Machine Learning-Based Prediction of Hospital Readmissions and Healthcare Costs: A Systematic Review of Predictive Models in Value-Based Healthcare Systems

Abstract

Background: Hospital readmissions exert significant clinical and financial strains on healthcare systems. This is especially the case where reimbursement is outcome-connected in value-based care models. The prediction of hospital readmission and healthcare cost burdens associated with readmissions has increasingly involved the application of Artificial Intelligence (AI) and machine learning (ML). However, the literature is deficient in providing an integrative overview of both clinical and economic dimensions. Methods: A systematic review compliant with PRISMA 2020 guidelines was performed. For scientific studies published in the last 12 years (2014 to May 2026), a multitude of sources