Covid although causing considerable distress but has also allowed innovation in healthcare to be greatly accelerated. The regulatory framework has helped fast track new ideas and solutions. Telecare and total triage have helped patients access their doctors remotely and at their convenience improving access. Telemedicine consultations have increased by over 5000% and changed the doctor-patient interaction. Vaccine development had taken 10 -15years prior to the pandemic and has been shortened to less than a year with rapid design and delivery of clinical trials. Covid supplies were delivered to remote areas using drones. Accurate real-time vital sign measurements, including heart rate and oxygen saturation could be measured via an app using AI-powered light signal processing technology to convert light reflected from blood vessels in the face. Smart stethoscopes were developed that both listen to patients’ hearts and transmit images of the lungs. Virtual reality was introduced to support training. Robots were introduced to sterilise rooms and offer support to patients. The key to this has been collaboration with industry and healthcare providers coming together at the time of need to share different skill sets. The pandemic is a global problem and the world has responded by sharing global solutions and hopefully this allows the new normal to help springboard health into the future.
Exponential technologies and the digital transformation of health
The world is at an inflection point with exponential technologies converging to help reimagine and reinvent healthcare. Technologies like AI, Robotics, 3D Printing, Gene sequencing/editing, immersive technologies, 5G connectivity, remote sensors, nanobiotechnology offer interlocking building blocks to help prevent illness, monitor physiology, improve diagnosis and offer new treatment modalities. There have been 3 windows to humanity. Copernicus discovered the telescope as a window into the universe. The microscope has helped us understand the intricacies of the human body. Data, the third window is now helping understand and build a personalised approach to medicine. Patients with chronic diseases will be managed more remotely with access to their data and therefore empowering them to be involved in their health. Rare diseases are now being sequences and whole genomic data become available on a national scale which will help understand population health. Drones are delivering medical equipment across cities and 3d printing is allowing the planning of treatment and implant of devices. Eventually this may lead to the production of a bioengineered organs. 5G with its low latency and fast bandwidth will help with remote surgery across continents and smart ambulances bringing valuable support to the roadside. The development of chatbots, digital twins and digital humans will ask important questions on what the future interaction between a patient and doctor may look like.
The Future of medical education
Medical education is going through a paradigm shift as technology enhanced learning are enabling hybrid models of delivering quality education. We have moved from papyrus to books to eLearning/online platforms. More recently tele platforms have become the normal. The pandemic has forced new ways of delivering clinical medicine. The future will encompass more traditional models converted to using augmented, virtual and mixed reality. Students will be trained more remotely with classrooms replaced by virtual rooms. Anatomy dissection will be enhanced digitally, clinical ward rounds can be supported by mixed reality and surgical operations will be viewed in virtual reality with more interactivity allowing teachers to be hundreds of miles away or even on the other side of the world. This will allow the democratisation of education that will allow every student to access world class education breaking down the barriers of cost and location. The adage of “see one’ do one, teach one” will be superseded by simulation using CGI or real time images thereby supporting training of practical procedures. Digital Health, entrepreneurship and innovation needs to be at the heart of any new curriculum to produce the digital doctor of tomorrow.
Education 4.0 will allow clinical teaching to use all of the available platforms for a richer experience.
In October 2017, I entered and embraced the metaverse for the first time from my operating theatre from the Royal London Hospital. I had created my avatar and joined surgeons from London, India and the US. We were able to interact in the virtual world — across three continents and three time zones simultaneously. We shared assets like CT scans, X-rays and 3d models to discuss the patient during live surgery. Imagine a world where a surgeon could call on help when required by simply transitioning from the real to the virtual world, allowing the true democratisation of healthcare.
In his 1992 book Snow Crash, American author Neal Stephenson introduced the term “metaverse,” referring to the 3D visual space occupied by lifelike human avatars. People in this dystopian future wear realistic mirrors to connect with the digital world! In Silicon Valley, it is a well-known novel. Metaverse is an all-encompassing 3D visual space shared by everyone. The metaverse can be thought of as a cluster of connected earths, just as the visible universe is a group of planets connected to space. Can the metaverse become a part of the healthcare system of the future?
Surgery is moving rapidly from analogue to a digital interface. The new 5 pillars of digital surgery are connected care, robotics, data analytics/AI, surgical navigation and remote collaboration. Over the last 20 years we have seen enhanced visualisation and improved fine dexterity allowing surgeons to manipulate a robot with the potential improvement in outcomes for the patients. The robot wars in 2022 are allowing more access and flexibility in offering minimal access surgery. By having large amounts of real time data during an operation by using analytics will also aid surgeons to assess their performance and move away from subjective methods of performance to a more robust and transparent process. For decades surgical acumen has been only facilitated by personal judgement. The use of artificial intelligence and computer vision will allow surgical navigation during a procedure allowing surgeons an intraoperative map to help avoid damage to important structures and ensuring cancers can be removed in their entirety to allow a potential cure. Preoperative planning will be supported by mixed reality headsets to overlay images on the patient to improve accuracy and decision making. Remote telemonitoring will be possible due to the power of connectivity with 5G allowing surgeons across the world to support global training and improve standards.
AI in healthcare
Artificial intelligence and deep machine learning is changing the face of medicine and may be the most important technology to be integrated into healthcare. AI has promised hope which has been followed by much hype. We are now witnessing the reality of real time applications of AI. AI can enhance clinical productivity due to its ability to handle a large capacity of tasks that are well suited for automation. AI can reduce the burden of clerical work of doctor’s thus improving the quality of care and allow them to spend more time with patients and the healthcare team
The collection of good quality data is a pre requisite for an algorithm to produce meaningful conclusions and outputs. This data includes patient biometrics, natural language and operational data. The outcomes have been to improve early detection/triage, diagnosis, disease management and monitoring diseases and wellbeing. Analysis of images has been well researched with AI algorithms diagnosing abnormalities on chest xrays and CT scans with over 90% accuracy. Dermatology is being supported by smart AI to help diagnose skin cancers. Drug development has been accelerated by molecular identification and targeting. Protein folding has been unravelled using powerful AI. Chatbots and intelligent conversation engines are helping with triage and stratifying risk.
However, the ethics need to be considered as there also inherent risks of AI with false prediction and the inappropriate use of patient data. This needs careful debate and patient engagement to ensure that AI is safely and responsible implemented.