Appendices.docx

This systematic review is a trivial effort to examine the transformative integration of artificial intelligence (AI) across public healthcare management, addressing a significant gap in existing literature by focusing on the administrative, financial and clinical usage of AI applications across public health sector globally. With the adept and rigorous methodological application of PRISMA guidelines with S Extension, CASP checklist qualitative assessment and methodological rigor inculcating AIDO framework (Analysis, Interpretation, Design, Outcomes) for AI integration in healthcare. Hence, this systematic study analyses 35 selected research articles published between 2013-2025 from an initial pool of 2,201 records accessed from Scopus and Web of Science databases using United Nations Sustainable Development Goal 3 framework as a filter during the paper accessing process. Furthermore, this review uniquely contextualizes findings by identifying the AI technologies implemented across varied public healthcare settings, evaluating their effectiveness, documenting implementation challenges and facilitators, and assessing measurable outcomes including cost reduction, improved resource allocation, and enhanced healthcare delivery systems and the impact due to SDG goals3 which are discussed using AIDO framework for AI in healthcare in a theoretical and conceptual framework which could be extended further in longitudinal phase-wise research studies. The data extraction synthesizes evidence on AI tools, technologies, applications frameworks employed specifically in healthcare management context of public health, thereby formulating valuable insights for policymakers, healthcare administrators, and researchers working to optimize public healthcare systems through technological innovation while addressing global healthcare challenges.