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The Future of Medicine Print E-mail
Prof Erwin Loh  
“Declare the past. Diagnose the present. Foretell the future.” - Hippocrates

Declare the Past:

The role of the doctor is a constantly evolving one. To know where it is headed, it is useful to know where it has come from. Much has been written about the history of medicine, which goes back thousands of years, as part of ancient Babylon, China, India, Egypt and Greece. For example, the Hippocratic Oath, which is still relevant today in its modernised version, was developed in 5th century BCE Greece.
Doctors were only systematically trained as a profession in 12th century AD in Europe at the beginning of the Renaissance, with the discovery of anatomy and microscopes. The Age of Enlightenment and the Industrial Revolution in the early 19th century led to the germ theory of disease being confirmed and the birth of public health medicine.
Consider that antibiotics were only discovered in the mid-20th century, and modern medical technologies we take for granted such as diagnostic imaging platforms, laboratory equipment, and computers were only invented in our own lifetimes, medicine has come a long way. The role of the doctor has evolved together with the tools of the trade. However, technology in medicine is developing at an exponential rate, and the speed at which this is happening is accelerating - medicine will advance more in the next 10 years than it did in the last 100 (1).

Diagnose the Present:

Today, patients are still suffering preventable adverse events and medical errors in hospitals. It is the third leading cause of death in the United States (2). Doctors are no longer expected to be just technical healers, but they also have an important role in leading the quality of care and patient safety agenda.
To this end, recent innovations like checklists, which are part of the standard operating procedures in the aeronautical space industry leading to significant improvements in its safety records, is now just penetrating medical practice, although with major resistance from the doctors themselves. Other strategies, such as the use of behavioural economics to influence behaviour, for example through positive peer pressure by publishing performance results, and increasing consumer empowerment, through the use of patient portals, have also been shown to be effective. The way we fund healthcare also drives practitioner behaviour and impacts clinical outcomes, with fee-for-service incentivising procedures, activity-based funding driving acute activity at the expense of chronic disease management. 
The use of electronic medical records (EMRs) have helped to improve clinical communication, documentation and standardise care through the use of order sets and evidence-based care pathways providing clinical decision support at the bedside. The rise of telemedicine and telehealth, including remote robotic surgery, has improved access for patients.
Technological advances in augmented reality is helping surgeons to visualise the surgical fields and improving medical education. New devices in the form of 3d printed prostheses, implantable artificial organs, and embedded microchips are already being used and will become even better. Wearables like FitBit will provide real-time, live biometric data, and help disease management remotely. These biosensors are already helping hospitals manage severely ill patients and predict deterioration, and are evolving to become electronic skins and tattoos.

Foretell the Future:

The improvements in hygiene and therapeutics will continue. There has been amazing progress in oncology for example, with immunotherapy, genomics and genetic engineering all playing a part to prevent, manage and potentially cure cancers in the not too distant future. Stem cell therapy could restore sight and neural damage (3).
Eminence-based, practitioner-dependent medicine, has evolved to become evidence-based, standardised, best practice medicine. But this current move to reduce variation and make everyone go down the same pathway will give way to personalised medicine, which is based on each individual’s genotype, including epigenetic factors, which will lead to individualised therapies that avoids the trial-and-error method of medication choice and dosing.
Genetic engineering can potentially edit out hereditary diseases. Robotics and neural interfaces may lead to cybernetic artificial limbs. Brain-computer interfaces (BCIs) are being developed: invasive interfaces, using new nanomaterials that provide two-way neural communications; and non-invasive interfaces, based on EEGs that allow the paralysed to type out words or control devices with just their thoughts (4).
In addition, there have been significant advances in anti-senescence and aging reversal therapies, with recent papers published on therapeutics like rapamycin, genetic therapies and telomere modification that could prolong life even more.
However, with these successes will come additional challenges. Healthcare is faced with a series of challenges that threaten to overwhelm its ability to meet them without a complete paradigm shift. The population is growing, ageing and becoming more obese, and people are living longer and surviving acute illnesses with chronic disease, dementia and other long-term disabilities.
The health system cannot possibly manage the increasing burden on its resources, workforce and finances, without a complete transformation. In the short term, the models of care need to be reviewed, and the hospital-based acute system that we rely on, needs to transition into a community, home-based framework of care. Care can then be decentralised to the home, but technology needs to be leveraged so that data can be transmitted back to centres of excellence for monitoring and decision-making.
But even with changes to the way we care for patients, the rate of medical knowledge is increasing at an alarming rate, and to align the available evidence with the amount of health information being collected from these patients is already beyond the comprehension of human abilities.
“Future medicine will be the medicine of frequencies” – Albert Einstein
The role of the future doctor will need to be supported by machines. Artificial intelligence, or AI, is basically intelligence exhibited by machines, in the form of computers or robots. When an AI is able to learn from data, this is also called machine learning. Deep learning is what happens when machine learning improves through the use of advanced statistical techniques applied to big data. Neural networks, interconnected computer nodes designed to network like a human brain, form the foundations of deep learning.
AI is transforming all aspects of every industry, and is increasingly being used in healthcare.  AI is able to consider, collate and sieve through the vast amount of available data and, at this point, able to equal the diagnostic power of doctors in certain areas. For example, deep learning systems are now able to review radiological and pathological images and provide diagnoses that are equal to radiologists (5) and pathologists (6) respectively. Other trials have shown similar results in oncology, dermatology and even psychiatry. AI is far superior to humans when it comes to patter-recognition and using algorithms to synthesise big data. This can then lead to more accurate diagnoses and better treatments, faster and cheaper.
Machines will support doctors, like they always have, but will they replace them? Some commentators have argued that AI will inevitably replace many doctors, lawyers and other professionals (7). Some argue that machines can never replace doctors because they lack the “human touch” of “compassion and kindness”, but IT experts use the “personal banker” and the “travel agent” as examples of professions that are being gradually replaced by computer systems.
It is most likely that technology will replace, not all, but 80%, of what doctors do (8). As AI becomes more prevalent in healthcare, and take the place of current digital clinical decision support systems, the role of the doctor as the primary diagnostician will slowly be taken over by smarter and smarter machines. This journey has already started with the advance laboratory and radiology systems that are being used, and will extend to the bedside, and then to primary care. AI will also be able to formulate best practice treatment plans, and then based on genomics data, customise this for the individuals. Proceduralists may still be needed, supported by robotics, but even simple surgical interventions may, at some stage, be replaced by advanced robots.
“You cannot manage men into battle. You manage things; you lead people.” – Grace Hopper
Support from technology will free up the future doctor to be the human face of the healthcare system for the patient, to provide the personalised care and compassion that are just as important as the technical answers being sought. The doctor can also be freed up to lead the health system as a whole. Machines can manage information, and provide a prioritised list of options based on best evidence, but machines can never lead people – in other words, people would not want to follow a machine – people follow people. In the same way, a doctor’s role as a health systems leader will never be replaced by technology.
My argument for all doctors today is this – why wait for the future? Be the human face of the health system today, and show compassion and kindness to your patients. And rise up and lead the health system. Because that is the one thing that no one can take away from your role as a doctor.
Prof. Erwin Loh
1. Vivek Wadhwa, Stanford University, “Medicine will advance more in the next 10 years than it did in the last 100”, 26 October 2016, https://singularityhub.com/2016/10/26/medicine-will-advance-more-in-the-next-10-years-than-it-did-in-the-last-100/
2. Martin A Makary & Michael Daniel, “Medical error—the third leading cause of death in the US”, BMJ 2016; 353 doi: https://doi.org/10.1136/bmj.i2139 (Published 03 May 2016), http://www.bmj.com/content/353/bmj.i2139
3. Michiko Mandai et al. iPSC-Derived Retina Transplants Improve Vision in rd1 End-Stage Retinal-Degeneration Mice. Stem Cell Reports, January 2017 DOI: 10.1016/j.stemcr.2016.12.008, http://www.cell.com/stem-cell-reports/abstract/S2213-6711(16)30298-3
4. Chethan Pandarinath, Paul Nuyujukian, Christine H Blabe, Brittany L Sorice, Jad Saab, Francis R Willett, Leigh R Hochberg, Krishna V Shenoy & Jaimie M Henderson, “High performance communication by people with paralysis using an intracortical brain-computer interface”, eLife 2017;6:e18554 (Published February 21, 2017), https://elifesciences.org/content/6/e18554
5. Max Wolf , Jens Krause, Patricia A. Carney, Andy Bogart, Ralf H. J. M. Kurvers, “Collective Intelligence Meets Medical Decision-Making: The Collective Outperforms the Best Radiologist”, PLoS ONE 10(8): e0134269. doi:10.1371/journal.pone.0134269, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0134269
6. JJ Ye, “Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.” Arch Pathol Lab Med. 2015 Jul;139(7):929-35. doi: 10.5858/arpa.2014-0478-OA. http://www.archivesofpathology.org/doi/10.5858/arpa.2014-0478-OA
7. Richard Susskind & Daniel Susskind, “Technology will replace many doctors, lawyers and other professionals”, Harvard Business Review, October 11, 2016, https://hbr.org/2016/10/robots-will-replace-doctors-lawyers-and-other-professionals
8. Vinod Khosla, “Technology will replace 80% of what doctors do”, Fortune, Dec 05, 2012. http://fortune.com/2012/12/04/technology-will-replace-80-of-what-doctors-do

Last Updated on Friday, 15 September 2017 12:44