The Food and Drug Administration has selected Dexcom as the first participant in a new digital health pilot program, allowing the company to bypass certain premarket authorization requirements while collecting real-world data through Medicare. This regulatory flexibility is designed to accelerate the deployment of innovative health technologies by reducing the time and cost typically associated with traditional approval pathways. The exemption applies specifically to the premarket review process, which normally requires manufacturers to submit extensive clinical trial data demonstrating safety and efficacy before a device can be marketed. By temporarily waiving these requirements, the FDA aims to support faster adoption of tools that could address gaps in chronic disease management, particularly for conditions where early intervention is critical.
Dexcom’s AI-powered glucose program to test real-world impact
Dexcom, a manufacturer of continuous glucose monitors (CGMs), will use the pilot to launch an artificial intelligence-enabled glucose health program. The initiative aims to screen for prediabetes and Type 2 diabetes by integrating data from its prescription G7 CGM and over-the-counter Stelo device. The AI component will analyze trends in glucose fluctuations, identifying subtle patterns that may indicate metabolic dysfunction before it progresses to full-blown diabetes.
The company said the program will combine glucose readings with contextual health information—such as nutrition, physical activity, sleep, and stress—to provide a more complete picture of metabolic health. By bringing together all of this data, Dexcom hopes to give users and healthcare providers a more full view of metabolic health, and to help improve glycemic control and lower blood sugar levels in people with prediabetes.
The goal is to improve glycemic control and lower blood sugar levels in people with prediabetes. Unlike traditional diabetes management, which often focuses on reactive measures like medication adjustments after symptoms appear, this approach emphasizes preventive strategies. Over time, these insights could help users adopt sustainable lifestyle changes, potentially delaying or preventing the onset of Type 2 diabetes.
For patients, this could mean earlier interventions and more personalized care plans. Instead of relying on periodic HbA1c tests, which provide a three-month average of blood sugar levels, clinicians could access dynamic, real-time data to tailor treatment. The system could also stratify risk by identifying individuals whose glucose patterns suggest progression toward diabetes, allowing for more aggressive intervention. However, the integration of AI introduces complexities, such as ensuring the algorithms are trained on diverse datasets to avoid biases that could lead to inaccurate predictions for certain demographic groups.
The data collected might also help clinicians identify patterns that traditional lab tests miss, though the long-term effectiveness remains unproven. Current diagnostic methods, such as oral glucose tolerance tests, provide snapshots of metabolic function under controlled conditions but fail to capture the variability introduced by daily habits. By contrast, continuous monitoring in real-world settings could reveal how factors like meal timing, exercise, or sleep deprivation influence glucose metabolism over weeks or months. This granularity might uncover previously overlooked correlations. However, the pilot’s reliance on post-market data means any benefits will need to be validated through long-term studies, as short-term improvements in glucose control do not always translate to reduced complication rates.
Pilot part of broader push for digital health adoption
The FDA’s Technology-Enabled Meaningful Patient Outcomes (TEMPO) pilot was announced last year as part of a larger effort to expand the use of digital health tools and wearables. This initiative reflects a shift in regulatory strategy, moving away from the rigid frameworks that governed earlier generations of medical devices toward a more adaptive model. The TEMPO pilot is structured to evaluate not just the technical performance of devices but also their real-world utility, including how well they integrate into clinical workflows and patient routines. The FDA has emphasized that this approach is not a relaxation of standards but rather a reallocation of oversight, with greater emphasis on post-market surveillance to ensure ongoing safety and effectiveness.
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It aligns with a separate 10-year program by the Centers for Medicare and Medicaid Services (CMS) to fund digital technologies for managing chronic conditions. The CMS program, known as the Innovation in Behavioral Health (IBH) Model, is designed to test whether digital tools can improve outcomes for beneficiaries with high-cost, high-need conditions. Unlike traditional fee-for-service models, which reimburse providers based on the volume of services delivered, the IBH Model will tie payments to measurable improvements in health metrics, such as reductions in hospitalizations or emergency department visits. This creates a financial incentive for healthcare systems to adopt technologies that demonstrate tangible benefits, while also providing a framework for evaluating which tools deliver the most value.
The CMS program targets four focus areas: hypertension, diabetes, heart disease, and chronic kidney disease, along with musculoskeletal pain, anxiety, and depression. Each of these conditions presents unique challenges for digital health interventions. For hypertension, tools might include remote blood pressure monitoring with automated alerts for abnormal readings, while heart disease management could leverage wearable ECG monitors to detect arrhythmias. Chronic kidney disease programs might focus on fluid intake tracking and medication adherence, given the high risk of complications from missed dialysis sessions or incorrect dosing. The inclusion of musculoskeletal pain and mental health reflects a recognition that chronic conditions often co-occur, requiring integrated solutions.
It launches in July, with the FDA planning to accept up to 10 manufacturers for each category. The selection process prioritizes technologies that address unmet needs, such as tools for underserved populations or those that reduce disparities in care access. Manufacturers must demonstrate how their devices will generate actionable insights for both patients and providers, rather than simply collecting data. The FDA has indicated that it will favor applications that include clear plans for data interoperability, ensuring that information can be seamlessly shared across electronic health records and other clinical systems. This interoperability is critical for scaling digital health solutions, as fragmented data silos have historically limited the utility of such tools in real-world settings.
The agency said the pilot will help regulators and CMS better understand how digital health technologies perform outside clinical trials. Real-world data could reveal gaps in usability, accuracy, or patient adherence that aren’t apparent in controlled studies. For instance, a device that performs flawlessly in a clinical trial might prove impractical for elderly users if it requires frequent battery changes or complex setup procedures. Similarly, a tool that relies on manual data entry may see low adherence if users find the process burdensome. The pilot will also assess how well these technologies integrate into existing care models, such as whether primary care physicians have the time and resources to review continuous data streams or whether patients receive adequate support for interpreting and acting on the insights provided.
Dexcom’s selection doesn’t guarantee long-term approval, but it signals the FDA’s willingness to test new regulatory approaches. The pilot is structured as a time-limited exemption, meaning that even if the program demonstrates success, Dexcom and other participants will eventually need to seek full authorization through traditional pathways. This phased approach allows the FDA to gather evidence incrementally, reducing the risk of widespread adoption of technologies that later prove ineffective or unsafe. The agency has also reserved the right to terminate participation for any manufacturer whose device fails to meet performance benchmarks, ensuring that patient safety remains the top priority. For companies, the pilot offers a unique opportunity to refine their products based on real-world feedback before committing to the costly and time-consuming process of full approval.
The agency is still accepting statements of interest from other manufacturers, with no set deadline for applications. This open-ended timeline reflects the FDA’s recognition that digital health is a rapidly evolving field, and that the most promising innovations may emerge from unexpected sources. The agency has encouraged submissions from startups and smaller firms, which may lack the resources to handle traditional regulatory pathways but could offer novel solutions. To facilitate participation, the FDA has published guidance documents outlining the types of data manufacturers should collect during the pilot, such as user engagement metrics, clinical outcomes, and adverse event reports. This transparency aims to ensure that all participants are held to consistent standards, even as the specific requirements may vary depending on the device’s intended use.
While the pilot offers a faster path to market, it also shifts some of the evidence burden to post-market surveillance. Patients and providers will need to weigh the potential benefits against the uncertainty of unproven technologies. For example, a glucose monitoring system that performs well in a controlled setting might produce false alarms or missed readings in real-world conditions, leading to unnecessary anxiety or delayed treatment. The FDA has acknowledged these risks and has emphasized the importance of robust post-market monitoring, including mechanisms for reporting adverse events and tracking long-term outcomes. Providers will need to educate patients about the limitations of these tools, ensuring that they understand the difference between clinical-grade diagnostics and wellness-focused devices. Meanwhile, patients will need to remain vigilant about following up on any concerning trends identified by the technology, rather than assuming the system will catch every potential issue.