Abstract

D-SNP/MLTSS plans face unique challenges in growing while managing complex member populations, especially in new markets. Siftwell offers a practical tool to ease this process, built by experienced MCO operators who deeply understand these challenges.

Author: Siftwell Team

Siftwell hosted a webinar with MLTSS Association in partnership with ACAP to discuss how D-SNP/LTSS/MA Plans can use AI to level up. In case you missed it, here are the key insights discussed – with more detailed strategies available in the full recording.

The Challenge: Building While Flying

Managing D-SNP/LTSS/MA plans in today’s healthcare landscape is like building a rocket while flying it. You’re simultaneously serving complex populations, navigating dual eligibility requirements, and implementing new technologies – all while trying to improve outcomes and control costs. Our recent webinar tackled these challenges head-on, offering practical solutions for plans feeling the pressure to innovate while maintaining operational excellence.

The Measurement Challenge

There’s a critical industry challenge: the lack of a standard set of National quality measurements for HCBS and its impact on developing and scaling meaningful MLTSS programs. This fundamental gap set the stage for a comprehensive discussion about measuring and improving outcomes in managed care.

Key Topics Covered

1. Member Retention Strategies

Plan leaders face three key retention challenges: measuring immediate impact of investments, aligning complex Medicare-Medicaid benefits, and navigating unique dual-eligible policy requirements. Siftwell presented solutions designed for member retention including:

  • Data-driven targeted campaigns and interventions
  • Psychographic modeling for predicting member behavior
  • Personalized outreach strategies based on comprehensive data analysis

2. AI Applications in Care Management

The webinar demonstrated practical applications of AI in managed care, including:

  • Predictive modeling for proactive member engagement
  • Integration of psychosocial and physical health factors
  • Strategies for addressing health inequities through AI-driven insights

3. Value-Based Care Implementation

The presentation covered concrete approaches to value-based contracting, exploring:

  • Methods for defining value within MLTSS populations
  • Risk assessment strategies
  • Integration of AI tools with human expertise

Notable Segments

  • Institutional transition strategies and community reintegration
  • AI-driven intervention demonstrations
  • Siftwell’s causal inference capabilities in action

Immediate Action Steps

  1. Launch AI-powered member retention program and personalized interventions
  2. Implement data-driven decisions and predictive modeling for proactive care delivery
  3. Partner with AI solution providers to advance value-based care initiatives
  4. Train care teams on effective AI tool utilization
  5. Schedule a demo with us to see Siftwell’s causal inference capabilities to address care inequities

→ Watch the full discussion