As health care continues to shift the focus from volume (fee-for-service) to patient outcomes, quality, and cost-effectiveness (value-based care), significant challenges remain in data sharing and implementation. Though many organizations find it hard to maintain long-term success in valuebased care, the model continues to receive increasing support from Medicare, private payers, and significant private investment.

Health plans and provider organizations are continuously confronted with increasing downside risks, narrowing profit margins, ongoing workforce shortages, and shifting expectations regarding digital quality and health equity. These challenges are further compounded by reliance on fragmented data and outdated workflows. Leaders are bombarded with artificial intelligence (AI) promises but lack a clear roadmap for where to start, how to scale responsibly, and how to quantify impact across valuebased care programs. The result is a widening gap between aspirations and outcomes.