Wherever you look in the healthcare industry, you’ll see new technologies being used to fight disease, develop new vaccines and medicines, and help people live healthier lives.
Over the past two years, many technology companies have focused on applying their expertise to solving problems created by the global pandemic. At the same time, many healthcare companies that aren’t necessarily traditionally thought of as technology companies have also turned to technology and its potential to transform the delivery of products and services.
5 Biggest Healthcare Tech Trends of 2022
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It’s clear that the pandemic has accelerated the digital transformation of the healthcare industry. According to HIMSS’s Future of Healthcare report, 80% of healthcare providers plan to increase their investments in technology and digital solutions over the next five years. Growth will continue in areas such as telehealth, personalized medicine, genomics and wearables, as organizers leverage artificial intelligence (AI), cloud computing, extended reality (XR) and the Internet of Things (IoT) to develop and deliver new treatments and services.
So, I want to share my predictions for the five biggest trends that will impact the healthcare industry over the next 12 months.
Telemedicine and Telehealth
During the first few months of the pandemic, the percentage of medical consultations conducted remotely jumped from 0.1% to 43.5%, and Deloitte analysts say most people are comfortable with it and will continue to use virtual visits.
The reasons for this increase are obvious, but even excluding epidemics, there are many good reasons to develop the capabilities to assess, diagnose, and treat patients remotely. In remote areas and places with physician shortages (such as China and India), this trend could dramatically expand access to healthcare and save lives.
To achieve this, a new generation of wearable technology is being equipped with detectors for heart rate, stress, and blood oxygen levels, allowing healthcare workers to accurately monitor vital signs in real time. The pandemic has also seen the establishment of “virtual wards,” using a centralized communications infrastructure to monitor the treatment of large numbers of patients from their own homes. An advanced form of this idea can be seen in a “virtual ER” pilot under development at the Pennsylvania Emergency Medicine Center.
In 2022, it is likely that methods developed during the pandemic to treat patients safely and remotely will be expanded to other areas of healthcare, such as mental health and providing ongoing follow-up care to patients recovering from surgery or serious illness. Robotics and IoT will be integral to this trend, with smart technology (machine learning) alerting specialists when sensors detect that intervention is needed or cameras detect that an elderly person has fallen at home.
Telehealth has the potential to improve access to healthcare in a world where half the population lacks access to essential services (WHO). But this depends on winning the trust of the public. Many people still need to interact with healthcare professionals in some situations, so providers need to take this into account when implementing services.
Augmented Reality for Clinical Training and Care
Extended reality (XR) is an umbrella term for virtual reality (VR), augmented reality (AR) and mixed reality (MR), all of which involve lenses and headsets that change our perception of the world – either placing us in a fully virtual environment (VR) or overlaying virtual elements onto a real-time image of the world around us (AR/MR). All of these have potentially transformative applications in healthcare.
VR headsets are used to train doctors and surgeons, providing a detailed understanding of how the human body works without putting patients at risk or requiring medical cadavers.
VR is also being used therapeutically: as part of therapy, it has been used to train autistic children in social and coping skills, and to facilitate cognitive behavioral therapy (CBT) to treat chronic pain, anxiety and even schizophrenia, developing treatments aimed at helping patients overcome their fears and psychosis in a safe, non-threatening environment.
In 2022, the applications of AR in the medical field will continue to grow. For example, the AccuVein system is designed to detect the thermal properties of blood flow and display it on the patient’s arm, making it easier for doctors and nurses to find veins for injections. Microsoft’s HoloLens system is used in operating rooms, where surgeons can receive real-time information about what they are seeing and share their view with other specialists or students observing the procedure.
AR health applications also exist for non-medical professionals, such as the AED4EU geolayer, which provides real-time directions to the nearest publicly available automated defibrillator unit.
Understanding medical data with AI and machine learning
As in other fields, advanced use cases for AI in healthcare include helping to make sense of the vast amounts of messy, unstructured data that can be collected and analyzed. In healthcare, this can be in the form of medical imaging data (X-rays, CT scans, MRI scans), or it can be information about the spread of infectious diseases like COVID, vaccine distribution, genomic data from living cells, and even handwritten doctor’s notes, among many other sources.
In healthcare, current trends in the use of AI include augmenting and upskilling human workers. For example, the surgeons working with AR assistance mentioned in the previous section are augmented with computer vision (cameras that know what they see and communicate information). Another important use case is automating first contact and triage with patients, freeing up clinicians’ time for more valuable tasks. Telehealth providers such as Babylon Health use AI chatbots powered by natural language processing to gather information about symptoms and route queries to the right medical professionals.
Another area of healthcare that will be heavily impacted by AI in the coming years is preventive medicine. Rather than treating a disease after it has already developed, preventive medicine aims to predict where and when it will occur and put solutions in place before it occurs. This includes predicting where epidemics will occur, hospital readmission rates, and where lifestyle factors like diet, exercise, and environment may lead to health issues in different populations and regions (for example, predicting opioid addiction in a community, or predicting which patients who self-harm are most likely to attempt suicide). AI is making it possible to create tools that can find patterns across huge data sets much more efficiently than traditional analytical processes, leading to more accurate predictions and ultimately improved patient outcomes.
Digital Twin and Simulation
Digital twins are becoming increasingly popular across many industries as part of a trend to create models based on real-world data that can be used to simulate any system or process.
In healthcare, this trend includes the concept of the “virtual patient” – a digital simulation of a human being used to test drugs and treatments, with the aim of shortening the time it takes to get new medicines from the design stage to general use. Initially, this may be limited to models and simulations of individual organs and systems; however, progress is being made towards useful models that simulate the entire body. Current research suggests that this is still far from a realistic possibility, but progress towards this goal will continue in 2022.
Digital twins of human organs and systems are on the way, allowing doctors to explore different medical conditions and experiment with treatments without risking harm to individual patients, while reducing the need for expensive human and animal testing. A good example is the Living Heart Project, launched in 2014, which aims to use crowdsourcing to create an open-source digital twin of the human heart. Similarly, the Neurotwin project (a European Union pathfinder project) is modeling the interactions of electric fields in the brain, which may lead to new treatments for Alzheimer’s disease.
Digital twin technology is considered one of the most important technology trends in healthcare for 2022 because of its potential to help the healthcare industry develop treatments more quickly and cost-effectively.
Personalized Medicine and Genomics
Traditionally, medicines and treatments were developed based on a “one size fits all” principle, with trials designed to optimize the drug’s efficacy for the greatest number of patients with the fewest side effects. Modern technologies such as genomics, AI, and digital twins enable a much more personalized approach, resulting in treatments that can be customized down to the individual level.
For example, Sweden’s Empa healthcare center is using AI and modeling software to predict the exact dosage of painkillers, including synthetic opioids such as fentanyl, for individual patients. These painkillers can be highly effective and life-changing for patients suffering from chronic pain, but can also be extremely dangerous if taken in too high a dose.
Pharmaceutical company Novo Nordisk has partnered with digital health company Glooko to develop a personalized diabetes monitoring tool that offers tailored recommendations on diet, exercise and disease management based on blood glucose levels and other individual-specific factors.
Genomics (the study of genes and, more recently, the use of technology to map individual genomes (the DNA structure of organisms such as humans)) is particularly useful in creating personalized medicine. This is rapidly leading to new treatments for serious diseases such as cancer, arthritis, and Alzheimer’s. Nutritional genomics is a subfield of genomics that is expected to see significant investment and advancements in 2022. This involves designing customized health-focused meal plans based on various genetic factors.
For more information on these and other upcoming trends, check out my new book, Actionable Business Trends: 25+ Trends Redefining Your Organization.
