Mark Clements, M.D., Ph.D. Chief Medical and Strategy Officer, Glooko
As healthcare providers, we find ourselves at an exciting crossroads in diabetes management. Rapid advancements in technology—from remote patient monitoring to artificial intelligence—have fundamentally altered how we approach patient care. Yet, despite these technological leaps, a critical ingredient remains consistently underrepresented: the clinician’s voice, and the voices of people with diabetes.For nearly two decades as a pediatric endocrinologist, I’ve witnessed firsthand the immense potential and significant challenges of integrating digital solutions into everyday diabetes care for both people with diabetes and their care providers. On any given day, a clinician managing diabetes navigates multiple complex responsibilities: reviewing continuous glucose monitoring (CGM) and/or meter data, keeping up with rapidly emerging devices and technologies, adjusting insulin regimens, coaching individuals with diabetes on lifestyle management, documenting clinical decisions, and coordinating care teams. For example, a single patient using a CGM device can generate up to 288 glucose data points daily, creating a complex datastream that requires detailed analysis and review. 1 Insulin pumps generate even more complicated data for review. Multiply this by dozens of people with diabetes seen by a clinician each day, and the clinician workload becomes enormous.
People with diabetes echo similar concerns. Many describe data fatigue from constant management and analysis of their glucose levels. As one person stated, “The data is overwhelming; without clear insights and simpler ways to interpret it, it’s just noise.”While these data are incredibly helpful to inform clinical decision making, they can come with unintended consequences. For clinicians and people with diabetes alike, burnout is alarmingly high. Among endocrinologists in particular, approximately half to two-thirds of clinicians report burnout symptoms. 2,3 Bureaucratic tasks, prolonged work hours, and the burden of data review contribute significantly to this stress, making effective integration of data and devices into their daily workflows critical.
Similarly, people with diabetes report significant stress from managing their condition daily. “Every glucose reading feels like a test I can fail,” is something I have heard before in the clinic. Effective integration of data into one’s daily experience of living with diabetes could alleviate such emotional burdens by making data actionable, intuitive, and less intrusive.Individuals with diabetes and the clinicians who care for them hold critical insights into behaviors, challenges with engagement in self-management, and care preferences. Yet, digital solutions are frequently developed without adequate input from clinicians and people with diabetes, leading to sophisticated but impractical tools. Only about 40% of digital diabetes solutions see active clinical use, largely due to poor workflow integration.4 True interoperability through electronic health record (EHR integration) and streamlined integration into clinicians’ flow of work are essential to increasing adoption and effectiveness. People with diabetes also stress the importance of simplicity and intuitive user experiences: If the technology is complicated, it just becomes another barrier.
Connected care, where user-generated data integrate seamlessly with clinical decision-making, represents the clear future of diabetes management. Evidence shows connected care platforms can support remote healthcare delivery in a way that significantly improves diabetes outcomes, including reductions of HbA1c levels up to 1.5% and decreased hypoglycemic episodes.5 Such platforms enable clinicians to rapidly identify high-risk patterns and deliver proactive rather than reactive interventions. For people with diabetes, this can lead to significant improvements in their diabetes self-management.AI-driven predictive analytics are also emerging as powerful tools. These can forecast impending hypoglycemic or hyperglycemic events, allowing for timely preventive interventions. Automating routine data analysis tasks can reduce clinician documentation time by approximately 30%, significantly alleviating administrative burdens. 6,7Looking forward, diabetes technology should aim for direct user engagement in design efforts, and in achieving personalized approaches via robust connected care ecosystems. Advanced analytics and AI-driven decision support informed by near-real-time clinical data can transform care from generalized treatment protocols to highly personalized management strategies.Innovation guided directly by clinicians and people with diabetes is essential for meaningful progress in diabetes care. By integrating the expertise of clinicians and persons with diabetes into the earliest stages of technology development, we ensure tools genuinely enhance clinical workflows, support self-care, and ultimately personalize diabetes management, by leaning on both the science and art of human-centered design.
References
Speakman, ASHP.Hammes et al., Endocrine News; Medscape Endocrinologist Lifestyle Report, 2022.Batta et al., BMJ Open Diabetes Res Care.Shah et al., J. Diabetes Sci Technol., 2023.Su et al., J. Med Internet Res., 2023.AMA Digital Health Report.Sidharthan et al., Scientific Reports, 2025.
About Mark Clements, M.D., Ph.D.
Dr. Mark Clements currently serves as Chief Medical and Strategy Officer of Glooko, a leading global diabetes data management company. Prior to his latest role, he served as fractional Chief Medical Officer of Glooko, as well as Professor of Pediatrics at the University of Missouri-Kansas City (UMKC) School of Medicine, where he held the Endowed Chair in Endocrinology and Diabetes. At UMKC, Dr. Clements also held the role of Medical Director of the Pediatric Clinical Research Unit and the Diabetes Research Program and was Co-Principal Investigator of the TrialNet Clinical Center and Data Science Lead for the Type 1 Diabetes Exchange-Quality Improvement (T1DX-QI) initiative.
