I have a habit of reading everything that falls into my hands. The range of information (driven by my internal need for access to data) that I have from various sources is becoming increasingly wide. The knowledge I gain allows me to connect more and more different dots from many fields.
In addition to modern technology, not since yesterday, I am also interested in medicine and how it affects the world around us. I often look into the medical press for doctors (taking them from my wife), where I read about reports on new therapies, research, or developments. The digital transformation that touches virtually all aspects of our lives is also happening in medicine, and today I’d like to talk about it.
Table of content
What is digital transformation (also in medicine)
Digital transformation is a technological, business, and above all, cultural transformation. It is based on three pillars, the change of which affects the holistic operation of the company. It usually concerns the work of individual units, the use of data, and the optimization of processes occurring within the organization.
Although it is tempting to focus only on the digital part, new platforms, or processes, we should not succumb to this temptation. We should not think that we will immediately increase quality, range of services, security, or productivity if we buy the software.
Digital transformation is about changing the way we think and work. Therefore it requires a thorough rethinking of business models and processes.
The first thing is strategy, then technology!
I talked more extensively about what digital transformation is in business as part of the “Entrepreneurial Summer” series that I had the honor of leading for Samsung Incubator. For those interested (only in Polish):
Artificial intelligence (AI)
It’s not hard to see that artificial intelligence, as in many other fields, has gained incredible momentum. Even before the 2017 pandemic, an Accenture report estimated that the market value of AI in health alone would reach $6.6 billion by the end of 2021. Insider Intelligence predicted that AI in healthcare will grow at an annual rate of 48% between 2017 and 2023. By 2025, the market value of AI-based tools in healthcare will exceed $34 billion, meaning that the technology will shape nearly every aspect of the healthcare industry.
Just machine learning alone can provide hospital staff with decision support based on existing data. It has become a daily reality that it improves the quality and efficiency of radiology departments and labs, mainly by reducing unnecessary repetitive tasks or eliminating errors caused by misreading data. Machine learning, with great probability, can also detect potentially dangerous situations like stroke. Thus, it can increase care priority for patients in whom it has identified a life-threatening episode. Predictive models demonstrate accuracy:
- 77% (for ventilator requirement) to 83% (for intensive care unit admission),
- and up to 87% for mortality.
Noteworthy examples include an AI that was able to identify signs that indicate long-term cardiovascular risk. It did this based on study results and their data from over 280,000 patients. The same AI then learned what patterns it should look for in retinal photos of people identified as being at risk. In the future, it will then be able to determine whether a patient belongs to this group based on the eye image alone. If this were approached traditionally, scientists would have to spend years coming to the same conclusions and manually analyze each retina, compare it to hundreds of others, and correlate it to the research findings.
In oncology, AI-based programs analyze terabytes of images representing different types of cancer to make highly accurate diagnoses and predict the best possible combinations of anti-cancer drugs based on the data.
AI can also aid preventive medicine or even help discover new drugs.
- 89% of therapies generated by machine learning have been found acceptable for treatment at the clinical stage,
- the radiotherapy process with AI compared to the conventional method (human-controlled) was 60% faster.
But that’s not all. According to Insider Intelligence, 30% of healthcare costs are linked to administrative tasks. The same is confirmed by a 2021 report from the Supreme Administrative Court, which shows that medical records and administrative work take up nearly one-third of medical consultation time. And during teleportation, these activities take up even more time. The AI can automate some of these tasks and, for example: take care of medical record-keeping; perform historical data analysis; or even, in the case of paid advice, invoice for the service.
It is predicted that by 2026, AI in healthcare will save, in the US alone, $150 billion per year.
Big Data in healthcare
Big Data is a term that refers to large, variable, and diverse data sets that are difficult to process and analyze yet valuable because they can lead to new knowledge.
Big Data-based solutions in marketing aggregate information from channels such as social media, online stores, and online transaction systems and identify patterns and trends that can be used in the future.
How can Big Data be used in medicine? For example, through software that, by analyzing patient’s documentation, will find any inconsistencies and correlations between a condition and the prescribed medications. Thus, the software will alert both the doctor and the patient when there is a potential risk of incorrect using drugs, interaction, or allergy.
In addition to patient data, you can also run predictions of what the rate of potential hospital admissions will look like for a given day or week. As a result, they will better manage inventory and employee vacations or staffing. They will also be able to plan for potential emergency room occupancy and manage it even better, such as reducing queues or waiting times for tests.
Analytics in Big Data is a complicated and complex process. It explores hidden patterns, trends, unknown correlations, or preferences, thereby helping physicians and organizations make informed clinical and business decisions. As the data shows:
- 50% of medical and life sciences companies report increased investment in data, compared to 22.4% of financial services companies,
- the Big Data Healthcare market was valued at $23,749.33 million in 2020 and is expected to reach $58,404.24 million by 2026.
Digital Twin
A digital twin is a virtual copy of real objects, systems, or processes. It is a combination of a physical object and its digital representation in virtual reality, realized thanks to the possibility of real-time processing data and constant updating of the state of objects and operations. The first practical definition of a digital twin came from NASA to improve the physical spacecraft model in 2010. Currently, the digital twin is most often used in manufacturing companies, where it is responsible for a virtual replica of events occurring in the factory in real-time. Thousands of sensors are placed on the plant floor, machines, or products, which are then used to collect all kinds of data such as environmental conditions, machine behavior characteristics, and the work performed. All this data is continuously transmitted to (and collected by) the digital twin.
This data is also used to map all processes, machines, or products and analyze how changing specific values in the environment or process will affect production.
In healthcare, many companies specialize in creating digital twins. They help transfer from the real world to the virtual one, for example, models of objects, supply chains, medical products, and even interestingly, whole body parts or organs. This allows us to:
- predict and identify bottlenecks in all our processes,
- model scenarios – e.g. surgical simulations,
- assist in medical education, or
- deliver better medical care.
Siemens is working on a digital heart twin to improve drug treatment and simulate cardiac catheter interventions. Startup FEops is creating a replica of a patient’s heart and combining it with AI-assisted analysis to improve the treatment of heart disease. Living Brain, meanwhile, is responsible for treating epilepsy and tracking the progression of neurodegenerative diseases. The company has also introduced similar designs for lungs, knees, eyes, and other organs.
And Sim&Cure is creating a digital twin to help neurosurgeons operate on aneurysms to improve planning and execution of minimally invasive catheter-based surgeries.
Swedish researchers are mapping mouse RNA to a digital twin. They are trying to predict the effects of different types and doses of drugs to treat arthritis. This procedure aims to personalize the diagnosis and treatment of humans using RNA.
The Digital Twins market is predicted to be worth $115.1 billion by 2035.
Treating patients with virtual (VR) and augmented (AR) reality
Virtual reality is a technology that generates a fully artificial environment. It includes images, sound, and sometimes even touch and smell. It is often used, for example, in games.
On the other hand, augmented reality combines the real and virtual world. Through glasses or devices (e.g., phone) on the image are usually superimposed 3D visualizations, with which the user interacts. We can, for example, check whether the shoes we buy online will look good on us and the cabinet will fit in the place where we would like to place it.
Virtual and augmented reality also has applications in medicine to improve teleportation and telehealth. It can be used not only to enhance patient-doctor contact but also to educate students (simulations of procedures or surgeries, distance learning, and conversations with specialists from around the world) and patients (better understanding of pending treatments and procedures), or to perform alternative therapies (currently used to treat long-term pain).
Only in surgery augmented reality can provide, among others, access to data and information that will always be in sight (the surgeon puts on special glasses that give him access to the data, virtual model of organs, or God forbid a tutorial on You Tube) and can be useful during treatments or procedures. And virtual reality can help, for example, in performing remote surgeries, where a specialized surgeon connects with a robot in another part of the world and performs the procedure.
The augmented reality segment in healthcare dominated the overall AR/VR market and accounted for the largest revenue share of 59.8% in 2020.
Pandemic resulted in revenue growth of 27.7% for this market.
The global AR/VR market in 2020, in healthcare alone, was valued at $2.0 billion and is expected to grow at a compound annual growth rate (CAGR) of 27.2% from 2021 to 2028. Thus, the market will be worth $9.5 billion by then.
Medical devices that you can carry with you, or the Internet of Medical Things (IoMT)
Companies in the sports industry have long since discovered the enormous potential that the Internet of Things (IoT) brings. Fitness bands, watches, shoes, clothing, special exercise devices, connectivity to equipment and entire ecosystems to extract and analyze data that, for example, personalize training. The same area is entering medicine in great strides.
The technology of “wearables” is an unlimited source of data that can be used for even better diagnosis. While the Holter monitor used to be innovative, today it’s an indistinguishable standard. Meanwhile, thanks to special devices or clothes, we can carry them with us all the time:
- heart rate monitors,
- sensors
- ecg monitoring, blood pressure,
- temperature,
- to detect, position, movement,
- dust, pollution, dust, allergens
- sweatmeters – used by diabetics to monitor blood sugar levels,
- smart pills (approved in 2017),
- oximeters – to monitor the amount of oxygen carried in the blood, often used by patients with respiratory diseases such as COPD or asthma,
- smart implants – the most popular are smart pacemakers
They can detect potentially dangerous situations, counter them, personalize healthcare, provide gamification elements, and save healthcare companies money. Health apps and wearable devices used for preventive care could save the U.S. healthcare system alone about $7 billion a year.
In the past, most patients went to the doctor once a year to get a checkup or only came in when something was ailing them. Today, the public’s increased awareness has led them to focus on prevention and demand information about their current health status. As a result, healthcare companies need to be proactive. Some are already investing in IoMT devices that can provide ongoing monitoring of high-risk patients to determine the likelihood of a severe health incident.
The IoT industry will be worth $6.2 billion by 2025. It is estimated that over 30% of the IoT device market share will come from healthcare.
- A study conducted by Augusta University Medical Center shows that IoMT devices reduced 89% of patient deterioration cases that were headed for cardiac or respiratory arrest,
- technology encouraged 75% of users to engage in their own health, and use of these devices by U.S. consumers alone increased from 9% to 33% in four years.
3D Printing
It’s impossible to underestimate the aid that has flowed from 3D printing companies to coronavirus-stricken hospitals in 2020. We’d be talking about even more damage if it weren’t for printed visors, respirator components, or masks.
However, 3D printing in medicine is much more important and offers many more possibilities than it might seem. It is used, e.g., in hospitals during surgeries, in surgeries (including dental surgeries – prosthetics, orthodontic appliances, prosthetic restorations), in the production of medical devices (e.g., hearing aids) or printing prostheses (including prostheses for children, where their rapid growth means that they can quickly outgrow traditional prostheses).
Anatomical models are considered one of the most popular applications of 3D printing in the medical industry. Image-based 3D printing technologies can produce models of, among other things, a patient’s organs or body parts or surgical tools needed to perform surgery. With the availability of medical-specific software and 3D printers, more and more hospitals are setting up 3D printing labs globally. If they do not have them, they can use the offer of companies and startups already present on the market for years. With these solutions, medical professionals can create highly accurate 3D printed models for preoperative planning. This allows surgeons to make better decisions about treatment and the surgery itself. Holding a fully dimensional organ and viewing pathology from different angles helps to understand its location better and plan the stages of removal. Add to this personalized surgical tools such as forceps, hemostats, handles, scalpels, or clamps and combine them with faster and less traumatic procedures. For example, 3D-printed blades are already streamlining the hip acetabular replacement process, reducing rejection rates from 30% to less than 3%.
The global 3D printing market in healthcare will grow at a CAGR of 17.5% over the next 5 years. And the global 3D printing medical device market was already valued at around $890 million in 2017. The market is expected to generate around $2.34 billion in revenue by the end of 2024.
Driving change
Healthcare has come to terms with it, too must enter the digital age. Digital technologies have constantly reshaped all industries and the human experience for years. Healthcare, too, has had to learn to adapt and understand that there is no future without technology. Currently, data shows that:
- 66% of healthcare executives say they will use the cloud within the next year and 96% in the coming three years.
- 81% of healthcare executives say the pace of digital transformation continues to accelerate in their organization.
However, many healthcare companies are still delaying the introduction of digitization into their organizations. Because of this, the gap between them and the leaders is growing by the day. In the future, these gaps may not be catchable. Leaders at the forefront of healthcare are prioritizing technological innovation. They are doing so primarily due to a changing world with increasingly different expectations.
Sources and supplementary materials:
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