Wherever we look in the healthcare industry, we can find new technology being used to fight illness, develop new vaccines and medicines, and help people to live healthier lives.
Over the last two years, many tech companies have focused on applying their expertise to solve problems caused by the global pandemic. At the same time, many healthcare companies that would not necessarily have traditionally been considered tech companies have turned their attention to technology and its potential to transform the delivery of their products and services.
It's clear that the pandemic has accelerated the digitization of the healthcare industry. According to the HIMSS Future of Healthcare Report, 80% of healthcare providers plan to increase investment in technology and digital solutions over the next five years. We will continue to see growth in areas including telemedicine, personalized medicine, genomics, and wearables, with organizers leveraging artificial intelligence (AI), cloud computing, extender reality (XR), and the internet of things (IoT) to develop and deliver new treatments and services.
So here are my predictions for the five biggest trends that will impact the healthcare industry over the next 12 months:
Remote healthcare and telemedicine
During the first months of the pandemic, the percentage of healthcare consultations that were carried out remotely shot up from 0.1% to 43.5%. Analysts at Deloitte say that most of us are happy with this and will continue to use virtual visits.
The reasons for this increase are obvious – but even when we take communicable diseases out of the equation, there are plenty of good reasons to develop capabilities to examine, diagnose and treat patients remotely. In remote regions and places where there are shortages of doctors (such as China and India) this trend has the potential to save lives by dramatically expanding access to medical treatment.
To deliver this, new generation wearable technologies are equipped with heart rate, stress, and blood oxygen detectors, enabling healthcare professionals to accurately monitor vital signs in real-time. The pandemic has even seen the establishment of “virtual hospital wards” where centralized communication infrastructure is used to oversee the treatment of numerous patients, all in their homes. An advanced form of this idea can be seen in the “Virtual ER” pilot under development at the Pennsylvania Center for Emergency Medicine.
In 2022 it’s likely we will see methods developed during the pandemic to deal with patients safely and remotely expanded into other areas of healthcare, such as mental health and the provision of ongoing follow-up care for patients recovering from operations and major illness. Robots and the IoT are integral to this trend, and smart technology (machine learning) will alert professionals when sensors detect that intervention is needed or cameras spot that an elderly person has had a fall in their home.
Telemedicine has the potential to improve access to healthcare in a world where half the population does not have access to essential services (according to the WHO). But this is dependent on winning the public’s trust – there are some situations where many people still feel an in-person interaction with healthcare professionals is required, so providers will need to consider this when implementing services.
Extended reality for clinical training and treatment
Extended reality (XR) is a catch-all term covering virtual reality (VR), augmented reality (AR), and mixed reality (MR). All of these involve lenses or headsets that alter our perception of the world – either placing us in entirely virtual environments (VR) or overlaying virtual elements on real-time images of the world around us (AR/MR). They all have potentially transformative applications in the healthcare sector.
VR headsets are used to train doctors and surgeons, allowing them to get intimately acquainted with the workings of the human body without putting patients at risk, or requiring a supply of medical cadavers.
VR is also used in treatment. This can be a part of therapy, where it has been used to train children with autism in social and coping skills. It's also been used to facilitate cognitive behavioral therapy (CBT) to assist with chronic pain, anxiety, and even schizophrenia, where treatments have been developed that aim to allow sufferers to work through their fears and psychosis in safe and non-threatening environments.
The number of applications for AR in healthcare will also continue to grow in 2022. For example, the AccuVein system is designed to make it easier for doctors and nurses to locate veins when they need to give injections by detecting the heat signature of the blood flow and highlighting it on the patient’s arm. Microsoft’s HoloLens system is used in surgical theatres, where it lets the surgeon receive real-time information about what they are seeing, as well as share their view with other professionals or students who may be observing the operation.
AR health applications for people who aren’t medical professionals exist too, such as the AED4EU geo layer, which provides real-time directions to the nearest publicly accessible automated defibrillator unit.
Making sense of medical data with AI and machine learning
The high-level use case for AI in healthcare, as in other sectors, is in helping to make sense of the huge amount of messy, unstructured data that’s available for capture and analysis. In healthcare, this can take the form of medical image data – X-rays, CT and MRI scans, as well as many other sources, including information on the spread of communicable diseases like covid, the distribution of vaccines, genomic data from living cells, and even handwritten doctors' notes.
In the medical field, current trends around the use of AI often involve the augmentation and upskilling of human workers. For example, the surgeons working with the assistance of AR, mentioned in the previous section, are augmented by computer vision – cameras that can recognize what they are seeing and relay the information. Another key use case is automating initial patient contact and triage in order to free up clinicians' time for more valuable work. Telehealth providers like Babylon Health use AI chatbots, powered by natural language processing, to gather information on symptoms and direct inquiries to the right healthcare professionals.
Another field of healthcare that will be deeply impacted by AI in the coming years is preventative medicine. Rather than reacting to illness by providing treatments after the fact, preventative medicine aims to predict where and when illness will occur and put solutions in place before it even happens. This can include predicting where outbreaks of contagious diseases will occur, hospital readmission rates, as well as where lifestyle factors like diet, exercise, and environment are likely to lead to health issues in different populations or geographical areas (for example, predicting opioid addiction in communities, or which patients who self-harm are most likely to attempt suicide.) AI makes it possible to create tools that can spot patterns across huge datasets far more effectively than traditional analytics processes, leading to more accurate predictions and ultimately better patient outcomes.
Digital Twins and Simulations
Digital twins are quickly becoming popular in many industries, in a trend that involves creating models informed by real-world data that can be used to simulate any system or process.
In healthcare, this trend encompasses the idea of the "virtual patient” – digital simulations of people that are used to test drugs and treatments, with the aim of reducing the time it takes to get new medicines from the design stage into general use. Initially, this may be confined to models or simulations of individual organs or systems. However, progress is being made towards useful models that simulate entire bodies. Current research suggests this is still some way from being a realistic possibility, but during 2022 we will continue to see progress towards this goal.
Digital twins of human organs and systems are a closer prospect, and these allow doctors to explore different pathologies and experiment with treatments without risking harm to individual patients while reducing the need for expensive human or animal trials. A great example is the Living Heart Project, launched in 2014 with the aim of leveraging crowdsourcing to create an open-source digital twin of the human heart. Similarly, the Neurotwin project – a European Union Pathfinder project - models the interaction of electrical fields in the brain, which it is hoped will lead to new treatments for Alzheimer’s disease.
This potential to help the healthcare industry to create treatments more quickly and cost-effectively is why digital twin technology is seen as one of the most important tech trends in healthcare for 2022.
Personalized medicine and genomics
Traditionally, medicines and treatments have been created on a "one-size-fits-all" basis, with trials designed to optimize drugs for efficacy with the highest number of patients with the lowest number of adverse side effects. Modern technology, including genomics, AI, and digital twins, allows a far more personalized approach to be taken, resulting in treatments that can be tailored right down to the individual level.
For example, the Empa healthcare center in Sweden uses AI and modeling software to predict the exact dosage of painkillers, including synthetic opiates like fentanyl, for individual patients. These can be highly effective and life-changing for patients suffering chronic pain but extremely dangerous in excessively high doses.
Drug company Novo Nordisk has teamed up with digital health company Glooko to create personalized diabetes monitoring tools, which provide bespoke recommendations for diet, exercise, and management of their illness, based on their blood sugar readings and other factors specific to them.
Genomics – the study of genes, and, recently, the use of technology to map individual genomes (the DNA structure of an organism, such as a person) – is particularly useful for creating personalized medicine. This is quickly leading to new treatments for serious diseases, including cancer, arthritis, and Alzheimer's disease. Nutrigenomics is a sub-field of genomics where we can also expect to see significant investment and progress during 2022 – this involves designing bespoke health-focused diet plans based on different genetic factors.