Assessing the Impact of Artificial Intelligence implementation in Hospitals on Healthcare Economics: A meta‐Analysis

Background: The integration of artificial intelligence (AI) into healthcare systems has been
postulated to carry significant economic implications. As hospitals globally pivot towards AIcentered
solutions, understanding these economic outcomes becomes pivotal.

Objective: This meta-analysis aimed to elucidate the economic impact of AI adoption in hospitals,
gauging its influence on metrics such as return on investment (ROI) and cost-efficiency.

Methods: Leveraging the PRISMA framework, relevant studies were sourced, screened, and
selected. The Cochrane Collaboration's risk of bias tool assessed study quality. Pooled data results,
heterogeneity, and sensitivity analyses were conducted, with the overarching findings presented
through forest plots.

Results: AI's integration in hospitals showcased a moderate positive economic impact (Hedges' g
= 0.65, 95% CI [0.50, 0.80], p < 0.001). Subgroup analyses indicated nuances based on AI
technologies, with neural networks in predictive analytics yielding the highest economic benefits.
ROI-centric studies indicated substantial positive effects. Notable heterogeneity was observed,
emphasizing the diverse nature of AI implementations and economic metrics.
Conclusion: AI's introduction into hospital settings yields positive economic outcomes,
solidifying its stance as a transformative force in healthcare economics. However, strategic,
informed integration is imperative to maximize these benefits.