TEHAI (Translational Evaluation of Healthcare AI)
TEHAI is a framework designed to evaluate how well artificial intelligence (AI) systems can be used in real healthcare settings. It looks at whether the AI works well, adds value, and can be successfully adopted in practice, with attention to ethical and practical issues.
At a glance
Use when
Evaluating AI systems for real-world clinical implementation,Assessing translational readiness of AI tools,Guiding development of AI systems with end-use in mind,Conducting multidimensional assessment of AI beyond technical performance
Avoid when
When only regulatory compliance check is needed,When evaluating non-AI health technologies,When resources for comprehensive evaluation are unavailable
Inputs
AI system design, development stage, clinical context, ethical considerations, technical performance data
Outputs
Comprehensive assessment of AI system's translational readiness across capability, utility, and adoption dimensions
How it works
TEHAI (Translational Evaluation of Healthcare AI) is a peer-reviewed evaluation framework developed through a literature review and expert consensus to assess the translational aspects of AI systems in healthcare. It comprises three components: capability (technical performance), utility (clinical and operational usefulness), and adoption (organizational integration and ethical considerations). It is grounded in translational research principles and supports evaluation across all stages of AI development and deployment.
- HTA domains
- Clinical Effectiveness, Organisational aspects, Patient and Social Aspects
- Assumptions
- The framework assumes that successful AI implementation requires more than technical performance and must include utility and real-world adoption factors; also assumes multidisciplinary input is available for evaluation
- Strengths
- Comprehensive coverage of translational aspects; applicable across development stages; grounded in translational research theory; includes ethical and organizational considerations; developed via international expert consensus
- Limitations
- May require adaptation for specific local contexts; does not replace regulatory assessment but complements it; practical application depends on availability of detailed system and deployment data
- Also known as
- Translational Evaluation of Healthcare AI
Questions this answers
- › How well does the AI system perform technically?
- › Does the AI system provide meaningful benefits in clinical practice?
- › What are the barriers and facilitators to adopting the AI system in real-world settings?
- › How are ethical considerations addressed in the AI system's design and use?
- › Can the AI system be generalized across different healthcare environments?
- › How does the AI system integrate into existing clinical workflows?
References & sources
Similar by meaning
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