Cardiac Health is Top of Mind. The Quest to ‘Zero’ Avoidable Cardiac-Related Deaths Continues.
Cardiac disease is one of the top health concerns in the United States. According to the Centers for Disease Control and Prevention (CDC), heart disease remains the leading cause of death for both men and women. As this major public health issue affects a large portion of the population, it has led to a significant focus on heart health in the public and private sectors.
Given its prevalence, it’s no surprise cardiac health is top of mind for clinicians, even as recent statistics are increasingly positive. Heart attacks have seen a downward trend thanks to advancements like improved emergency response, better detection, public health initiatives, and lifestyle interventions. Rates for heart disease decreased from a peak of 307.4 per 100,000 people in 1950 to 134.6 in 1996—a decline of 56%. This trend continues today, decreasing from 182.8 per 100,000 in 2009 to 161.5 in 2019.
Even with the marked decrease in heart attacks, there’s still progress to be made. Research suggests preventable cardiac deaths have various causes, including poor healthcare access, limited heart health awareness, inadequate preventative care, and inefficient emergency response. These challenges are compounded in ‘medical deserts,’ where resources are scarce. A GoodRx whitepaper notes that 80% of the population lacks adequate access to healthcare, which results in significantly poorer cardiac outcomes.
Out-of-hospital cardiac arrest (OHCA) occurs at a rate of ~356,000 annually, with nearly 90% fatal. Meanwhile, the survival rate to hospital discharge after EMS-treated OHCA is only about 10%. This suggests that preventable cardiac death is still a major concern, as even a single avoidable death is one too many.
Medical Deserts, Virtual Telemetry, and the Power of AI to Enable Access and Agility at Scale
Instead of accepting current cardiac outcomes as a reality, providers can be inspired and motivated by the ‘zero’ milestone, a hypothetical state in which the number of avoidable cardiac deaths reaches zero. Naturally, all providers aspire towards such a vision, but the question remains: Is it achievable? And if so, how?
One way to revitalize ‘medical deserts’ and amplify proactivity in cardiac interventions is through virtual telemetry, which brings higher acuity levels of monitoring to patients regardless of location—and due to the communication nature of telemetry’s monitoring and transmitting data in near real-time, as cardiac events are occurring, it enables providers faster access to analyze and act with unprecedented speed. Virtual telemetry has the potential to be truly transformative, but tapping into its full potential is not without challenges. As cardiologists continue to scale higher levels of acuity monitoring across patient populations, they face a mounting data problem.
Analyzing vast and nuanced cardiac datasets, which most frequently do not represent a major cardiac event, has historically been a hurdle in unlocking the full potential of virtual telemetry. How can providers wade through all of the data, uncover significant trends, and take preventative action? The answer is AI-enabled analysis support. And this isn’t just another AI buzzword—it has tangible and transformative applications in virtual telemetry cardiac use cases.
While there is perhaps no condition that has impacted more lives than heart disease, there is possibly no technology that has captivated public attention more than AI. Let’s examine AI’s potential to transform virtual telemetry’s hurdles into strengths for healthcare organizations.
Unpacking Virtual Telemetry Challenges
AI accelerates healthcare innovation in exciting new ways and has the potential to revolutionize heart health. To understand AI’s power in cardiac care, we must first examine some of the key challenges continuing to plague remote patient monitoring (RPM):
- Intermittent symptoms: When reviewing data from a specific period through discrete analysis, providers risk missing critical pieces of the picture. The signs can be even more nuanced when dealing with preventative care, requiring a longer monitoring period to recognize and understand anomalies outside of major events.
- Contiguous, not continuous monitoring: While some solutions on the market claim to offer “continuous” monitoring, these solutions often suffer from a lack of continuity. This is due to breaks in connectivity from incomplete data transmission to having to remove the device to charge it, thus creating gaps in monitoring, all in addition to a variety of other factors that make it hard to understand the full picture and improve the precision and timeliness of care.
- Data overload: When continuous monitoring is available, the amount of data generated is simply too great to be accurately analyzed in a timely fashion—at least not without additional technology that can prioritize and surface insights. Data overload stands in the way of proactive and timely interventions.
- Provider resource constraints: The data challenge is intensified by the ongoing shortage of providers and time constraints among busy cardiologists lacking time for manual analysis. A recent report highlighted a shortage of 1,600 general cardiologists and 2,000 interventional cardiologists. To meet the expected demand, the number of cardiologists will need to double by 2050.
- Data acuity inadequacies: In many cases, even continuous remote patient monitoring data is limited in acuity. Higher acuity levels are especially valuable when diagnosing more nuanced conditions in their early phases or that occur outside an event.
- Poor technology integration: There’s often poor integration between RPM platforms and other systems inside the hospital—including electronic health records (EHR), telehealth solutions, data analysis tools, patient portals, and many more. Disparate systems result in data leakage, gaps, and latency—all of which challenge hospitals to realize the full potential of RPM.
Taking the Challenges Heart-On: The Power of AI-Enabled Analysis
AI-enabled analysis represents a seismic shift in addressing the limitations of RPM, turning obstacles into opportunities for improved cardiac care. Here’s how AI is making a difference:
- Overcoming intermittent symptoms and data limitations: AI algorithms excel at detecting patterns that may be indiscernible to the human eye. By analyzing long-term data trends, AI can identify subtle changes or early warning signs of cardiac issues, even when symptoms are intermittent or elusive. This continuous, nuanced analysis helps in early detection and intervention, potentially preventing major events.
- Transforming contiguous into continuous monitoring: Virtual telemetry solutions must evolve into being able to support both contiguous and continuous monitoring. Inside a facility with robust communications like Wi-Fi, these platforms’ AI-enabled analysis enables data to be transmitted continuously and then compensates in remote, virtual, or mobile environments by seamlessly switching to cellular and then to Wi-Fi, should it be supported in a patient’s home. Further solutions must utilize intelligent charging strategies to eliminate potentially dangerous gaps in monitoring, allowing the patient to wear the device at all times and maintain connectivity as their communications environment changes, thus ensuring a more consistent monitoring capability—and never missing a beat.
- Managing data overload: With the ability to process vast amounts of data quickly, AI systems can sift through the excess to find meaningful insights and present them to the human cardiologist to empower decision-making. AI-enabled analysis can also prioritize critical information, surfacing urgent insights and allowing cardiologists to focus on the most important information first. In addition, AI can dynamically filter false alarms and notify healthcare providers of patterns or events to be addressed.
- Easing provider resource constraints: It’s no secret that healthcare teams are experiencing burnout in their day-to-day practice. By automating routine data analysis, AI significantly reduces provider workloads. This efficiency is vital in the face of ongoing staff shortages and a high demand for cardiac care. AI offers quick, accurate, and actionable insights, allowing providers to focus on patient care rather than data analysis.
- Enhancing data acuity: Enabled by modern RPM solutions, which provide far greater acuity than previously possible, AI’s advanced algorithms can detect nuances in data that indicate early stages of cardiac conditions. In addition, by its very nature, AI analysis continually improves over time, leading to higher levels of analytical acuity. This high level of data acuity is essential for diagnosing conditions before they escalate, aiding preventative care and better management of chronic heart diseases.
- Improving technology integration: AI facilitates better integration of RPM with other hospital systems like EHRs and telehealth solutions. It can harmonize data from disparate sources, establishing a unified and comprehensive view of patient health. This integration is essential to enabling precision medicine and personalized care.
The above points are further supported by continuous improvements in virtual telemetry that enhance the continuity, acuity, and timeliness of RPM cardiac data. And let us not forget the power of AI-enabled analysis and virtual telemetry to simultaneously advance healthcare’s most critical goals: improving the quality of the patient experience, supporting population health, lowering per capita costs (via reduced readmissions, quicker discharges, and less costly care), and ultimately improving patient outcomes (via a lower probability of fatal cardiac events).
The Future of Cardiac Care is Here: AI-enabled Analysis and Virtual Telemetry are Leading the Way
Virtual telemetry plays a starring role in the healthcare AI revolution by providing AI models with the continuous, high acuity, and near real-time data needed for analysis. As the industry continues to navigate AI’s utility and long-term role, AI-enabled analysis in RPM represents a tangible and highly valuable application of AI that is accessible to healthcare providers today.
As healthcare embraces AI’s many enhancements to patient care, it must do so with an eye on quality, data integrity, security, compliance, and innovation—the essential tenets to successfully adopting healthcare technology.
As for AI-enabled analysis in cardiology, providers can start by finding and embracing a modern virtual telemetry platform that prioritizes data acuity and delivers tools for AI-enabled analysis. With the right platform and a shared vision, providers will be well on their way to reducing—and hopefully, one day eliminating—avoidable cardiac deaths.
About Stuart Long
Stuart has been the CEO of InfoBionic 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. Before joining InfoBionic, he was CEO at Monarch Medical Systems, LLC, and global chief marketing and sales officer for CapsuleTech, Inc.