Healthcare, just as every industry, went through developmental phases that ultimately brought it to where it is today. What was once considered technology is today considered common practice.
Observing its development, you can see that it’s a step-by-step process that takes years to reach its full potential. It first needs to solve the basics and then take care of the advanced approaches. A kind of “healthcare theory of needs”.
A brief history of healthcare
Healthcare 1.0 brought about the solutions to major public health problems. The approaches became evidence-based and smarter. This included preventing infectious diseases with vaccines and making drinking water cleaner.
Healthcare 2.0 was focused on improving what was achieved during the previous phase. Therapeutics became widely available and antibiotics occurred on the market. Doctors not only became better and more professional, but also started specializing into subdomains to improve the treatment of more complicated conditions. These were very much the basics of modern medicine.
Healthcare 3.0 is when technology started making its way into medicine. Computers the size of the whole operating theatre do little good. But as they became smaller, they were used in ever more (and better) devices. Together, they helped to uncover diseases sooner and more accurately. Simultaneously, the internet provided healthcare with continuous access and storage of data. Doctors entered the era of evidence-based medicine.
Times are changing rapidly and healthcare is developing further. There are lots of reasons to believe we're currently in the middle of a transformation to a new era of healthcare.
The era of smart medicine or healthcare 4.0 - a collection of approaches that make medicine better, more efficient and more personalised. Some of them are precision medicine, artificial intelligence, automation and telemedicine. All covered in the next few paragraphs.
Precision medicine is adapting care and treatment to the patient based on their characteristics. Just about a year ago, a Slovenian 2-year-old received gene therapy for spinal muscular atrophy, Zolgensma that saved his life.
The trend is clear. There will be more and more drugs that will be tailor-made to the patients. But it's not just drugs. Every smart device you wear also contributes to precision medicine in a way. This vitally expands the time of data collection about your vital signs, exercise, sleep and more that your doctor can theoretically use for diagnosis and treatment.
The next step is proteome sequencing, where significant advances were made just two weeks ago at DeepMind. This is also where biology connects with advanced computational techniques, which will give us additional insights into our bodies' biochemistry.
Artificial intelligence will soon be an ordinary thing in medicine. There will always be more patients than doctors, and the gap will only increase. We need to thus find ways to help doctors, but also keep patients in mind.
We’re collecting more data than ever before. At one point, there will just be too much of it for a doctor to absorb and use in practice. One of the most helpful new tools on the horizon are decision support systems (DSS). Some are already used in practice and showed a significant improvement of diagnosis. A good thing is that the scientific community is constantly searching for ways to make them better and safer.
We're well on the way of developing such tools, which appears to not be a problem. The bigger issue is to shift the mindset of healthcare workers that this is not their replacement, but a helping hand that will make their job easier and better.
Apart from AI, replacing healthcare workers with automated systems is another dreaded topic. I'm not advocating that machines should (nor will) take over. But what they could do is replace humans in repetitive tasks that present the biggest burden. Is it such a bad thing if automated systems were to assist healthcare workers, so they can focus all of their energy on their patients?
An example is controlling the entry-points into the hospitals during the pandemic. You usually need a person, who measures the temperature of everyone, who enters the building and checks if they have any COVID-19 symptoms. Wouldn’t it be better for them to care for patients and make this automated?
Another example is hospital ward automation. We're starting to interconnect devices to share data (called "internet of things"). One of the most important applications is an alerting system for nurses if anything requires their attention.
Here's how healthcare automation and AI can help doctors from Nature Medicine:
He [Eric Topol] envisions that speech-recognition software could, for instance, capture physician–patient talks and turn them into notes. “Doctors will love this,” he says, “and patients will be able to look a doctor in the eye, which enhances the relationship.”
A way to relieve the time and space constraints of healthcare is by implementing telemedicine. To be fair, this is a topic we heard in medical school…although not very up-to-date. And to be even fairer, COVID-19 gave this area a significant boost.
How did people and healthcare professionals react? According to countries such as Sweden, Germany and Estonia, which have the most technologically advanced healthcare systems in the world, the start was tough and different. But after a few months of coping with the new reality, both the people and healthcare professionals adopted and adapted to it. Because technology is only getting better, it’s here to stay.
Reviewing and condensing all of what I wrote about in the last few months makes me optimistic. Sure, not all technology is great, we need human connection in healthcare. But the human connection is here to stay, just as technology is.