Medtech companies have already transformed healthcare into a virtually unrecognizable service to what it was only ten years ago. But now, MedTech is playing an increasingly vital role in improving care and driving down costs in the industry. It’s doing so by reshaping the medical device sector in waves of new and exhilarating digital health solutions.
Healthcare companies need help to adapt to these changes. They need new talent with cutting-edge skills who can help them take the lead in the medical device industry—not just in harnessing the digital technologies that work with medical devices but in being a key player in the research and development of future solutions.
Where will the industry’s digital health solutions take us next? Read on to learn how the industry is changing and the people needed to deliver the future today.
Turning How Healthcare Does Business on Its Head
It’s not just the devices and the digital tools that control them which are changing. It’s also how the medical device industry does business that significantly affects the sector down the line. This is a big deal for an industry that is famously rigid and formal.
But these days, roughly 30% of deals within medical device and digital health solutions are breaking the traditional mold of only making deals within their sector. Now medical device and digital health segments are increasingly embracing digital innovations beyond their silo.
This is causing much more change than shifting how healthcare providers do business. The changes in how these sectors do business create a seat at the table for a new generation of innovators and collaborators. As a service, these changes are creating a new focus on:
- Strengthening personalized care offerings
- Growing business around connected care
- Transforming the delivery of healthcare with integrated solutions
- Expanding portfolios
- Building a connected infrastructure to bring meaning to valuable data
Providing Faster, More Personalized Care Anywhere and Everywhere
Demands from the consumer patient are changing how, when, and where healthcare providers can meet their needs. One key example is how common convenience and accessibility have become for patients to get the care they need. Patients now expect from their provider’s services that can be accessed quickly and easily, either in person or through digital channels. This is evident in the growth of retail clinics, urgent care centers, and telemedicine, which allow patients to receive care outside of traditional hospital settings.
The demand from patients has only grown in the medical device industry. It has caused an explosion of growth and innovation in:
- Consumer-Centric Design: More medical device manufacturers are designing products that are easy to use, intuitive, and appealing to patients. This includes devices that are more compact, portable, and aesthetically pleasing.
- Patient Engagement and Empowerment: Patients are seeking out devices such as wearables, mobile apps, and remote monitoring devices that allow them to track their health data and communicate with their healthcare providers.
- Data Analysis: Devices and artificial intelligence (AI) are doing the majority of data analysis with deep learning algorithms and graphics processing of genetic information and other health metrics that often outperform human intelligence in providing more targeted, individualized treatment.
Artificial Intelligence and Medical Devices
The term “AI” might be a little overused these days.
A more applicable term in the medical device field may be “machine learning,” which focuses on developing algorithms that enable machines to learn and adapt to new data without the need for explicit programming. “Deep learning” is a further extension of this concept, which involves using artificial neural networks with multiple layers to simulate human thought processes.
Several types of medical devices use machine or deep learning, which are now critical to modern healthcare, including:
- Imaging devices such as CT and MRI scanners that use machine learning algorithms to improve image quality and reduce radiation exposure.
- Diagnostic devices such as lab-on-a-chip systems that use machine learning to analyze patient samples and make diagnostic decisions.
- Medical robots and surgical assistants that use machine learning to navigate and manipulate instruments in the operating room.
- Wearable devices such as smartwatches, fitness trackers, and remote monitoring devices that use machine learning to monitor patient vital signs and detect early warning signs of disease.
- Clinical decision support systems that use machine learning to analyze patient data and provide treatment recommendations to healthcare providers.
- Drug discovery and development systems that use machine learning to analyze large amounts of data to identify new drug targets and optimize drug design.
- Natural Language Processing (NLP) based clinical documentation and coding systems that use deep learning to automatically extract information from patient charts and medical records.
- Computer-aided detection and diagnosis (CAD) systems for medical imaging, such as mammography, CT, and MRI, use deep learning to assist radiologists in detecting and diagnosing diseases.
AI seems like all the rage these days. It is, and it isn’t.
Some companies will design a toaster that will turn off when it senses burning. The hype in these cases seems to be around mislabeling highly technical devices as “AI” as a marketing gimmick. But in the medical device sector, the hype is not only well-founded, but difficult to overstate its influence and reliance within MedTech and related sectors
Become a Leader in Digital Health Solutions With HCRI
The vast potential for the change digital health solutions can bring is exciting when you consider just how much MedTech has evolved healthcare in recent years.
If you want your business to do more than just keep up, we can help you lead by hiring the medical device talent who can take you there. Contact us today, and let’s discuss the future.