Clinical-grade remote patient monitoring (RPM) is a solution that involves the secure transmission of medical data collected on devices, via telecommunications services. It's enabled through text, sound, images or other digital media used for the prevention, diagnosis, treatment and follow-up of healthcare patients.
The applications of emerging technologies such as the Internet of Medical Things (IoMT), Artificial Intelligence (AI), and Big Data analytics are enabling vendors to develop new use cases for remote patient monitoring.
Remote Patient Monitoring Market Development
In recent years, venture capitalists have increasingly invested in start-ups with competencies in these areas, especially integrated and lower-cost monitors and sensors. With this development, RPM will help to shift some healthcare services from the hospital to the home.
According to the latest market study by Frost & Sullivan, RPM is forecast to become a mainstream medical service, with related revenues growing to $1.15 billion in 2023 at a strong CAGR.
"AI technology is poised to become more visible across the healthcare process and clinical workflows. There will be significant opportunities in the virtual assistant space and other data-driven AI applications," said Chandni Mathur, an analyst at Frost & Sullivan.
HealthTech vendors are also choosing the bring-your-own-device model (BYOD), giving people the flexibility of using their own hardware. Data-driven technologies such as predictive analytics and data visualization are also gaining momentum.
"Europe is an enthusiastic adopter of RPM solutions, with the highest growth expected from the United Kingdom, Germany, the Netherlands, and Sweden," noted Mathur.
Furthermore, the imminent spate of regulatory approvals across Europe for consumer-grade wearables to monitor vital signs will prove a huge growth driver over the next five years.
Outlook for Remote Patient Monitoring Growth
Going forward, it will be essential for HealthTech vendors to further explore the combination of emerging technologies to deliver innovative new services. For further growth opportunities, RPM vendors should:
The applications of emerging technologies such as the Internet of Medical Things (IoMT), Artificial Intelligence (AI), and Big Data analytics are enabling vendors to develop new use cases for remote patient monitoring.
Remote Patient Monitoring Market Development
In recent years, venture capitalists have increasingly invested in start-ups with competencies in these areas, especially integrated and lower-cost monitors and sensors. With this development, RPM will help to shift some healthcare services from the hospital to the home.
According to the latest market study by Frost & Sullivan, RPM is forecast to become a mainstream medical service, with related revenues growing to $1.15 billion in 2023 at a strong CAGR.
"AI technology is poised to become more visible across the healthcare process and clinical workflows. There will be significant opportunities in the virtual assistant space and other data-driven AI applications," said Chandni Mathur, an analyst at Frost & Sullivan.
HealthTech vendors are also choosing the bring-your-own-device model (BYOD), giving people the flexibility of using their own hardware. Data-driven technologies such as predictive analytics and data visualization are also gaining momentum.
"Europe is an enthusiastic adopter of RPM solutions, with the highest growth expected from the United Kingdom, Germany, the Netherlands, and Sweden," noted Mathur.
Furthermore, the imminent spate of regulatory approvals across Europe for consumer-grade wearables to monitor vital signs will prove a huge growth driver over the next five years.
Outlook for Remote Patient Monitoring Growth
Going forward, it will be essential for HealthTech vendors to further explore the combination of emerging technologies to deliver innovative new services. For further growth opportunities, RPM vendors should:
- Partner with health systems in different countries to deploy RPM solutions for data gathering and, eventually, precise risk stratification.
- Integrate monitoring data from disparate medical-grade wearables or data collection tools into a single platform.
- Collaborate with telemedicine providers to offer a holistic service.
- Offer a continuous RPM system coupled with predictive AI that provides actionable insights when required and reduces manual intervention.