Traditional diabetes care often relies on scheduled visits, medication plans and periodic glucose checks. Digital therapeutics, which use Artificial Intelligence (AI) and real-time health tracking, now offer patients more continuous, personalized support. Joe Kiani, founder of Masimo, sees this shift as a way to reduce the daily strain on patients while improving outcomes. As both approaches continue to develop, many are weighing how digital solutions stack up against conventional care in terms of long-term results and patient engagement.
While traditional care continues to play a role in long-term diabetes treatment, digital therapeutics is emerging as a new category of support. These software-based tools are designed to deliver clinically proven interventions and help patients manage their condition with greater consistency and personalization. These platforms use AI to monitor trends, deliver personalized insights and help patients make small, daily adjustments that support better outcomes over time.
How Standard Diabetes Care Works
Traditional diabetes management has been centered around glucose testing, medication adherence and lifestyle modifications. Patients often rely on Self-Monitoring Blood Glucose devices or Continuous Glucose Monitors to track their blood sugar levels. Healthcare providers use this data to make treatment adjustments, but these changes are often reactive rather than proactive.
While conventional care remains effective, it has several limitations. Many patients struggle with adherence to medication and lifestyle recommendations due to a lack of continuous support. Periodic visits to healthcare providers may not be sufficient to detect early warning signs of complications. Without real-time insights, patients often make decisions based on incomplete data, leading to fluctuations in glucose levels and an increased risk of long-term complications.
How Digital Therapeutics is Improving Diabetes Care
Digital Therapeutics is changing the face of diabetes care by integrating AI, mobile health applications and real-time data tracking into patient management. These solutions provide continuous, personalized feedback that helps individuals make informed decisions about their health. AI-driven tools analyze blood glucose patterns, dietary intake, exercise levels and even stress responses to provide customized recommendations.
Unlike traditional methods, which rely on intermittent data points, AI-driven platforms offer a comprehensive view of a patient’s metabolic health. By aggregating information across multiple inputs, such as diet, activity, stress levels and sleep patterns, these platforms provide a more nuanced understanding of how daily habits influence blood sugar. This enables patients and providers to identify trends that might otherwise be missed.
Comparing Patient Engagement and Adherence
One major advantage digital therapeutics have over traditional diabetes care is improved patient engagement. Many digital platforms incorporate gamification elements, AI-driven chatbots and virtual coaching to keep users motivated. These features encourage adherence to treatment plans, making it easier for individuals to maintain healthy habits over the long term.
Traditional care, on the other hand, often lacks continuous engagement. Many patients find it difficult to stay motivated between doctor visits, leading to inconsistent glucose control. Digital therapeutics bridge this gap by providing daily support and reminders, helping individuals stay on track with their treatment goals.
The Role of AI in Predictive Analytics and Proactive Care
AI-driven digital health solutions excel in predictive analytics, allowing for proactive diabetes management rather than reactive treatment. Machine learning algorithms analyze vast amounts of patient data to detect trends and anticipate glucose fluctuations before they occur. This predictive capability enables timely adjustments to diet, medication and lifestyle choices, reducing the risk of complications.
In contrast, traditional diabetes care relies heavily on historical data from previous blood tests and patient-reported symptoms. While healthcare providers can make educated adjustments, they often lack the real-time data needed to anticipate problems before they escalate. Digital therapeutics fill this gap by continuously monitoring patient health and delivering actionable insights in real-time.
Preventing Complications and Improving Long-Term Outcomes
Both traditional diabetes care and digital therapeutics aim to prevent complications such as neuropathy, retinopathy and cardiovascular disease. However, digital health solutions offer a more personalized and data-driven approach. By tracking a patient’s progress in real-time, AI-powered tools can identify early warning signs and recommend immediate interventions.
Patients using digital therapeutics often experience better glycemic control, reduced HbA1c levels and fewer diabetes-related complications compared to those relying solely on traditional methods. The ability to integrate continuous monitoring with AI-driven recommendations enhances long-term health outcomes and lowers the burden on healthcare systems.
Blending Digital and Traditional Approaches to Improve Care
Digital therapeutics continue to offer new possibilities for diabetes care by supporting better daily decision-making and more consistent treatment outcomes. With real-time monitoring, personalized feedback and predictive insights, these tools are helping patients manage their condition with fewer disruptions. Traditional care remains essential, but when combined with digital support, it becomes easier to catch issues early and maintain long-term stability.
Many individuals face the burden of managing diabetes around the clock, often without adequate support between clinic visits. Joe Kiani says, “The people who have this disease don’t get to really live a good, easy life; they’re constantly managing their disease.” That reality demonstrates the need for care models that reduce stress, improve accessibility and offer support beyond the doctor’s office.
As digital therapeutics gain wider use, integrating them into standard care may offer the most practical way forward. Patients benefit from the structure of in-person medical oversight while gaining continuous support that adapts to their needs. This combined approach helps reduce complications, improve engagement and support long-term stability in diabetes management.
The Future of Personalized Diabetes Care
As the field of digital therapeutics becomes more advanced, they are emerging as a powerful tool in diabetes management. While traditional care methods remain essential, AI-driven solutions offer a level of personalization and continuous support that wasn’t possible with earlier approaches. By improving patient engagement, enabling predictive analytics and preventing complications, digital therapeutics is reshaping the future of diabetes care. Ongoing clinical validation and improved integration with primary care workflows will also be key to ensuring these technologies are both effective and scalable across diverse populations.
Ultimately, the best approach to long-term diabetes management may lie in a combination of both traditional and digital methods. As AI-powered tools reach more patients, integrating them into standard diabetes care protocols will ensure that individuals receive the most comprehensive and effective treatment possible. The future of diabetes care is moving toward a data-driven, patient-centered model that prioritizes proactive health management and long-term well-being.