Transformasi Artificial Intelligence dalam Sistem Pelayanan Kesehatan Primer-Sekunder Daerah: Kajian Pemodelan Value Organisasi, Sumber Daya Manusia Kesehatan dan Sistem Kesehatan Daerah - Rafialdo Arifian (Badan Pengembangan Sumber Daya Manusia Provinsi Kalimantan Timur, 2025)
Artificial Intelligence (AI) transformation in primary and secondary health care systems in regions presents significant potential for enhancing efficiency, accessibility, and quality of services. This study examines the strategic transformation of artificial intelligence (AI) in primary and secondary health care systems in various regions through a multidisciplinary approach that encompasses organizational values, health human resources, and regional health policies and systems. A systematic literature review method, guided by the PRISMA approach and thematic-inductive analysis, is employed to assess the impact of AI on institutional readiness, health worker capacity, and policy formulation from the district/city to provincial levels. Literature from 2018 to 2024 is analyzed using VOSviewer software to visualize the relationships between concepts and develop an integrative conceptual framework. The study’s results indicate that effective AI transformation requires strategic leadership, organizational digital maturity, and a roadmap aligned with the institution’s vision. In primary care (Puskesmas), AI contributes to improved early detection, supports clinical decisions, and automates administrative services. In secondary care (RSUD), AI facilitates medical imaging diagnosis, optimizes referral systems, and manages chronic diseases. Nevertheless, challenges such as limited digital infrastructure, a shortage of skilled human resources, and institutional resistance pose significant obstacles. Successful adoption necessitates leadership capable of managing change, fostering cross-sector collaboration, and formulating contextual policies. Regarding human resources, digital literacy and technology acceptance are crucial factors. Structured training tailored to local needs, ongoing education, and digital competency certification are essential for cultivating adaptive human resources. Meanwhile, policy interventions should ensure the provision of infrastructure, data interoperability, and sustainable financing schemes, including public-private partnerships. AI is more than just a technological tool; it serves as a strategic lever to create more equitable, efficient, and data-driven health services at the local level. A holistic and adaptive approach is essential for the success of this transformation