The biggest barrier to better diabetes care isn't a lack of technology—it's that your health information is locked in separate systems that can't talk to each other. A new national framework is pushing to change that, potentially transforming how people with type 1 diabetes, type 2 diabetes, prediabetes, and gestational diabetes receive care and manage their glucose levels. What's Keeping Your Diabetes Data Fragmented? If you've ever switched doctors or gone to a specialist, you've probably experienced it: your new provider asks you to fill out the same health history again, or they can't access your previous blood sugar readings, A1C results, or insulin adjustments. This fragmentation isn't just frustrating—it's a real problem for diabetes management. Despite nearly universal adoption of electronic health records (EHRs) across hospitals and clinics, the health system lacks what experts call a "cohesive digital and data architecture." In plain terms, this means there's no common language or set of rules that allows different systems to share information seamlessly. Your continuous glucose monitor (CGM) data might live in one app, your metformin prescription in another system, and your doctor's notes in a third—with no bridge connecting them. This fragmentation has real consequences. Care coordination suffers, innovation slows, and patients end up managing their own diabetes information manually, copying numbers between apps and providers. For someone tracking blood sugar patterns, insulin doses, and medication side effects, this creates unnecessary friction at a time when they need clarity most. How Could Better Data Sharing Help Diabetes Patients? A new discussion paper from the National Academies of Sciences, Engineering, and Medicine outlines a vision for what better data architecture could enable. The authors describe specific opportunities where improved data sharing could transform diabetes care. Imagine your doctor could instantly see your real-time glucose patterns from your CGM, your medication adherence with GLP-1 drugs or metformin, and your A1C trends—all in one place. That's the kind of integration experts say is possible with the right infrastructure. Better data sharing could also enable artificial intelligence (AI)-driven predictive analytics to spot patterns in your blood sugar that you might miss, helping catch prediabetes earlier or predict diabetic neuropathy risk before complications develop. Remote patient monitoring becomes far more powerful when data flows seamlessly. Instead of manually logging glucose readings, your devices could automatically sync with your healthcare team, allowing them to adjust your insulin regimen or other treatments in real time. Telehealth visits could be more effective because your provider would have complete, up-to-date information about your glucose control and medication history. What Would It Take to Fix This Problem? The National Academies paper identifies four major barriers and specific solutions to break them down: - Regulatory Complexity: The current patchwork of rules from different federal agencies creates confusion. The solution involves prioritizing a small set of foundational interoperability standards—like SMART on FHIR (Fast Healthcare Interoperability Resources) and Bulk FHIR—while reducing unnecessary certification requirements that don't directly improve data sharing. - Industry Fragmentation: Health technology vendors compete in ways that discourage data sharing. Experts recommend establishing stronger accountability mechanisms, including potential fines for vendors whose products fail to meet interoperability standards, and empowering patients to demand seamless access to their own health data. - Misaligned Financial Incentives: Hospitals and clinics currently have little financial reward for sharing data. The solution involves linking reimbursement and quality measurements to effective use of standardized data exchange systems, shifting focus from procedural compliance to actual improved coordination and patient outcomes. - Patient Empowerment Gaps: Many patients don't realize they have the right to access and share their own health information. Better policy could enable patients to easily acquire, use, and share their diabetes data—including glucose readings, images, device-generated measures, and genetic information—across clinical care, research, and direct-to-consumer apps. Steps to Advocate for Better Diabetes Data Access - Request Your Health Records: Under current law, you have the right to access your health information. Ask your doctor's office for your complete diabetes records, including A1C results, glucose logs, and medication history. This helps you understand your own data and identify gaps in what different providers can see. - Use Patient Portals Strategically: Many healthcare systems now offer patient portals that display some health information. Familiarize yourself with what's available in your provider's system and note what's missing—this information gap is exactly what better interoperability aims to solve. - Demand Interoperability from Your Providers: When choosing a doctor, clinic, or diabetes management app, ask whether they use standardized data exchange formats. Specifically, ask if they support FHIR standards or can export your data in a portable format. Consumer demand for this capability creates market pressure for change. - Support Policy Changes: The National Academies recommendations require federal action. Staying informed about health data policy and supporting organizations that advocate for patient data rights helps accelerate these changes at the national level. Why This Matters Now Diabetes affects over 37 million Americans, and managing it effectively requires constant attention to glucose patterns, medication adjustments, and lifestyle factors. The current fragmented system forces patients and providers to work harder than necessary. Better data architecture isn't just a technical upgrade—it's a foundation for more personalized, responsive diabetes care. The National Academies paper emphasizes that "robust interoperability is necessary but not sufficient." Simply connecting systems isn't enough; they need to be designed with patients at the center, using common standards and clear protocols. This shift from isolated data silos to an integrated ecosystem could mean the difference between reactive diabetes management and truly preventive care. The good news: experts and policymakers are increasingly recognizing this problem. The framework outlined in this discussion paper provides a roadmap for federal agencies, healthcare systems, and technology vendors to work together. For people living with diabetes—whether type 1, type 2, or managing prediabetes—better data sharing could mean fewer manual entries, faster treatment adjustments, and ultimately, better health outcomes.
