Moving Toward Healthcare Centered on Signals

Moving Toward Healthcare Based on Signals

In the ever-evolving landscape of healthcare, a shift towards proactive care is gaining momentum. This approach, which aims to reduce costly hospitalizations and improve performance in value-based care models, is expected to revolutionize the industry.

At the heart of this transformation lies a proactive, signal-based model of care. By using physiological and behavioral indicators for early intervention, healthcare providers can anticipate and prevent health issues before they escalate. This approach, contrary to the traditional reactive model, operates on insight rather than hindsight.

The proactive care movement is backed by recent federal actions. Initiatives like the AI Action Plan and new interoperability policy group efforts are aimed at reducing barriers and enabling data-driven approaches to expand care access. Emerging interoperability agreements, such as the Trusted Exchange Framework and Common Agreement, can simplify data flow across disparate systems.

Investment in AI and analytics is suggested as a more beneficial allocation of resources. These technologies can predict deterioration and reduce long-term utilization. AI can synthesize data streams from multiple sources to identify patterns and trends imperceptible to human clinicians. A virtual-first approach is essential, relying on AI-driven triage and agentic AI bots to alert healthcare professionals only when a patient's condition deviates significantly from their norm.

Wearable devices, such as those provided by companies like Omron, Samsung, Med-Watch, and others, play a crucial role in this new paradigm. These devices can track daily movement patterns and blood pressure, providing valuable data for proactive care.

However, privacy and security concerns require robust safeguards for patient data. HIPAA and business associate agreements must be addressed to ensure the protection of sensitive information.

Successful proactive care programs share common traits: early intervention through continuous monitoring, cost-effective data acquisition, consistent patient engagement, patient-centered design, clear clinical goals, adequate follow-up, and teams that act on data. Programs such as remote patient or therapeutic monitoring can qualify for reimbursement through current procedural terminology (CPT) codes, creating an immediate revenue stream.

The acceleration of proactive care depends on the use of non-regulated data sources, such as consumer wearables, for trend analysis rather than diagnosis. Quick wins in facilitating this transformation can be achieved by acquiring observational data from tools patients already use, such as smartphones, connected watches, or voice biomarker technologies, and applying AI to detect trends.

However, it's important to note that signal-based care may deliver limited ROI if implemented too narrowly, targeting only populations of people who are unlikely to generate significant healthcare costs. The ongoing physician shortage in the U.S. can be addressed through a shift towards proactive care, allowing clinicians to focus their attention where it is most needed.

The end goal of proactive care is to make better decisions earlier, with less burden on both patients and providers, shifting from reactive to proactive care. Long-term investments should focus on AI platforms that can integrate varied data streams, support scalability, and adapt as new devices enter the market.

Kent E. Dicks, CEO of Life365, a digital health company specializing in Remote Patient Monitoring (RPM) and AI-powered analytics, is at the forefront of this revolution. His company focuses on precision process control and healthcare technology innovation.

Access barriers, such as broadband, smartphones, or digital literacy, can widen the care gap when advanced digital tools are deployed without considering them. Federal programs, including a $50 billion allocation for rural digital health over the next five years, aim to help close the digital divide.

Excessive investment in fee-for-service infrastructure is discouraged, as it encourages reactive care rather than proactive interventions. The objective should not be just to generate more data, but to make better decisions earlier. In a system shaped by insight rather than hindsight, the real victory lies not in treating disease, but in anticipating and preventing it.