Exploring Patient-Focused Strategies in Value-Based Care at CAQH Connect 2024
Challenges in Value-Based Care Adoption
Health care leaders emphasized the need for collaboration, data standardization, and an iterative, patient-centric approach to advance value-based care (VBC) during a panel discussion at the Council for Affordable Quality Healthcare (CAQH) Connect 2024 in Washington, DC.
Key Adoption and Administration Challenges
Moderator Kristine Burnaska, PhD, senior director of research at CAQH, asked panelist Todd Couts about the challenges in adopting VBC programs. Couts, from the Center for Medicare and Medicaid Innovation (CMMI), identified two main challenges: policy design and operational issues.
- Policy Design: He emphasized the uncertainty of temporary CMS models and the challenge of balancing federal spending reductions with provider incentives.
- Operational Issues: Couts noted the need for rapid execution of new models and the complexity providers face due to overlapping VBC models.
Aligning Payers and Enhancing Patient-Centric Care
Further discussions included insights from Michael Westover, who described the challenges of managing multiple contracts and emphasized the importance of collaboration in improving patient outcomes. Panelist Amal Agarwal stressed the need for proactive engagement with patients.
Streamlining Data and Infusing AI
The panelists also discussed the role of data standardization and the potential of AI in EHRs to enhance VBC efficiency. They advocated for a partnership-focused approach between payers and providers, prioritizing shared goals and transparent communication.
Building Consensus in VBC
Despite varying definitions of quality measures, the experts agreed on the importance of iterative partnerships to improve VBC effectiveness over time. Striving for collaboration rather than confrontation can lead to better outcomes for patient populations.
This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.