Technology has pervaded all spheres of life. Education, design and even sports – all are getting their share of improvement owing to the inclusion of technological advancements and digitisation in the sectors. Healthcare too, has been one of the sectors which has seen a plethora of improvements owing to the incorporation of technological fundamentals within.
This trend brings up the underlying basic – data driven decisions. Traditional forms of medicine, sports and education focused on trial and error approaches, which although simple on the performer’s part, did not turn out to be always effective.
And that’s where technology came in, in the form of data algorithms and analytics. Numbers and readings are converted into analytics. Analytics is converted into information and this information converts into insight. A beautiful metamorphosis of numbers into insightful knowledge occurs, and what better example to support this than the fundamentals of the Quantified Self movement.
Which brings me to the crux of my article: Will data driven decisions complement the medical and healthcare sector to such an extent that one day doctors might be replaced entirely? Are we heading into an era where algorithms will replace practical human knowledge? In this piece, I talk about the possibilities of mobile medicine replacing doctors in the future.
The inspiration for this piece comes from legendary VC Vinod Khosla’s views on the subject. Vinod Khosla has been a patron of the Quantified Self movement for quite some time now, having made investments in reputable lifelogging companies such as AliveCor, Jawbone, Misfit and Narrative, among others.
In an interesting paper that he’s written, Vinod Khosla states that while the traditional approaches of healthcare and medicine are sufficient enough to tackle the existing health problems, they are far from being flexible. For example, when multiple doctors are presented with the same symptoms and asked for their diagnoses, most doctors gave different diagnoses, and as a result there wasn’t a clearly defined solution to a problem.
Although the above experiment was carried out merely as a survey, personally I believe that it might have alarming effects in the real world. A wrong decision might result in the patient’s health deteriorating rather than improving, a wrong diagnosis might be the defining factor which separates a quack from genuinely intelligent and sincere doctors. And herein lies the inefficiency of the system.
Technology is already making its presence felt in the field of medicine. For a simple example, consider this: prescriptions and medical records were earlier maintained through pen-paper approaches.
The disadvantages of this modus? One, paper isn’t permanent, isn’t flexible, and doesn’t allow for seamless integration across different hospitals for a single patient. And Two, pharmacists and doctors alike would have to get used to the mindset of the earlier consultant – be it in the form of reading the scrawls of the doctor’s prescriptions or going over the medical history of a patient.
And this fundamental is reflected in what Vinod Khosla says in his paper. He states that healthcare – an intricate science by itself already – will become even more consistent through the inclusion of technology. The technology can be in the form of inexpensive data gathering techniques, continual monitoring, more rigorous science and more flexible and ubiquitous bits and pieces of relevant information.
Apply this principle directly to the Quantified Self movement, and you’ll see striking similarities: inexpensive data gathering techniques (Sensors, wearables, trackers and applications), continual monitoring (Internet of Things trackers, non obtrusive wearable devices) and information being processed through robust algorithms that churn out insightful knowledge from mere data – all these parameters constitute the brilliant ecosystem encapsulated by the Quantified Self movement.
AUTOMATION STEPS IN
In an interview with MIT Technology Review, Vinod Khosla states that there is a clear distinction between the advantages of a machine taking over the role of a doctor and a human playing the same role. He quotes Atul Gawande – a renowned surgeon – and says that while machines are more adept at handling the cognitive parts of medicine – which involve diagnosis and writing the right prescriptions, humans are better at the humane aspect of comforting or being a physical presence to the patient.
This actually reminds me personally of the Disney movie Big Hero 6, wherein a robot is designed specifically to detect physical ailments or afflictions, and assist the concerned patient by not only providing a (apparently) correct diagnosis, but also doing so in a comforting manner. While Baymax is just a fictional character as of 2016, it does bring about the question – will it become a reality later on? And if it does, will the need of human doctors be redundant?
While the possibility is quite frankly intriguing, the answer to the question as to whether doctors will be replaced by algorithms is quite tough to get to. Vinod Khosla states that healthcare today is the practice of medicine, rather than the science of it, and I completely agree. Modern medicine focuses on a doctor seeing a symptom, correlating it with the patient’s previous history and/or the doctor’s own medical experience, and then coming to a suitable conclusion.
While this approach is without a doubt helpful when it comes to detecting known diseases, one has to consider the science of virology itself – which doesn’t really take things for granted. Diseases themselves evolve as well, and sometimes give rise to new, varied forms of the same disease. While the doctor ponders over the symptoms, it is quite likely that the disease will have the upper hand.
The need of the hour in this regard is a more scientific, robust approach, which focuses on the integration of artificial intelligence (to some extent), data collection algorithms, analysis and experimentation to rapidly improve systems. Herein comes the data driven approach that I mentioned earlier in this article, wherein physicians would be assisted with data algorithms in order to come to suitable conclusions regarding a specific disorder.
With the help of data driven algorithms, physicians can come to suitable conclusions when it comes to a disease, and the chances of misdiagnosis, conflicting diagnoses and errors are completely averted. Science and data need to come to a common ground and work hand in hand with physicians and medical personnel in order to deliver comprehensive medical care.
Again, I’ll go back to Vinod Khosla’s very interesting views on this matter. He says that the primary goal of medicine should be to make a consumer the CEO of his own health. And this might probably explain his recurring funding in the lifelogging / digital health sphere, specially in devices and software which help people track their own health parameters from the comfort of their own homes.
Devices such as CellScope allow the user to see the ear in detail. AliveCor is another such technology which allows users to take ECG readings and push the reading directly to a smartphone. Technologies such as these – which directly utilise a smartphone’s capabilities – might not be better forms of medicine, but they certainly are precise forms.
In fact, we’ve already discussed the importance of sensors within smartphones. We’ve previously explained how brands such as Apple and Google are making use of sensors in order to gather more data and try and understand the user through machine learning algorithms. In fact, the scope of the usage of mobile phone sensors has been the inspiration for our applications such as Instant and Sleeply.
The increasing usage of contextual principles and machine learning algorithms pave the way for more cognitive actions that your smartphone can perform. Right now, it’s all about studying the smartphone user, but in the near future we can see the applications extending from mere novelty and data gathering / analysis to things even more intricate, such as diagnosing symptoms.
Phones are already getting better at tracking heart rate stats, blood pressure, oxygen levels and even skin health (an app called Skin Scan takes a photograph of the user’s skin, studies the lesions and/or texture and accordingly comes to a conclusion regarding the skin health. It can actually help in diagnosing skin cancer).
So will mobiles replace doctors? At the current rate, and through mere functions, yes they will. Mobiles and sensors will become even more advanced in the near future, and they can be calibrated to take finer readings and gather more data. Algorithms can take over to come to suitable diagnoses that work with an efficiency which threatens to overshadow that of human doctors.
But, will it be a practical solution?
THE BOTTOM LINE
Firstly, to answer the question I asked in the previous paragraph, no it would not be a practical solution. Precise, yes. Flexible, yes. Possible, definitely. But not practical.
You see, medicine and healthcare are very delicate concepts. While technology will definitely improve the way things are functioning right now, personally I believe that the scope will be at best to assist, to complement – but never to replace.
Vinod Khosla clearly has some well defined notions about how technology can improve the healthcare sector, and I completely agree with his points. The power of data is infinite – be it in sectors of healthcare, education or within workplaces, data driven decisions are insightful, intelligent and seldom wrong.
Data driven healthcare will convert healthcare into a more wellness oriented sector – wherein instead of treating sick people, doctors and algorithms alike can work hand in hand to not just rectify ailments, but also to avert their occurrence altogether. A simple example: genetics sees which trait you carry from your genealogy, data algorithms decipher what are the chances of you being affected by the trait, and modern medicine will help avert the disorder.
That is why I believe that mobile technology would never be able to replace modern medicine. Data and science will work hand in hand in order to provide more consistent, more quantifiable and more effective results.
The future of medicine is in the form of mobile technologies. Healthcare will evolve into wellness. And this can only take place if data complements the doctor, numbers complement science, and not replace.
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