Who should be paying - and how much - for AI in healthcare?

There is still little known about the impact of artificial intelligence (AI) tools on healthcare. Early Health Technology Assessment (HTA) is a method that can help predict the financial and health outcomes of an intervention before it is implemented. One can for example simulate different prices and performances of the AI product to find out whether the tool is expected to be cost-effective.

This week one of the first papers was published using this method for the assessment of AI. More specifically the authors show the potential cost-effectiveness of using AI to the detection of large vessel occlusions in stroke diagnostics. This helps answer the question who should be paying - and how much - for AI in healthcare?

Spoiler alert: for this use case it shouldn’t be the radiology department.

Author Kicky van Leeuwen wrote a blog explaining the context and implications of the research. Also, this is the place to find the the early HTA model in Excel which can be adapted to varying clinical situations.

Read the full paper titled Cost‑effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment here.

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