How CCMP Predicted and Reduced ER Visits with Data-Driven Care Management in Health Homes 

For health homes and care management programs, having the right data at the right time can mean the difference between your clients thriving or ending up in the emergency room. Data can force positive change, challenge outdated systems, predict future health risks, and ultimately save lives. Community Care Management Partners (CCMP) have harnessed this power to revolutionize client outcomes, particularly in predicting and preventing costly ER visits. 

Turning Data into Action: CCMP’s Breakthrough in Care Management 

For years, the New York Department of Health (DOH) believed that shorter enrollments in health home programs led to better outcomes. This approach, shaped by state policy, prioritized quick interventions over longer-term care. But CCMP and Foothold Technology (FCM) questioned this assumption. 

“We needed to show why this wasn’t a data-driven idea,” recalls Tavin Weeda, CCMP’s data scientist. Using FCM’s platform, CCMP analyzed client data comprehensively and uncovered a different truth: clients who stayed in the program longer consistently showed better health outcomes. 

This wasn’t an anomaly. CCMP’s data revealed a direct correlation between longer program enrollment and positive results, such as lower depression and substance abuse scores. Rather than a bureaucratic formality, longer enrollments were often lifesaving for many clients. 

Clients who remained in CCMP’s program longer demonstrated:  

CCMP’s data-driven approach didn’t just challenge the status quo—it presented an opportunity to improve care and rethink how New York health homes support clients over time. By validating their insights across their network, CCMP provided undeniable evidence that longer enrollments were vital to improving client outcomes, effectively contesting the state’s previous stance. 

Predicting and Preventing ER Visits: Using Data to Drive Healthcare Outcomes 

But CCMP’s most groundbreaking discovery went beyond just enrollment lengths. By diving deeper into the data, they identified predictive patterns that would change how they approach care management. 

“I can remember where I was standing,” recalls Nathan Ito-Prine, CEO of CCMP. “Tavin called to tell me he had built a model that could predict ER visits with stunning accuracy.” 

The data revealed that certain clients were six times more likely to visit the emergency room (ER) within the next two weeks. This wasn’t just a vague insight—it was a concrete, data-driven prediction that allowed CCMP to help clients before a crisis could occur. 

Their learning model used a combination of static variables (such as age and medical history) and dynamic variables (like real-time alerts and assessments) to produce a list of high-risk clients. With this list, care managers could intervene before emergencies struck. 

Imagine the impact this could have on health homes! By identifying high-risk clients, CCMP could intervene with personalized preventive care plans, lowering the likelihood of unnecessary ER visits and improving overall client outcomes. This predictive insight transformed how CCMP approached healthcare—shifting from reactive responses to proactive, preventive care. 

The Role of Rapport: How Care Managers and Predictive Analytics Reduced ER Visits by 64% 

A key part of this success wasn’t just the data itself but how CCMP’s care managers used that data. The predictive model was designed to alert care managers when a client was at high risk for an ER visit, but the intervention process relied heavily on the relationships built between care managers and their clients. 

“We learned that when care managers established trust and rapport, clients were more likely to engage in preventative care,” says Nathan. “Even something as simple as a phone call could prevent a client from feeling the need to visit the ER.” 

This combination of predictive data and human connection had a tangible impact: members who received timely interventions saw a 64% reduction in ER visits. This translated into better health outcomes and significantly reduced health costs. 

The Unified Data Approach Behind CCMP’s Predictive Healthcare Model 

At the heart of this success was CCMP and FCM’s ability to create a single source of truth, unifying data from various touchpoints like emergency room admissions, care manager interactions, and medical histories. They integrated client data across multiple systems to gain a full, real-time view of each participant’s health profile. This system, built on Foothold Care Management (FCM) data, allowed CCMP to connect the dots between client behaviors, program participation, and health outcomes- predicting crises before they happened instead of simply reacting to them. 

“One of the key reasons this model works so well is that it’s constantly updating,” Tavin explains. “We’re pulling real-time data from multiple sources and integrating it into our system so that care managers always have the most up-to-date information when making decisions.” This ability to work with fresh data—often just minutes old—meant that CCMP could intervene quickly, before a client’s condition escalated. 

This integration of predictive analytics wasn’t just about efficiency—it was about enabling CCMP to see the patterns others might miss. 

Why Predictive Analytics Matter for Health Homes and Care Programs Everywhere 

CCMP’s data-driven approach isn’t just a victory for their program—it’s a blueprint for healthcare providers everywhere. “We want this to benefit the world,” Nathan says. By proving that longer health home enrollments and predictive interventions lead to better outcomes, CCMP is redefining what’s possible in care management. The ability to use data for predictive care is a massive opportunity for health organizations, and the results speak for themselves. 

1. Improved Client Outcomes: CCMP’s ability to identify clients at risk of ER visits allowed care managers to provide targeted, preventive care, improving long-term health outcomes. 

2. Cost Savings: By reducing avoidable ER visits, CCMP reduced healthcare costs for both clients and health home programs, highlighting the financial benefits of a data-centric approach. 

3. Scalable Impact: This approach isn’t limited to health home programs. Any healthcare provider can apply these data-driven techniques to create a more proactive and personalized care model. 

A Data-Driven Model for the Future of Healthcare: CCMP’s Vision 

As healthcare continues to shift toward value-based care, CCMP’s story is a reminder of the power of predictive analytics to drive change. “This isn’t just about CCMP,” Nathan insists. “It’s about showing that data can transform how we deliver care—not just react to crises but prevent them from happening in the first place.” With Foothold Technology’s data, CCMP has set a new standard for integrating data systems to unlock insights that directly improve client care and reduce costs. 

CCMP is currently working on expanding its model, applying it to new populations, and refining its approach even further. With their successful pilot projects and growing interest from healthcare stakeholders, CCMP is clearly leading the charge in data-driven care management. 

For healthcare providers looking to follow in CCMP’s footsteps, the key takeaway is this: it’s not just about collecting data—it’s about analyzing it in ways that reveal actionable insights. From enrollment lengths to ER visit predictions, CCMP has shown that data can predict the future and, more importantly, prevent crises before they happen. 

Watch the Full Breakdown with CCMP to Hear Exactly How Their Learning Model Works 

Watch the full webinar here to learn more about how CCMP and Foothold Technology used data to change client outcomes. Hear directly from the experts about the methodologies, challenges, and successes behind this groundbreaking work.