Adverse drug interactions are responsible for thousands of hospital admissions each year, and half of them are entirely preventable.

In an age of advanced diagnostics, precision medicine, and AI, this statistic should make us pause. Despite the tools we have, patients continue to fall through the cracks. Polypharmacy in older adults is increasingly common. Real-time prescribing decisions are made under pressure. Cross-speciality communication gaps persist.

But this is where healthcare must evolve.

More innovative e-prescribing platforms should do more than flag duplicate therapies. They should understand patient context, adjust for renal or hepatic impairment, and learn from prior outcomes.

AI-driven clinical decision support systems can help clinicians identify subtle yet serious drug-drug interactions that standard checklists may overlook.

Integration with pharmacy, primary care, and hospital records can ensure continuity and safety across transitions of care.

AI-powered decision support systems, such as Katana, can detect subtle yet serious interaction risks that conventional systems often miss, transforming how we prevent medication errors. It doesn't just flag issues it explains them, empowering clinicians and patients alike to make safer choices. We already have the data. We have the computing power. Now, with platforms like Katana, we also have the tools.

What is needed is a collective will to embed safety-first thinking into every prescribing decision.

Because if we know that 50% of drug interaction events are preventable, letting them happen isn't just unfortunate; it is indefensible.