兰州大学循证社会科学交叉创新实验室 Innovation Laboratory of Evidence-based Social Sciences,Lanzhou University

Applications of artificial intelligence and the challenges in health technology assessment: a scoping review and framework with a focus on economic dimensions.

2025-06-04

Background:
     
     Health Technology Assessment (HTA) is a crucial tool for evaluating the worth and roles of health technologies, and providing evidence-based guidance for their adoption and use. Artificial intelligence (AI) can enhance HTA processes by improving data collection, analysis, and decision-making. This study aims to explore the opportunities and challenges of utilizing artificial intelligence (AI) in health technology assessment (HTA), with a specific focus on economic dimensions. By leveraging AI's capabilities, this research examines how innovative tools and methods can optimize economic evaluation frameworks and enhance decision-making processes within the HTA context.
   

Methods:
     
     This study adopted Arksey and O'Malley's scoping review framework and conducted a systematic search in PubMed, Scopus, and Web of Science databases. It examined the benefits and challenges of AI integration into HTA, with a focus on economic dimensions.
   

Findings:
     
     AI significantly enhances HTA outcomes by driving methodological advancements, improving utility, and fostering healthcare innovation. It enables comprehensive assessments through robust data systems and databases. However, ethical considerations such as biases, transparency, and accountability emphasize the need for deliberate planning and policymaking to ensure responsible integration within the HTA framework.
   

Conclusion:
     
     AI applications in HTA have significant potential to enhance health outcomes and decision-making processes. However, the development of robust data management strategies and regulatory frameworks is essential to ensure effective and ethical implementation. Future research should prioritize the establishment of comprehensive frameworks for AI integration, fostering collaboration among stakeholders, and improving data quality and accessibility on an ongoing basis.
   

研究类型
系统评价再评价
人群
混合人群
国家
Iran
关键词
Applications; Artificial intelligence; Economic evaluation; Health technology assessment; Policy-making.
来源期刊
Health Econ Rev
发布日期
2025-06-04
全文链接
https://pubmed.ncbi.nlm.nih.gov/40461901/
相关网址
https://pubmed.ncbi.nlm.nih.gov/40461901/
DOI
10.1186/s13561-025-00645-4
主题
["技术资源"] ["财力资源"]
作者
Amirhossein Takian Ahad Bakhtiari Sanaz Bordbar Rajabali Daroudi Maryam Ramezani Saharnaz Sazgarnejad Ali Akbar Fazaeli Hakimeh Mostafavi Mohammadreza Mobinizadeh Alireza Olyaeemanesh Hamid R Rabiee