Medicine has never been subject to such massive changes as it is now in terms of technological advances and the rise of digital health innovation. It’s important to be aware of these developments because they have implications for the way that Doctors work, how patients look after themselves and how diseases are dealt with by the health service.
Let’s take a look at some examples so that you can start to be familiar and understand these changes. This may be especially helpful for medical school interviews and MMI circuits where such questions may be posed as ‘What do you think are the advantages and disadvantages of artificial intelligence in medicine?’
This technology has come along in leaps and bounds over recent years and whilst excellent for playing SuperHot VR, it also has multiple medical applications. These include simulations for training eg. for surgical skills (check out FundamentalVR), emergency scenarios and communication practice. VR can also be used as part of treatment for a variety of medical conditions eg. as part of distraction therapy for patients with chronic pain or undergoing uncomfortable procedures such as dressings changes, it can be used to help manage various phobias through graded exposure and has found some success with mental health problems such as bipolar disorder.
From the training perspective VR provides good opportunity for medical students and junior doctors to experience a variety of medical situations that may be difficult to access on a day to day basis, allowing them to try and fail in a safe environment. It could also enable more experienced Doctors to maintain their skills in the same way that airline pilots have to complete a certain number of hours per year in a flight simulator in order to have their competencies checked.
The downside of VR however is that it is not really real. It cannot always fully emulate a real life case, it’s a sophisticated video game and the pressure of the real world is not inherently present. We don’t want Doctors to lose their humanity at the expense of creating a generation of technicians.
Microprocessors and sensors are getting smaller, more durable, adaptable and wearable. Medical devices increasingly have the ability to detect and monitor medical conditions, this could be something relatively simple from the Apple iWatch which can detect heart rhythm disturbances such as Atrial Fibrillation to implantable glucose sensors which can give a continuous read out of your blood glucose levels. Soon your smart toilet will be able to pick up abnormalities in your urine and send information to your Doctor before you even know that you have a problem. Through your connected smartphone app you’ll be notified of your latest medical results and a treatment plan set in motion.
There are many benefits of living in a connected world, so long as people are happy with the sharing of their private health data overlapping with the internet of things. The Amazon Alexa system has recently been approved as a medical device and tucked away in the small print of the terms of conditions alarming things may be described as to how they will use your personal data.
Be careful what you mean here by ‘AI’ as this is a misused term. An algorithm which suggests that you want to watch The OA on Netflix based on your viewing history is not AI, nor is a rule engine that can tell you that you have a 12% risk of a heart attack happening in the next 5 years. AI is the simulation of human intelligence by computer systems. This includes learning, reasoning and self-correction. Narrow AI is something trained for a particular task, such as Siri on the iPhone. General AI had more extensive cognitive abilities. When presented with an unfamiliar task, a strong general AI system is able to find a solution without human intervention.
AI presents strong possibilities in the field of medicine, over and above cognitive computing. An example would be a computer programme that is able to analyse and act on thousands of blood results simultaneously and identify patients with acute kidney injury such as DeepMind’s ‘Streams’ application. Kheiron Technologies have developed an image analysis AI for detecting cancerous cells in breast biopsy pathology slides, which works as well if not better in some circumstances than Consultant Pathologists.
Babylon Health have a symptom checker AI in their smartphone app which can assist with medical diagnosis and treatment plans. It automates much of the information gathering but don’t worry Doctors are redundant just yet. One of the underlying problems that has been identified with such systems is the presence of potential bias in the underlying machine learning algorithms in AI systems. After all, humans write the code and the decision-making trees underlying AI. Humans are biased, contradictory and make value judgments all the time. It would be a shame if all the AI oriented systems of the future were based on the unworldly preferences of young, white computer geeks who live at home with their parents.
ELECTRONIC MEDICAL RECORDS
One place where big leaps have been made over recent years is in the realm of healthcare data collection, storage and retrieval. Paper notes and fax machines are slowly dying out and Doctors are spending more and more of their time staring into computer screens rather than the faces of their patients. This is because this is where the action is now happening. The hapless house officer on the ward round is busy typing away into the computer on wheels whilst the nurse sends the digital biometric observation data from her tablet into the central database.
Meanwhile, the GP is feeding the beast, inputting data into the EMR system and trying to improve their QoF scores during the pressured 10-minute appointment. Record systems and databases are excellent ways of organising the vast amounts of medical data that we need to stay on top of, but we do run the risk of becoming data entry servants rather than empathic action-orientated problem solvers? Just imagine the freedom of a blank piece of clerking paper…
So in summary, health tech is here and it is growing. There are good connotations and bad. There is the possibility that through automation and data processing we can pick up and treat medical problems even more efficiently than ever. However there is the downside that Skynet will take over and that Doctors become technically proficient computers who forget how to treat the human condition. Or is the reality likely to be somewhere in the grey area in between?
We hope that this was a helpful overview of this hot topic in healthcare and you feel more confident tackling it if it comes up as an interview question. Don't hesitate to send us any questions or comments by email at hello@theMSAG.com. Good luck in your interview!