The CDC estimates that more than 129 million Americans, roughly 37% of the population, are living with at least one chronic condition. These conditions account for nearly 90% of the $4.5 trillion the U.S. spends on healthcare each year.
For providers, payers, and policymakers, chronic disease is not just a clinical challenge. It is a central economic pressure shaping the future of healthcare.
Chronic care management (CCM) is essential, but most programs are still built on fragmented, semi-manual workflows that were never designed to support continuous care.
As a result, CCM cannot succeed as a manual, check-the-box program. To improve outcomes and control costs at scale, it must be technology-enabled and operationalized across the care continuum.
This isn’t a new problem. Historically, these programs were limited to a small subset of patients due to staffing constraints and disconnected systems. Today, most care teams still struggle to consistently reach more than a small portion of their patient population.
At its core, the role of technology in CCM is to make care coordination scalable so it can reach far more patients, not just the highest-risk few.
Here are five ways technology is transforming CCM:
1. Enables population-level risk identification – Historically, identifying high-risk patients has been reactive, often triggered after an acute event like an ER visit or hospitalization.
Technology platforms change that by continuously analyzing clinical, claims, and utilization data to identify patients at rising risk earlier. Instead of static lists, these systems dynamically update risk scores and flag patients whose conditions or behaviors indicate they may need intervention.
This allows care teams to focus attention where it will have the greatest impact across a broader patient population, not just those already in crisis.
In value-based care environments, proactive risk identification is critical to improving outcomes while managing cost.
2. Delivers personalized care at scale – Identifying risk is only the first step. The real challenge is tailoring care to each individual patient across large populations.
Technology enables this by combining patient-specific data, including medical history, medications, social factors, and engagement patterns, to guide care plans and outreach.
AI-driven workflows can help determine:
- Which patients need outreach
- What type of intervention is most appropriate
- When and how to engage them
This allows care teams to deliver individualized care without limiting support to a small subset of patients, moving beyond one-size-fits-all outreach.
With the right technology, care teams can support significantly larger patient populations than traditional models allowed.
In a system facing workforce shortages and growing demand, this balance between personalization and scalability is essential.
3. Integrates SDoH into care delivery – Non-clinical factors like housing stability, transportation, and food access, known as Social Determinants of Health (SDoH), play a significant role in health outcomes. Studies estimate that social determinants of health can account for up to 50% of health outcomes.
Yet in many organizations, SDoH data is collected but not operationalized.
Technology platforms can embed SDoH data into care workflows, allowing care teams to identify barriers and take action in real time.
For example:
- Flagging transportation needs before appointments
- Identifying food insecurity that may impact diet adherence
- Connecting patients to community-based resources
When integrated into care plans, these insights make interventions more effective and targeted, reducing missed visits, avoidable admissions, and overall cost of care.
4. Enables earlier, more targeted interventions – One of the biggest opportunities in CCM is intervening before a patient’s condition escalates.
Technology, particularly Artificial Intelligence (AI), plays a key role by analyzing historical patterns and real-time data to identify patients likely to deteriorate or utilize high-cost services.
Platforms can:
- Identify rising ER utilization
- Detect gaps in medication adherence
- Highlight changes in clinical indicators or engagement
AI can then recommend the next best action, whether outreach, medication review, or escalation to a provider.
This allows care teams to intervene earlier and more precisely, reducing avoidable hospitalizations and improving patient stability.
5. Creates a unified, longitudinal view of the patient – Fragmentation remains one of the biggest barriers in healthcare. Patient data is often spread across EHRs, claims systems, pharmacies, and other sources, making it difficult to get a complete picture.
Technology platforms address this by integrating data into a single, longitudinal patient record.
This creates a cohesive view that allows care teams to:
- Understand the full patient journey
- Coordinate across providers and specialists
- Avoid duplicative or conflicting interventions
Rather than relying on disconnected systems, care teams can operate from a shared, up-to-date view of the patient.
As these platforms evolve, organizations must prioritize transparency, clinician oversight, and clear escalation pathways to maintain safety and trust.
Technology alone is not the solution, but when paired with clinician-led care, it enables a fundamentally different approach to chronic disease management. These tools are designed to augment care teams by reducing administrative burden and allowing clinicians to focus on higher-value care.
The real impact of technology in CCM is not just better care, but the ability to deliver coordinated care to far more patients than traditional models allowed. As healthcare shifts toward value-based models, scalable, technology-enabled CCM will become a core part of how care is delivered.
The organizations that succeed will not be the ones with the most technology, but those that use it to fundamentally change how care is delivered between visits.
Photo: AlexandraFlorian, Getty Images
Stephen Stewart is the Chief Operating Officer of CareHarmony, where he leads the company’s operational strategy, business execution, and nationwide scaling of its AI-enabled care coordination platform. Stewart brings two decades of experience in healthcare operations and technology-driven business strategy.
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