A Vital Priority: Why AI-Driven Virtual Cardiac Care is a Top Investment Area for Providers

By Stuart Long, CEO, InfoBionic
LinkedIn: Stuart Long
LinkedIn: InfoBionic, Inc.

Healthcare IT leaders are continuously balancing the need to improve patient care, optimize operational efficiency, secure data, and manage costs. Prioritizing the right digital investments is crucial, with significant implications for clinical and financial outcomes.

Research shows healthcare IT investment continues to grow, with fragmented focus areas. A recent survey found that 75% of healthcare providers increased their IT budgets from 2019 to 2023, prioritizing cybersecurity, EHR modernization, digital care, advanced analytics, artificial intelligence (AI), and machine learning (ML).

Tremendous potential lies in the space between these investment areas, such as virtual telemetry solutions, which combine elements of digital care, advanced analytics, and AI in one high-impact investment. When weighing their digital priorities, IT leaders can maximize impact by focusing on service lines with an outsized need for improvement. Cardiology is a prime example, as it impacts one in two Americans but remains inefficient due to complex care and specialized procedures. Cardiovascular diseases collectively cost the U.S. healthcare system over $200 billion annually, highlighting significant opportunities for savings and optimization.

An Investment Worth Making: Virtual Care, Virtual Telemetry, and AI Enter the Cardiology Clinic

While the possibilities for healthcare innovation are virtually limitless, one intersection of digital technologies has taken center stage in the cardiac specialty: the powerful combination of virtual cardiac care, virtual cardiac telemetry, and AI-enabled analytics, which usher in a new era of virtual-first interventions. Let’s take a closer look at these digital advancements.

Virtual cardiac care has redefined care settings beyond traditional telehealth, enabling providers to deliver the richness and quality of in-person care interactions from nearly anywhere. Virtual-first care interactions rely heavily on the availability of high-acuity data, and modern virtual telemetry solutions make hospital-grade diagnostic data possible outside the clinic.

With virtual telemetry comes a massive amount of data for processing and analyzing, which is where AI-enabled analytics comes in. AI-enabled algorithms support clinicians by rapidly identifying patterns and anomalies that might otherwise be difficult for the human reviewer to decipher. These insights can be used to diagnose conditions, anticipate patient complications, and personalize treatment plans.

These technologies, individually valuable, are even more impactful together, with the potential to transform cardiac care’s efficiency and effectiveness. Let’s look at some of their key benefits.

Earlier Interventions
Virtual-first care interactions, supported by rich diagnostic data, enable providers to intervene before conditions worsen. The early detection and treatment of cardiac issues can prevent complications, reduce hospital admissions, avoid expensive emergency care, and improve patient outcomes. In fact, one study found that remote patient monitoring (RPM) reduced the time to detect decompensation in heart failure patients by up to 50%, allowing for earlier intervention and potentially preventing hospitalizations.

Time Savings
Automating data analysis through AI and remote telemetry significantly reduces clinicians’ time reviewing and interpreting data. Studies have found that implementing AI in monitoring and treatment plans can save 21.67 hours per day per hospital in the first year. This optimization of clinical resources empowers providers to focus more time on patient care and less on administrative tasks, enhancing care quality and reducing the dire effects of a mounting cardiologist shortage.

Enhanced Patient Engagement
Virtual cardiac care facilitates better patient engagement by providing easy access to healthcare services. Patients can attend virtual appointments, access their health data, and communicate with care teams from anywhere. This convenience, coupled with an intuitive user experience, encourages patients to be more proactive in managing their health, leading to better adherence to treatment plans and improved health outcomes. One study showed admissions for chronic care complications were reduced between 19% and 41% due to RPM.

Cost Efficiency
According to new research, studies project that AI adoption in healthcare could save the industry up to $360 billion annually. By reducing complications and hospital admissions and optimizing resource allocation, these technologies help manage the high costs associated with cardiac care. The scalability of virtual care solutions allows for more efficient use of resources, further enhancing cost efficiency. Additionally reported, physician groups could save 3-8% of their total costs, amounting to $20-$60 billion in savings in the next five years, while hospitals could save 4%-11%, or $60-$120 billion.

Improved Data Accuracy and Security
Secure data management is crucial in maintaining patient trust and complying with healthcare regulations. Advanced telemetry and AI analytics ensure the accurate collection and interpretation of patient data; for example, one deep-learning AI tool outperformed radiologists in detecting structural abnormalities associated with heart failure on chest X-rays. These technologies enhance data security by minimizing manual data handling and reducing risk. AI’s integration into healthcare could potentially reduce 86% of errors made by healthcare workers, possibly saving 250,000+ lives each year.

The Bottom Line: Embracing a New Era of Cardiac Care

The integration of virtual care, advanced remote telemetry, and AI-enhanced analytics is already revolutionizing cardiovascular disease management and treatment, with its full potential only beginning to unfold. These technologies promise to enhance the accuracy and timeliness of diagnoses, enable personalized treatments, and transform the cardiac specialty from an epicenter of complexity into a highly efficient and data-driven healthcare service line.