TY - JOUR
T1 - Generative Artificial Intelligence for Healthcare Administration: A Systematic Review of Applications in Documentation Support, Operational Reporting, Patient Communication, Governance Dashboards, and Workflow Automation
AU - Andrei Popescu
AU - Mihai Ionescu
AU - Elena Stan
AU - Sorin Dumitrescu
AU - Irina Pavel
JF - Journal of Health Informatics and Digital Systems
JO - J. Health Inform. Digit. Syst.
SN - 3149-8973
Y1 - 2026
VL - 6
IS - 1
DO - 10.68159/j827489866
SP - 121
N2 - Healthcare administration is document-intensive, communication-heavy, and increasingly dependent on digital systems that require timely synthesis of clinical and operational information. Generative artificial intelligence has been proposed as a potential means of reducing administrative workload across documentation, reporting, patient communication, governance, and workflow coordination. This systematic review examined applications of generative artificial intelligence across five healthcare administrative domains: documentation support, operational reporting, patient communication, governance dashboards, and workflow automation. The review aimed to characterize reported use cases, model types, evaluation approaches, implementation barriers, and evidence maturity from 2017 to 2025. A PRISMA 2020-compliant search strategy was applied to PubMed, Scopus, IEEE Xplore, and Web of Science for studies published between January 1, 2017, and December 31, 2025. Screening was conducted in duplicate, and eligible studies were synthesized narratively by administrative domain. Documentation support was the most mature domain, particularly for clinical summarization, discharge summaries, patient-message drafting, and document classification. Operational reporting and governance dashboards were emerging areas, while patient communication and workflow automation showed diverse prototypes but limited prospective validation. Common challenges included hallucination, privacy, bias, regulatory uncertainty, integration burden, and limited evidence of real-world administrative impact. Generative artificial intelligence appears technically capable of supporting multiple healthcare administrative tasks, but evidence remains uneven across domains. Real-world impact, safety, scalability, and governance require stronger evaluation before these systems can be relied upon for high-stakes administrative decision-making.
UR - https://cirpublications.com/j827489866
ER -