The Role of Al in Reshaping Healthcare Payment Models: Examining the Transition from Fee-for-Service to Value-Based Care

Abstract

In today’s system of transition from Fee-for-Service (FFS) to Value-Based Care (VBC) payment models in the US, healthcare stakeholders have many opportunities and challenges. Currently, Artificial Intelligence (AI) has the potential to become a catalyst and helping healthcare systems with their quality outcomes while controlling costs in their transformation. The purpose of this study is to determine which AI use, AI familiarity and security perception influence the support of healthcare professionals towards Value Base Care models.

In order to examine organizational characteristics associated with the co-production of value, a cross-sectional survey was conducted with 400 healthcare professionals from a variety of organizational settings throughout the United States (U.S.) including hospitals, clinics, insurance companies, health technology firms and government agencies. Descriptive statistics, Chi-square tests, binary logistic regression ordinal logistic regression as well as Kruskal-Wallis nonparametric test were used to analyse the data.

Both AI use and AI familiarity were shown to predict one’s preference for Value Based Care models. Those using AI were almost twice as likely to favor VBC compared to those not using AI. Participants’ future AI investment was dependent on how trusting they were with the security perception of AI systems. This suggests that trust has a significant role to play during technology adoption. While some of the reported statistical associations were weak, there were consistent directional trends in support of the role of AI as a strategic enabler in healthcare payment reform.

The study emphasizes the requirement for a more robust AI education, a stringent security framework and a collaborated leadership model with incentivized to speed up the switch toward Value Based Care in the United States. The insights from this study present useful policy implications for healthcare administrators, policymakers and technology developers in a developing and digital healthcare environment, particularly in the reengineering of the future payment models.