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Digital Tools Can Prevent Medical Errors, But Only If We Design and Use Them “Correctly”

In an era of AI-assisted diagnosis, smart alerts, and electronic health records (EHRs), it’s tempting to believe that technology will solve our patient safety problems. And to a degree – it can 😊 Digital tools have helped us: ✔ Reduce prescription errors ✔ Improve documentation ✔ Flag drug interactions ✔ Track lab results in real-time […]
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Medication Safety

Look-alike sound-alike (LASA) drugs are medications that have similar names, spelling, or packaging, increasing the risk of confusion and medication errors. This can happen between different medications, brand-name and generic versions, or generic-generic versions. Insulin and Isoprinosine. Adrenaline and Atropine. In high-pressure healthcare settings, sound-alike, look-alike medications (LASAs) are not just a nuisance—they’re a quiet […]
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Speaking Up Saves Lives:

In healthcare, the stakes are high—one misstep can mean the difference between life and death. Yet, many frontline workers hesitate to report concerns due to fear of retaliation, blame, or being ignored. Building a safety-first culture isn’t just about following protocols—it’s about fostering an environment where speaking up is encouraged, valued, and acted upon. Why […]
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Ensuring zero harm to patient

Patient safety is a fundamental pillar of quality healthcare. Every hospital strives to provide the highest level of care, but ensuring a safe environment where patients receive treatment without preventable harm is a continuous challenge. As part of the broader quality dimensions in healthcare, patient safety focuses on reducing risks, preventing errors, and ensuring a […]
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Artificial Intelligence

The rapid integration of artificial intelligence (AI) into healthcare is revolutionizing the way patients receive care. AI-driven algorithms are improving diagnostics by analyzing vast amounts of medical data with incredible speed and accuracy, often detecting diseases like cancer or heart conditions earlier than traditional methods. Machine learning models can predict potential health risks based on […]
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