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Case Study: Healthcare & Life Sciences

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Fixing AI Governance in Healthcare Before It Puts Patients at Risk

A healthcare system integrated AI for diagnostics and patient risk assessment. Instead of improving care, the AI flagged incorrect diagnoses, overlooked critical conditions, and made treatment recommendations that no one could explain. Regulatory scrutiny was inevitable.

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The Problem

- Developed an AI governance framework to ensure clinical decisions met ethical and regulatory standards.
- Standardized patient data sources to reduce inconsistencies across hospitals and labs.
- Implemented audit trails so every AI-generated recommendation was traceable and explainable.

What We Did

✔ Reduced AI misdiagnoses by 30%, improving patient safety.
✔ Passed regulatory compliance checks with zero flagged violations.
✔ Increased clinician trust—AI recommendations were now backed by clear medical reasoning.

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Results

AI in healthcare isn’t just a tech upgrade—it’s a medical liability if done wrong. If doctors don’t trust the system and regulators see risk, it fails. We ensured this AI wasn’t just accurate—it was accountable.

The Takeaway

Danny Katz Consulting

We help companies fix knowledge chaos, streamline AI governance, and build systems that actually work. Whether it’s unsearchable knowledge silos, AI making bad decisions due to bad data, or compliance teams struggling with operational execution—we solve the problems that stall productivity, increase risk, and waste time.