Back to all news
Literature Review Highlights Gaps in Economic Evaluation of Healthcare AI
Tags:Research
A Finnish review finds significant gaps in economic evaluation reporting of AI technologies in Western healthcare.
Key Details
- 1A literature review examined economic evaluations of AI in healthcare, revealing insufficient research and inconsistent reporting.
- 2Over half of the reviewed studies (55.6%, n=10) only broadly described methods as 'ML' or 'deep learning,' lacking system-specific details.
- 3Most studies did not account for all costs, such as integration, support, or maintenance of AI systems.
- 4There is a need for unified guidelines for economic evaluation and reporting of AI in healthcare.
- 5The article emphasizes ongoing interdependencies and evolving performance of AI systems in real-world clinical settings.
Why It Matters
Clear and comprehensive economic evaluations are essential for decision-makers considering the adoption of AI in radiology and wider healthcare. The lack of robust, standardized evaluation methods may impede informed investments and implementation of AI technologies.
Source
AI in Healthcare
Related News
•AI in Healthcare
Economic Evaluations of AI in Healthcare Face Major Gaps
A Finnish review finds significant deficiencies in how studies evaluate and report the economic impact of healthcare AI.
•Health Imaging
AI Platform Triples Functional Independence in UK Stroke Patients
AI brain imaging software deployed by NHS has significantly improved stroke outcomes and functional independence rates in England.
•AuntMinnie
AI in Breast Imaging Achieves High NPV but Raises Recall Rates
AI systems in breast imaging yield near-perfect negative predictive value but increase recall rates compared to radiologists, particularly for intermediate-risk classifications.