common is that the health services serve the individual. As a result, we can free up resources for doctors to not only focus on the patients who truly need a physical consultation but also to have a more effective consultation to address the overall well-being of the patient.
Millennials and Generation Z, in particular, have taken on a more active role in tracking and managing their health by means of smartphone apps and wearables. They’re digital natives and used to the instant accessibility facilitated by the digital transformation. They expect the same from their health services. For many, booking a physical consultation sometime in the future can be an unnecessary inconvenience if the issue could be handled virtually – especially in regions where doctors and specialists are in short supply, and patients have to travel far for a consultation within a reasonable timeframe.
Quality: The doctor is ready to see you – in 18 months
Emerging technologies can improve the quality of our health services through better diagnostic accuracy, individualised treatments, and more effective disease management.
This need is particularly evident in dermatology. 1 in 4 will develop a skin condition over the course of their lives, but patients are often trapped in long waiting periods to see a specialist.
In the UK, there are only 650 consultant dermatologists, many of whom work part time. With a population of more than 66 million, that’s about one dermatologist per 100.000 people. If we travel further West, the waiting time to see a dermatologist can be as long as 18 months in certain parts of Canada. Now head due South to the US where the waiting time for dermatology services have increased by 46% from 2009 to 2017. Patients now wait an average of 32.2 days to receive an appointment. As a consequence, 54% of patients experience fear or anxiety because of the waiting time, and between 2005 and 2011, there was a 17% increase in the number of hospitalisations for skin infections.
For many, the first point of contact is a general practitioner. With the existence of more than 3000 different skin conditions, it’s understandable that GPs misdiagnose skin conditions in up to half the cases.
For this reason, we’ve made it our mission at LEO Innovation Lab to leverage AI to improve the quality of care for patients with skin conditions. This includes combining skin tracking, progression monitoring, and diagnosis in digital platforms. One of our core strategies is to develop the capability for AI-powered skin diagnosis, available through a smartphone. We currently identify certain diseases at the same level as clinical experts, including psoriasis with an accuracy of 91%, and dermatitis with an 84% accuracy.
We also put the benefits of digital health tools to the test at a study in Hamburg where 37 general practitioners were exposed to 31 patients with different skin diseases. With the aid of a digital clinical decision support system, the overall diagnostic accuracy was improved by 34%. Patients also reported that they better understood the information provided during the consultation.
This is only the beginning. In the future, AI can reveal insights into the progression of your disease, predict how it will evolve or when your next flare-up will be. It can also determine when you need a refill of your medication, and have it delivered to your doorstep – but artificial intelligence needs the right data to be able to do so.
We need to put health data to work
A prerequisite for realising the prospects of emerging health technologies is better use of data. Over the years, the amount of personal health data has exploded. According to IBM, we each generate one million gigabytes of health data throughout our lives, enough to fill 300 million books.
This growing body of data holds the key to new insights into public health, to facilitate precision medicine, and to accelerate new discoveries and development of treatments. By leveraging health data, we can not only provide patients with personalised treatments but also reduce the strain on public health systems by moving from sick care to healthcare. That is, to increasingly prevent rather than treat disease.
Unfortunately, the reality is that we have a lot of data but very little insight. The majority of these data never find their way into the healthcare system.
One of the reasons is a lack of digital readiness in a very conservative sector. In a recent global survey among psychiatrists, only 36% felt that the potential benefits of future artificial intelligence and machine learning would outweigh the possible risks in their field.
Another barrier is the reluctance to move forward due to fears relating to data (in)security, and that digital platforms will dehumanise healthcare, replacing it with cold tech.
First of all, data security has to be a top priority. It doesn’t mean locking data away but ensuring smart, safe, and sensible use of data. Secondly, healthcare is already increasingly dehumanised as the doctor’s time is stretched paper thin. We can’t produce an extra 13 million healthcare workers by 2035, but we can scale and amplify the knowledge of those we have. The goal isn’t to replace doctors but to augment them.
Healthcare is also a field rife with ethical challenges to take into account, with emerging technologies raising concerns over potential bias, the “black box” dilemma, and questions relating to privacy and responsibility. Far too often, the ethical debate turns into an either/or discussion. Do we want AI in healthcare? Instead, the focus should be how we adopt new healthtech solutions for the benefit of doctors, patients, and the system as a whole. I dare say it’s unethical if we don’t realise the potential of health technologies – especially in a sector in need of precision and high levels of accuracy while specialists are in short supply.
Countries like China and the US are already moving full speed ahead with heavy investments in artificial intelligence. Meanwhile, Europe is lagging behind.
How can we start integrating digital technology into health systems?
We need to speed up if we want to set the direction for how AI is going to shape our future in the EU – otherwise, others will do it for us. Fortunately, we’re starting to see movements in the right direction. In December last year, the European Commission put forward an European AI strategy, followed by ethical guidelines for trustworthy AI.
We need a political framework to encourage innovation, allowing digital solutions to be tested iteratively. A driving force behind new technologies is the start-up community. They need more transparency on the regulatory barriers surrounding healthcare to avoid spending a lot of time and resources only to realise they can’t get approval for their product.
We need to promote the collaboration between public and private partners for maximum impact. This is to combine insights into the needs and workflow of public healthcare with tech competencies from startups and private actors to develop solutions tailored to our health systems. In Copenhagen, for example, the public emergency services have teamed up with the private company Corti. Using machine learning and sound-recognition software, they’ve developed a solution to detect if a cardiac arrest is in progress from the voice and background noises of an emergency call.
Digital technology and artificial intelligence can become the foundation of sustainable healthcare in the future – if we’re willing to pave the way for it.