AI in Pharmacovigilance: Why Governance Will Define Success
As adoption accelerates, organizations must ensure that the use of AI strengthens and not weakens accountability and patient safety.
Healthcare Is Deploying AI Tools — It’s Not Ready for AI Colleagues
Most healthcare organizations are experimenting with AI. Few are preparing to manage AI agents as participants in everyday healthcare workflows.
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Closing the Quality-Affordability Gap in Workplace Mental Health
In an interview, Kyan Health Co-Founder and Chief Commercial Officer Konstantin Struck discussed how Kyan gives mid-market and enterprise employers access to premium workforce mental healthcare, at a price point that is affordable.
Former Mayo Clinic Leader Sues System Over Alleged AI Cover-Up: 6 Things to Know
A former Mayo Clinic research director claims she was silenced, demoted and ultimately fired for sounding the alarm on AI safety and patient privacy lapses at the health system. Traci Tamiko Eto is now suing Mayo for retaliation.
From Copilots to Clinical Judgment: The Next Phase of AI in Digital Behavioral Health
The next phase of AI in healthcare is about building systems where human clinicians, supervisors, and AI can all contribute, challenge each other, and improve how decisions are made.
Healthcare AI Is Only As Good As the Systems That Govern It
AI doesn't just demand better processes. It requires a complete redesign of traditional healthcare operations for a new level of precision, traceability, and governance. A new operating model that the vast majority of healthcare organizations simply aren't built around today.
AI Health Check: No Governance, No Trust
Will doctors or patients who are burned by one AI solution trust the next one they’re given? Probably not. That’s why every provider rolling out AI tools has to understand this risk and build governance into its development process.
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From Blind Spots to Better Outcomes: How SNF Data Transparency Strengthens LTSS
What if health plans could identify member decline before an avoidable hospitalization occurs? Real-time clinical visibility into long-stay SNF members uncovers risk earlier and drives better outcomes.
Scaling Autonomous AI in Healthcare Without Compromising Clinical Trust
AI in healthcare will not fail because the models are weak. It will stall when leaders hesitate to redesign how decisions are made, measured and governed.
Shadow AI and the Governance Gap: Leading Healthcare Through the GenAI Revolution
GenAI has real promise, but it’s also bringing real risks. It is not about whether we should use it but how we can use it responsibly and with positive outcomes.
When Innovation Outpaces Oversight: Lessons from IV Spas to AI
We should never wait for tragedies to force a conversation around clear governance and accountability. Oversight has to evolve alongside innovation to protect people before harm occurs.
How Are Healthcare Leaders Tackling Automation Bias?
At MedCity News’ INVEST Digital Health conference, healthcare experts explored strategies to mitigate automation bias — emphasizing the importance of vendor responsibility, use case-specific governance and clinician engagement.
Where Will AI Deployment Benefit Payers the Most?
We are taking a look at how health insurers are using AI, defining success, and managing cybersecurity risks. Give us your opinions by completing our brief, anonymous survey.
Don’t Let the Floor Fall Out From Under Healthcare AI: Tips from UW Health’s CMIO
Without trust, the rapid adoption of AI in healthcare could stall, pointed out Joel Gordon, UW Health’s chief medical information officer. He urged healthcare leaders to focus less on flashy rollouts and more on governance, collaboration, and meaningful metrics to ensure AI delivers lasting value.