As more and more healthcare activities take place from home, continuous monitoring solutions—including those that can track a patient’s status overnight—and new technologies, such as artificial intelligence (AI) will be critical to support communications between providers and patients. Solutions that offer continuous and passive monitoring will play a critical role in helping to fill the gaps, particularly in assessing patient deterioration or important changes in health conditions.

As of April 2021, 66% of U.S. broadband households reported that they are familiar with telehealth services compared to 50% in May of 2020. The use of telehealth services has more than quadrupled in recent years, increasing from 15% in 2019 to 64% in 2021.

Remote care in the home relies both on the quality of patient monitoring and on the insights provided to the care team. There is a real danger that data overload and alert fatigue will undermine otherwise well-designed remote patient monitoring (RPM) and Hospital at Home programs. The software platform and algorithms tasked with integrating and evaluating data must identify the data that matters, when it matters.

Increasingly, RPM platforms apply AI to sort through the noise. The use of predictive analytics and machine learning algorithms in health care can turn real-time data into actionable and potentially life-saving insights and diagnostic support. Examples of use cases powered by AI and algorithms include the ability to algorithmically compare patient trajectories, proactively identify and avoid health crises, triage at-risk patients, diagnose unidentified and undiagnosed medical conditions, and predict falls or mobility declines in the elderly, among many others.

Predictive analytics can proactively flag at-risk patients for an intervention prior to a health incident. These systems can integrate with EMRs via the HL7’s Continuity of Care Document standard, Admit Discharge Transfer feeds and custom field integrations. This lessens clinician reporting fatigue and allows event-based triggers to occur via the provider’s own systems.

Just retrieving measurements is only scratching the surface of what connected health solutions can do. AI and machine learning, as well as highly tested and clinically proven algorithms, vastly increase the value proposition of connected health technologies and platforms. They enable a wide variety of new use cases, provide decision support tools for clinicians and reduce administrative burden. They translate data into meaningful information and can even be shared back as insights or educational material for patients and family caregivers to understand their own health status.

Remote Health Care is Evolving

Models of remote health care in the home are both scaling and evolving. Innovative players in this space are rolling out well-designed and user-intuitive health IoT solutions, pulling in data from sensors and devices in consumers’ homes, and building intelligent, integrated platforms that better serve their clients and patient populations.

Changes in reimbursements have also helped accelerate the adoption of new approaches to monitoring that, in lieu of sending data straight to medical records and putting the burden of viewing and interpreting data on clinicians, call on intelligent platforms to interpret the data and escalate to clinicians if appropriate.

The rollout of 5G technologies can appease increasing consumer and industrial demand for improved connectivity solutions and networks; 5G technologies will ultimately ease the burden on mobile networks and smart homes while providing much quicker broadband speeds and more reliable connectivity. These improvements will target the billions of new connected health devices that will connect to operators’ networks over the next decade and beyond. With 5G implementation, connected markets that are reliant on both high and low bandwidth connectivity will experience disruption.

The rollout of 5G services may allow operators to gain market share in the competitive mobile market, as well as gain a foothold in the home broadband market. Loss of connectivity with smart devices is a consistent pain point voiced by device owners, and cellular devices that can offer standalone plug-and-play connectivity with little to no downtime will be compelling.

Health care has a need for noninvasive solutions that enable providers to proactively understand and manage healthcare events for consumers. With new technologies such as AI and advanced connectivity, the industry has an opportunity to engage consumers with a message of empowerment: virtual care solutions enable consumers to care for themselves and family members at home.