The 6 avenues of MedTech
AI, big data or medical devices. The avenues of MedTech are far more complex than you think.
If you haven’t read the article on what MedTech is and what those avenues are, then you can find it here. Nevertheless, for those who don’t want to read that, KnowMedTech has identified the following six avenues as those that can best encompass MedTech:
- AI and machine learning
- Big Data
- Paperless
- Internet of Things (IoT)
- Medical Devices
- Genomic Technologies
Just knowing what those avenues are is all well and good, it’s a start to being aware of MedTech, but it doesn’t necessarily mean you understand those avenues. That’s where this article comes in. That’s its job. Hopefully, over the course of this article, we can discover together what they actually mean.
AI and machine learning are buzz words in the current climate. They are used interchangably (rightly or wrongly) and are probably the first aspect you think of when you think of MedTech. Artificial intelligence at its very core produces ‘smart’ machines or, machines that are able to think, with the ultimate aim of reproducing human intelligence. Now, explaining what ‘intelligence’ really means is a whole article in itself but in essence, it involves taking sets of data, being able to analyse them and then ultimately make decisions using them.
Machine learning and deep learning are further sub-sections of Artificial intelligence and knowing about them will allow you to appreciate what ‘intelligence’ is. Machine learning uses algorithms to learn from large sets of data to make informed decisions which progressiveley get better with each iteration of decision. However, an engineer needs to monitor this to ensure the machine learning code produces the right decisions, intervening when it doesn’t — it’s not fully automated.
Deep learning is a denomination of machine learning which has the capabilites of being fully automated. It uses algorithms to learn from large sets of data, makes informed decisions and then is able to decide whether it was right or wrong. It does this using an ‘artifical neural network’. A neural network is very similar to the architecture of the human brain, being extremely complicated with a complex series of connections (similar to neurons).
Artificial Intelligence then, uses a combination of machine learning, deep learning and other techniques to solve problems and predict future patterns. To do this however, it requires extremely large amounts of information to develop these algorithms from. This is why you sometimes have to select all the images that contain a traffic light to confirm that you’re not a robot — you’re providing that data. This allows progression to the next section more seemless, we require Big Data.
For a more detailed explanation on the difference, check out this zendesk article!
Big Data in healthcare is the compilation of physical and clinical data that is too complicated to be analysed using traditional statistical methods. Due to this, the data is normally ‘crunched’ using artificial intelligence and machine learning.
Big data relies on other aspects of MedTech spoken about in this article such as Medical Devices that use Internet of Things to communicate data to a central location which then uses AI and Machine Learning to analyse it. Although it uses other aspects of MedTech, we felt that Big Data required its own section because it allows the solution to the vast data available, growing healthcare costs and the focus on personalised medicine.
The data available facilitates the development of personalised medicine which is the future of medicine, producing treatments and management plans that are bespoke to the patient. This should in theory increase the likelihood of success of healthcare.
For a more detailed explanation of Big Data in Healthcare, check out this article by Evariant.
Paperless is not a technology in itself. However, it is a key aspect for the future of digital health and it is arguable the stepping stone for other technologies to fluorish.
Going paperless mainly relies on the developments of Electronic Health Records (EHR) which essentially takes the majority of a patient’s health information and stores them digitially. This is important because it provides monitoring of various health risks of a patient at large scales without having to seive through copious amounts of paper. Going paperless also allows for quick access to specific information points which allow for a quicker consultation with a patient. This in turn allows clinicians to see more patients in a given time period ultimately prvodiing healthcare to a larger audience.
The reason why we initially said that going paperless was a stepping stone for other technologies however, is because ultimately it provides larger data sets. Now, privacy and the fair use of this data is important but a topic for another day. Wearables can integrate with the EHR to provide real-time patient monitoring, aritificial intelligence can use the EHR to predict what issues a patient is more likely to face in the short and long-term, and Big Data technologies can then use this to predict healthcare trends for the future, allowing us to put preventative measures in place.
If nothing though, going paperless allows us to reduce climate change and try to save the planet.
Internet of Things (IoT) is really interesting. It is not just a medical technology, in fact, it isn’t a medical technology. It encompasses anything connected to the internet really and allows devices to communicate to each other including wearables, smartphones and even cars! The ultimate aim of IoT is to create a connected world.
IoT is not new with regards to application within the healthcare community. It allows communication of patient wearables (allowing patient monitoring), treatment progression or even storage of medical equipment. The progressions that IoT bring could change healthcare from being mostly reactive diagnosis and treatment, to preventative measures that emphasises personalised medicine.
IoT can be used to monitor the elderly at home for example. Let’s say there is an elderly patient who usually requires a carer once a day to come to their house and check in on them. If their house was fitted with a couple of motion sensors near the kitchen and a smart kettle, that elderly patient’s family could monitor each day, whether the patient has carried out their normal acitivites, i.e. coming into the kitchen and making some tea. If the patient doesn’t carry out these activities, the information is sent to the family who can then check on the patient and act accordingly. This simple methof could allow the elderly patient to remain fully independent which would improve their mental health, but also allow the monitoring of their health as a whole, especially if they were given a wearable.
Medical Devices are more common than you think. The European Union Directive have a complex definition for what they are. Essentially however, they are any device (instrument, appliance etc…) that can be used by itself or in conjunction with software, to provide healthcare services.
The wide spectrum of this industry is what drives its success. At one extreme, there are highly invasive implants such as electrically active pacemakers, neurostimulators which can help to control pain or even swallowable cameras to help visualise the inside of the body. The other end of the extreme includes expendables such as bandages, needles and disposable surgical instruments. The industry includes imaging technologies such as CT and MRI scanners which are obviously vital to the provision of good quality healthcare.
Medical devices are vital for the advancement towards personalised medicine and continuous health monitoring which is becoming ever important in today’s society. The advancements in this field wil increase the accuracy and efficiency of the devices, potentially reducing how invasive medicine has to be.
Genomic Technologies can be considered more of a science than a digital technology. MedTech is defined by the application of science for the advancement of medicine and therefore, genomics should be considered an aspect of MedTech in our opinion.
Genomics is the study of an organism’s complete set of genetic material and is being used to revolutionise the delivery of personalised medicine. Understanding someone’s genetic code enables you to understand what makes them predisposed to certain diseases on and individual and large scale. This information is key to producing not only the right treatments but also the right preventative measures.
The more and more genomes that are mapped and the longer this technique is carried out (to map their genome to long-term health conditions), the increased chance of understanding what predisposes you to non-communicable diseases. These diseases, such as Diabetes and High Blood Pressure, are some of the most common around the world and even some of the biggest causes of mortality. By looking at the genetic information of those with high blood pressure, we can understand why certain people are more likely to get it and why certain medications work more than others.
According to Healthcare UK, a document released by the Department of Health, “Pharmaceutical companies recognise that currently their major treatments may only be effective in 30–60% of the population for these conditions”. Therefore, genomics provides the key to more successful medical care.
As you can appreciate now, MedTech is vast. We don’t think the 6 aspects chosen cover ALL of it, but we believe they have the scope to cover the majority of the field, which is why they have been selected.
However, what was extremely clear to see, was that personalised medicine is the key to providing better healthcare. The combination of the 6 Med Tech aspects working together is the best way for us to achieve personalised medicine. Therefore, shouldn’t you be taking a serious interest in MedTech?
