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Artificial Intelligence as a Catalyst for Value-Based Health Insurance in the United States: Narrative Review and Policy Perspective - PMC
The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have revealed the limitations of the Fee-for-Service (FFS) model. Value-based care (VBC) aims to realign incentives toward outcomes, quality, and efficiency.
Artificial intelligence is pivotal in transitioning the U.S. health insurance system from a Fee-for-Service model to a Value-Based Care approach, enhancing efficiency and outcomes.
Executive Summary
The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have revealed the limitations of the Fee-for-Service (FFS) model. This long-standing structure, while once effective in expanding access, now struggles to deliver efficiency and value. Value-based care (VBC) aims to realign incentives toward outcomes, quality, and efficiency. This article explores how artificial intelligence (AI) can serve as the digital backbone to accelerate the transition from FFS to VBC. The article reviews evidence from bundled payment programs and Accountable Care Organizations (ACOs), examines AI-driven frameworks for cost prediction, outcome measurement, and risk adjustment, and discusses associated challenges and future considerations using an illustrative case.
Source: @ncbi
Authors: Amol Kodan
Published: 2026-02-22
Original Article: https://pmc.ncbi.nlm.nih.gov/articles/13004588
Usage Rights: https://creativecommons.org/licenses/by/4.0/
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