Technology Assessment

The technological architecture of Connected Health is evolving from simple connectivity—where devices merely transmit data—to intelligent autonomy, where systems analyse, predict, and increasingly act upon that data. This section assesses the critical technology stacks driving this transformation for the 2025-2030 period.

Forecasting Technical Evaluation

In the context of Connected Health, this implies that future assessments cannot look at a device in isolation. There is much to be learned from networking around the multiple approaches to the evaluation of the impact of healthcare technology infrastructures.

The forecast suggests that successful technology assessment will depend on interoperability between these diverse fields. An advantage of this approach is that it facilitates collaboration with community interest companies and not-for-profit initiatives. However, a disadvantage can be the complexity of aligning technical specifications with human factors, requiring rigorous testing to ensure the technology supports rather than hinders the patient care pathway.

The Internet of Medical Things (IoMT)

The Internet of Medical Things (IoMT) serves as the sensory nervous system of Connected Health. The market for these devices is projected to grow from approximately USD 230 billion in 2024 to nearly USD 660 billion by 2030, driven by the integration of telehealth services and the rising demand for remote patient monitoring.

A critical trend in this domain is the blurring line between consumer electronics and medical devices. We are witnessing the transition of wearables from fitness trackers to clinical-grade tools. Devices are now capable of continuous, accurate monitoring of vital signs such as blood oxygenation, glucose levels, and cardiac rhythms. This shift is pivotal for the viability of "Hospital at Home" models, where acute care is delivered in a residential setting. For such models to be safe, clinicians need ICU-level data reliability, which the new generation of FDA-cleared wearables provides.

Looking toward 2030, the form factors of IoMT will evolve further. We anticipate the proliferation of "smart implants"—orthopaedic, cardiac, and neurological devices that transmit real-time performance data from within the body. Emerging research in nanotechnology also points to the feasibility of ingestible sensors (smart pills) for real-time gastrointestinal diagnostics, moving monitoring from the skin's surface to the body's interior.

However, this exponential growth in devices creates a "data deluge." A single patient in a connected ICU environment can generate millions of data points daily. The challenge for the 2025-2030 period is not data collection, which has become commoditized, but signal detection. Without advanced analytics, this data creates "noise" rather than insight, leading to alarm fatigue among clinicians—a critical safety issue where desensitized staff may miss genuine emergencies.

Artificial Intelligence and Generative AI

Artificial Intelligence (AI) is the "brain" processing the sensory input from the IoMT. The integration of Generative AI (GenAI) marks a discontinuous leap in capability, moving beyond predictive analytics to content generation and complex reasoning.

Generative AI Use Cases:

• Clinical Administration and Documentation: GenAI is being deployed to automate the creation of clinical notes, discharge summaries, and insurance pre-authorisations. This application directly addresses clinician burnout by removing the "pajama time"—the hours spent on documentation after shifts—that drives workforce attrition.
• Synthetic Data and Digital Twins: By 2030, "Digital Twins"—virtual replicas of patient physiology—will be used to simulate treatment responses before administering therapies to the actual patient. This capability, driven by GenAI and massive datasets, promises to revolutionise personalised medicine and de-risk clinical trials.
• Decision Support: AI algorithms are moving from passive alerts to active decision support. In radiology and pathology, AI models are already achieving diagnostic parity with human experts. By 2030, these systems are expected to handle the majority of routine screening and triage, allowing human specialists to focus on complex, ambiguous cases.

Despite the potential, trust remains a significant barrier. Surveys indicate a complex relationship with AI adoption. While trust in AI for administrative tasks is generally high, skepticism remains regarding clinical diagnosis, particularly in Western markets. Interestingly, consumers in China and India show significantly higher trust and willingness to adopt AI-driven care than their counterparts in the US and Europe, suggesting that the "AI revolution" in healthcare may be led by the East, unencumbered by the legacy skepticism found in established markets.

Connectivity Infrastructure

5G and Beyond

The promise of Connected Health relies heavily on the "plumbing" of telecommunications. 5G is not merely faster 4G; its low latency and high reliability are prerequisites for mission-critical applications. The deployment of 5G infrastructure is expected to add over USD 530 billion to global GDP by 2030 through healthcare applications alone.

Impact of 5G by 2030:

• Remote Telesurgery: True remote robotic surgery requires near-zero latency, often referred to as the "tactile internet." 5G networks are enabling the first viable commercial applications of this technology, potentially allowing specialists to operate on patients in rural or conflict zones without physical presence.
• Massive IoMT Density: 5G allows for a density of connected devices (up to 1 million per square kilometer) that 4G cannot support. This is essential for the "Smart Hospital" concept, where every bed, infusion pump, and monitor is connected to a central command center.
• Bandwidth for Imaging: High-resolution pathology and radiology images, which can be gigabytes in size, require massive bandwidth for real-time transmission. 5G enables mobile diagnostic units to transmit these images instantly to specialists, facilitating immediate triage in field settings.

Cybersecurity: The FDA 2025 Paradigm Shift

As healthcare becomes hyper-connected, the attack surface expands exponentially. Cybersecurity in this context is no longer solely an IT issue but a patient safety issue; a compromised pacemaker or infusion pump can be lethal. The regulatory environment has responded with aggressive mandates.

The FDA's Final Guidance on Cybersecurity in Medical Devices, issued in June 2025, represents a watershed moment for the industry. This guidance fundamentally changes the market dynamics for medical device manufacturers (MDMs). Key requirements include:

• Security Lifecycle Management: Manufacturers are now responsible for monitoring and patching devices post-market. The "ship and forget" model is legally obsolete. MDMs must demonstrate a plan for the entire lifecycle of the device, including end-of-life support.
• Software Bill of Materials (SBOM): A mandatory inventory of all software components, including open-source libraries, contained within a device. This requirement is designed to allow rapid identification of vulnerabilities (similar to the Log4j incident) across the entire health ecosystem.
• Malware Prevention: Explicit requirements for design controls to prevent malware introduction during the manufacturing process itself.

By 2030, "cyber-hygiene" will be a prerequisite for market entry. Devices that cannot guarantee data integrity or provide an SBOM will effectively be barred from the connected ecosystem, forcing a capital replacement cycle for legacy hardware in hospitals.