Main Library
Emergency department utilization is one of the most powerful cost accelerators in value-based care arrangements. For ACOs, Medicare Advantage organizations, and provider groups operating under downside risk, preventable ED visits can quickly erode shared savings and destabilize financial performance.
The challenge is not simply managing ED use after it occurs- it is identifying and stabilizing rising-risk patients before they deteriorate.
In this webinar, we will examine how predictive analytics and AI-driven digital health platforms are enabling a shift from reactive ED management to pre-emptive intervention. By integrating EHR data, claims data, remote monitoring, medication adherence signals, and patient-reported inputs, VBC organizations can detect early warning patterns that precede ED visits. We will explore how predictive insights translate into action through continuous digital care pathways, automated outreach, symptom monitoring, & intelligent care team escalation—allowing providers to intervene at the right moment without overwhelming staff.
Attendees will gain practical insight into how predictive ED risk modeling can:
- Identify rising-risk patients before acute deterioration
- Reduce avoidable ED visits & observation stays
- Improve chronic disease stabilization between visits
- Enhance medication adherence and symptom monitoring
- Prioritize care management resources more effectively
- Reduce total cost of care volatility in downside risk contracts
- Strengthen quality performance & patient satisfaction
- Scale preventive intervention without increasing staffing burden
We will also discuss real-world implementation considerations, including workflow integration, alert prioritization, & measuring ROI within MSSP, ACO REACH, & MA populations.
This session is designed for healthcare leaders, population health executives, care management directors, and financial decision-makers who are seeking scalable, predictive strategies to reduce ED overutilization and improve performance under VBC models.