Leveraging AI for Strategic Management in Healthcare: Enhancing Operational and Financial Performance
This paper explores the transformative potential of artificial intelligence (AI) in revolutionizing hospital management practices, particularly in enhancing operational and financial performance. The incorporation of artificial intelligence (AI) technologies, including machine learning, predictive analytics, and natural language processing, hospitals are addressing inherent inefficiencies in traditional management approaches, thereby improving patient care quality and operational efficiency. Evidence increasingly supports AI's significant impact on optimizing hospital operations, from resource allocation and patient flow management to scheduling and financial processes. AI's role in optimizing staffing, resource utilization, streamlining billing, and claims processing, along with its application in decision support systems for strategic planning and performance monitoring, highlights its effectiveness in tackling long-standing inefficiencies. The strategic integration of AI provides healthcare executives with the necessary instruments to optimize decision-making processes, reduce costs, and enhance overall performance. To maximize AI's benefits, hospital leaders are advised to prioritize comprehensive training, robust data governance, and continuous system evaluation. The paper also suggests avenues for future research, including the development of advanced AI models for complex medical scenarios and the integration of AI with technologies like blockchain and IoT to bolster data security and real-time decision-making. As AI technology advances, its transformative role in healthcare administration will expand, paving the way for a future where hospitals can deliver care with unparalleled quality and efficiency.
Authors
- Zefeng Wang (ORCID: https://orcid.org/0000-0002-3089-6886)
- Wu Yinhang (ORCID: https://orcid.org/0000-0001-5227-7413)
- Ruixiang Zhao
- Laurent Peyrodie (ORCID: https://orcid.org/0000-0001-6602-9584)
- Jean-Marie Nianga
- How‐Ran Guo (ORCID: https://orcid.org/0000-0003-3343-3446)
- Xuecan Yang
Publication Details
- Journal
- Journal of intelligence and knowledge engineering.
- Published
- 2024-09-01
- DOI
- https://doi.org/10.62517/jike.202404301
- Citations
- 6
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 3.17