By admin 
The focus this month remains squarely on how the federal government intends to bridge the gap between the Food and Drug Administration’s (FDA) approval of medical devices and Medicare’s decision to pay for them. For years, the health tech sector has argued that the current system is fragmented. A startup might spend years securing FDA clearance for an artificial intelligence-driven diagnostic tool, only to find that Medicare has no specific code or payment mechanism to cover it. This disconnect has led to the development of the Transitional Coverage for Emerging Technologies (TCET) pathway. TCET is designed to provide a predictable, time-limited coverage period for certain "breakthrough" devices, allowing manufacturers to collect the real-world evidence that CMS requires to make a permanent national coverage determination. However, the industry remains divided on whether TCET goes far enough. Critics argue that the cap on the number of devices accepted into the program—initially suggested to be as few as five per year—is far too low to keep pace with the explosion of innovation in digital health and AI.
The challenge of paying for AI in clinical care is particularly acute. Unlike a traditional surgical instrument or a pharmaceutical drug, AI software often functions as a service that requires constant updates and monitoring. The current Medicare reimbursement model, which is largely built on fee-for-service payments for discrete procedures, struggles to account for the ongoing value provided by an algorithm that assists a radiologist in spotting a fracture or a cardiologist in identifying an arrhythmia. While CMS has experimented with New Technology Add-on Payments (NTAP) for inpatient software, these are temporary measures. The long-term goal for many in the industry is the creation of a more permanent framework that recognizes "Software as a Medical Device" (SaMD) as a distinct category of clinical intervention.
In the realm of mental health, the stakes are equally high. The proliferation of mental health chatbots and digital therapeutics has promised to expand access to care in a country facing a dire shortage of clinicians. However, the evidence base for these tools remains uneven. Mario Aguilar’s reporting has frequently highlighted the tension between the convenience of consumer-facing mental health apps and the rigorous clinical validation required for medical-grade interventions. As September unfolds, the industry is watching for updates on how the FDA plans to refine its oversight of these "black box" algorithms. The agency is increasingly focused on the lifecycle management of AI, proposing frameworks that would allow manufacturers to pre-authorize certain types of algorithmic updates without needing to file a new 510(k) submission every time the software learns from new data.
Furthermore, the rise of consumer wearables is blurring the lines between "wellness" and "medicine." Devices like the Apple Watch, Oura Ring, and various continuous glucose monitors (CGMs) are no longer just for fitness enthusiasts; they are being integrated into chronic disease management programs. This shift raises significant questions about data privacy and the role of the patient in the digital ecosystem. When a wearable identifies a potential heart condition, who owns that data, and how does it move from a consumer’s iPhone into a hospital’s electronic health record (EHR) system? The interoperability of this data remains a significant hurdle. While the 21st Century Cures Act mandated that patients have easier access to their digital health information, the technical reality of "information blocking" continues to frustrate both patients and providers.
September also brings a renewed focus on health equity in the digital age. There is a growing concern among policymakers that the "digital divide" is being replicated in the health tech space. If the most advanced AI diagnostics and remote monitoring tools are only available to patients at elite academic medical centers or those with high-end smartphones and reliable broadband, the technology could inadvertently widen the gap in health outcomes between affluent and marginalized communities. CMS is under increasing pressure to ensure that its reimbursement policies incentivize the deployment of technology in rural and underserved urban areas. This includes expanding permanent coverage for telehealth services, many of which are still operating under temporary flexibilities granted during the Covid-19 public health emergency.
The legislative calendar is also heating up. On Capitol Hill, lawmakers are grappling with how to regulate the use of generative AI in healthcare. While the potential for large language models (LLMs) to reduce administrative burden and summarize patient charts is immense, the risks of "hallucinations"—where an AI generates plausible-looking but factually incorrect medical information—are a major concern. There is bipartisan interest in creating a regulatory framework that ensures transparency, requiring developers to disclose the datasets used to train their models and to prove that their algorithms do not harbor racial or socioeconomic biases.
From a financial perspective, the health tech sector is navigating a "new normal." The era of "easy money" and sky-high valuations for digital health startups has cooled, replaced by a more disciplined investment environment. Venture capitalists are now prioritizing companies that can demonstrate not just a "cool" technology, but a clear path to clinical efficacy and, crucially, a sustainable business model within the complex US reimbursement system. This shift is leading to a wave of consolidation, as smaller startups are acquired by larger health systems or established tech giants looking to bolster their healthcare portfolios.
As we look toward the final quarter of the year, several key milestones loom on the horizon. The physician fee schedule for the upcoming year will be finalized, providing clarity on how doctors will be paid for remote patient monitoring and digital check-ins. We also expect more clarity from the FDA on its "Digital Health Center of Excellence" and how it will coordinate with international regulators to create global standards for AI in medicine. The goal is to create a regulatory environment that is "global by design," allowing a developer in Boston to easily bring their technology to markets in London, Tokyo, and beyond.
In this edition of the newsletter, we also delve into the cybersecurity threats facing the healthcare sector. As hospitals become increasingly digitized, they have become prime targets for ransomware attacks. These breaches are not just a matter of data privacy; they are a matter of patient safety. When a hospital’s EHR is locked down, surgeries are canceled, and ambulances are diverted, leading to measurable increases in mortality rates. The Department of Health and Human Services (HHS) is considering new, mandatory cybersecurity standards for hospitals, a move that would represent a significant shift from the current voluntary guidelines.
The transformation of healthcare through technology is an iterative process, marked by moments of rapid acceleration and periods of cautious reflection. September serves as the annual "reset" for this cycle. Whether it is the refinement of the TCET pathway, the evolution of AI regulation, or the ongoing struggle for interoperability, the decisions made this month will reverberate through the halls of hospitals and the boardrooms of tech companies for years to come. We will continue to track these developments, providing the deep-dive analysis and insider perspectives that STAT+ subscribers have come to rely on. The intersection of medicine and technology is more crowded and complicated than ever, but it is also where the most significant breakthroughs in human health are likely to occur. Stay tuned as we navigate this landscape together, uncovering the stories that define the future of medicine.
