Jan 30, 2026
Why Chronic Disease Care Breaks Down Between Visits — and How AI Fixes the Gap
Every doctor's office visit for chronic disease follows a familiar script: review labs, adjust medications, schedule the next appointment. But what happens in the months between those appointments is where chronic disease management actually succeeds or fails.
The statistics are sobering. Medication nonadherence rates for chronic diseases range from 30% to 50%, and studies show that more than half of patients either discontinue medications or fail to adhere to prescribed regimens. The consequences extend far beyond individual health outcomes. Poor medication adherence leads to increased morbidity and death and costs approximately $100 billion per year.
Why Manual Outreach Fails at Scale
Some health plans attempt to bridge this gap with care coordinators making phone calls or sending reminder letters. But when you're managing thousands of members with diabetes, hypertension, and hyperlipidemia, manual outreach becomes a losing battle against basic math.
Care coordinators can only reach a fraction of the population. Calls go to voicemail. Letters go unread. And the members who need help most—those with multiple chronic conditions, transportation barriers, or limited English proficiency—are precisely the ones least likely to respond to traditional outreach methods.
The result is a predictable pattern: the "easy" members get their care coordinated while high-risk, high-need members fall through the cracks. Quality scores remain stagnant. Readmission rates stay elevated. And care teams burn out trying to manually manage what should be an automated workflow.
The AI-Powered Alternative
Agentic AI represents a fundamental shift in how chronic disease management works between visits. Rather than waiting for patients to take action, or relying on care coordinators to manually track and reach out to hundreds of members, AI-powered platforms can engage appropriate members automatically, at scale, across multiple channels.
Blooming Health’s Care Enablement Workflows address chronic disease management failures at their source: the gaps between appointments where clinical control either happens or collapses.
How It Works
Our HIPAA-compliant platform uses agentic AI trained on over five years of real-world care pathway outreach data to automatically engage appropriate members for the specific interventions they need, including:
A1C testing and blood pressure screening
Kidney and vision exams
Statin and medication adherence tracking
Follow-up after ED visits for chronic conditions
Blooming Health’s AI reasons and takes action in real time by
Identifying risk
Determining next-best actions
Moving members through care journeys automatically
Scalable, Human-Centered Engagement
The system delivers culturally adaptive, multilingual outreach across 80+ languages via SMS, voice, surveys and reminders. All with closed-loop follow-up that escalates to human care teams only when needed.
Research shows that patients who meet medication adherence quality measures experience fewer inpatient stays and lower costs. Blooming Health makes this scalable.
Health plans implementing Care Enablement Workflows see:
Higher clinical control rates
A1C < 9%
BP < 140/90
Improved Star and HEDIS ratingsImproved Diabetes Control (CDC)
Improved Blood Pressure Management (CBP)
Increased statin and medication adherence
Reduced ED and inpatient utilization
A New Operating Model
Unlike manual care coordination—which can only reach a fraction of high-risk members—Blooming Health’s automated workflows deliver consistent engagement across entire populations.
AI represents a shift from point solutions to a new operating model for population health and quality teams at a time when plans are under pressure to do more with fewer resources.
Ready to close the gaps in chronic disease care? Contact the Blooming Health team today to learn how AI-powered Care Enablement Workflows can help your health plan improve clinical control rates, strengthen quality ratings, and reduce total cost of care, automatically, at scale, and with measurable equity.
