Can AI Really Handle Your OTC Dosing Questions?

As large language models (LLMs) become more embedded in our daily lives, their applications in healthcare, particularly in answering medication queries, are under scrutiny. With the increasing reliance on AI for advice about over-the-counter (OTC) medications, like acetaminophen and ibuprofen, it's critical to assess their accuracy and reliability.

DOSEBENCH: Measuring AI's Medication Accuracy

Enter DOSEBENCH, a benchmark designed to test the proficiency of LLMs in handling common dosing scenarios. The study focuses on 81 curated cases involving adult use of acetaminophen and ibuprofen. By analyzing 1,620 responses from four different LLMs, the study aims to evaluate aspects like decision correctness, consistency, and the verifiability of explanations.

The results? Not exactly confidence-inspiring. The models frequently fumbled with the complexities of rolling-window calculations and cases requiring nuanced judgment. Even when they appeared confident, their answers often violated dosing constraints. The regulatory detail everyone missed: determining safe medication dosages is far from trivial for AI.

Why This Matters

Why should you care? If AI can't reliably advise on something as straightforward as OTC medication dosing, what does that imply for more complex medical queries? In clinical terms, this shortcoming reveals a significant gap in AI's ability to handle safety-relevant information.

Surgeons I've spoken with say that while AI shows promise, its role should be supportive, not advisory. For now, leaving all dosing decisions to AI could be risky. It's not just about getting the math right. it's about understanding patient context and medical history, areas where AI still has a long way to go.

The Path Forward

This leads to a critical question: Are we rushing to integrate AI into healthcare without fully understanding its limitations? The FDA pathway matters more than the press release. Regulation will need to evolve alongside technology, ensuring that patient safety remains key.

, while AI is a formidable tool in many domains, it's not infallible in healthcare. As the industry continues to develop these models, keeping a cautious eye on how they handle clinical complexities will be vital. Until then, perhaps it's best to keep a human in the loop your health.