Today’s hospital is an epicenter of medical device innovation, with modern devices showing greater acuity, capabilities, and diagnostic accuracy than any generation before them. While medical devices are essential to care delivery inside the hospital, they are perhaps even more integral to care that is delivered outside of the hospital’s walls.
Along with the rising sophistication of inpatient medical devices, data acuity in remote patient monitoring (RPM) devices is also on the rise. Virtual telemetry, for example, enables the continuous collection of health data like heart rate and blood pressure from nearly anywhere a patient may be located.
The applications of RPM are both numerous and diverse. Insider Intelligence estimates that 70.6 million U.S. patients, or 26.2% of the population, will be using RPM by 2025. But this utilization metric is just the beginning. Wearable RPM devices are growing increasingly sophisticated through the integration of advanced technologies like artificial intelligence (AI) and machine learning (ML), which continue to multiply their potential applications and quantifiable impact. For example, research has shown that the use of RPM devices can significantly reduce systolic blood pressure and diastolic blood pressure compared to typical care and self-monitoring alone for hypertension.
Advanced, AI-enabled RPM devices require us to reframe our understanding of the medical device, expanding our view beyond the physical wearable to include the sophisticated analytics that bring its data to life. In this article, we will explore how the marriage of high-acuity virtual telemetry devices and AI-enabled analytics in cardiology is already transforming the timeliness, efficiency, effectiveness, and accessibility of care while forever redefining the medical device itself.
The Anatomy of the High-Acuity Virtual Cardiac Telemetry Device
Before we look ‘beyond the device,’ let’s first explore how the powerful capabilities of high-acuity virtual cardiac telemetry devices make effective RPM possible. These innovative devices are drastically different from the traditional cumbersome, wired monitoring equipment of yesterday. Their design ensures the delivery of high-acuity, up-to-the-minute data, which is essential to support AI-enabled analytical models. High-acuity virtual telemetry devices uniquely offer:
- Near-immediate data transmission. Near real-time data enables providers to act at a moment’s notice and it feeds AI models with a degree of timeliness that is essential to the delivery of proactive, effective care. For example, when supported by near-immediate data transmission, AI-enabled analytics enables multi-class arrhythmia detection with accuracies above 99% in controlled test datasets.
- Continuous connectivity. Modern virtual cardiac telemetry devices offer reliable Bluetooth or Wi-Fi connectivity as they travel with the patient everywhere they go. Long battery life and low latency minimize delays and eliminate blind spots that have historically hindered the cardiologist’s point of view. Connectivity is directly correlated to data acuity, ensuring that all of the data is captured all of the time.
- Multiple test types in a single device. These devices give providers full diagnostic autonomy and the ability to choose which diagnostics are right for each patient, with multiple available test types like Holter and Event. They can conveniently combine multiple test types in one single device by integrating various sensors and technologies to simultaneously measure and transmit diverse physiological data such as heart rate, blood pressure, oxygen levels, and more.
- Unobtrusiveness for the patient. Comfortable and easy to use, next-generation devices empower patients to manage their health more proactively and easily, which leads to better adherence to treatment plans and improved health results. One study found that RPM generates improved compliance and engagement, with 80% of patients considered well-engaged and 70% following the instructions issues by their practitioner.
- Exceptional data acuity. The ability to capture every single beat provides a level of acuity that has never before been possible in remote cardiac monitoring. But as the acuity of remote data inches ever closer to the acuity of in-hospital data, providers will naturally find themselves with a glut of cardiac data. That brings us to our next point—how to effectively manage and leverage this vast amount of data.
AI as an Extension of the Medical Device
Unsurpassed data volume is a hallmark of the next-gen remote patient monitoring device, which means that the device by itself is not sufficient to derive value in its intended use case. Instead, we must expand our view of the device to include the sophisticated machine learning algorithms that power its models. It is at this intersection of the device and the model where transformation truly occurs.
AI algorithms take the data collected from remote patient monitoring devices and analyze it by first processing and filtering the raw data to eliminate irrelevant or redundant information. They then use machine learning models to identify patterns, trends, and anomalies within the data, such as irregular heartbeats (i.e. signs of arrhythmia) or unusual blood pressure levels. The algorithms compare current data against historical data to detect significant changes and predict potential health issues.
These insights are then presented to cardiologists and other clinicians in an actionable format, including dashboards and alerts, which enable them to make informed decisions, initiate timely interventions, and personalize patient care plans based on near real-time, data-driven insights.
AI-enabled analytics not only solve the data volume challenge presented by high-acuity devices, but they also raise the bar for detection and diagnostic accuracy well beyond what is possible with a human reviewer alone.
High-Acuity Virtual Telemetry Devices Empowered by AI-Enabled Analytics: Exploring the Benefits
The marriage of high-acuity virtual telemetry devices and AI-enabled analytics redefines the medical device forever and unlocks transformative benefits for patients and providers alike.
In fact, the continuous transmission of high-acuity data offered by virtual telemetry devices joins forces with the continuous analysis provided by AI-enabled analytics to enable continuous improvement—which is an essential prerequisite to the widespread transformation of cardiac care. A new generation of AI-enabled RPM devices can surface predictive indicators of cardiac conditions and events, some of which have yet to be recognized or referenced in existing cardiology literature.
Additionally, AI-powered RPM devices can dramatically reduce healthcare costs across all service lines. A Deloitte Center for Health Solutions report estimates that utilizing RPM can provide an annual savings of $1,054 to $1,950 per patient, and when applied across the national population, this could amount to $5.4 to $9.9 billion saved annually. Additionally, AI could save the U.S. up to $360 billion annually if adopted more widely in healthcare, according to a report from McKinsey and Harvard.
Embracing the Future of the Next-Gen Medical Device
The future of patient care is bright, and its luminescence is fueled by a new generation of medical devices that combine both wearable technology and AI algorithms in a fully integrated way.
As we advance into the future, the convergence of AI with high-acuity remote monitoring devices is redefining the medical device itself—transforming it from a mere data collection tool into a powerful catalyst for predictive, personalized care.
In this exciting new era, remote monitoring devices bring the care setting to life wherever the patient is located, while AI acts as a force multiplier, enhancing clinical accuracy, efficiency, and insight. Together, these technologies enable cardiologists and other clinicians to make the most informed, timely, and data-driven decisions, ultimately reshaping the way we understand and deliver healthcare in cardiology and beyond.
To learn more about AI-enabled virtual cardiac telemetry, visit https://infobionic.ai/.
Editor’s Note: Stuart Long has been the CEO of InfoBionic.Ai since March 2017. He underscores the company’s commitment to widespread market adoption of its transformative wireless remote patient monitoring platform for chronic disease management. With more than 25 years of experience in the medical device market, Stuart brings expertise in achieving rapid commercial growth.