Missing the Point: Isolation Alone Will Not Build AI Safety
Treating AI agents like contract nurses and minimizing their access to critical patient information certainly reduces potential risk. But, it also minimizes key opportunities.
The Big Challenge for AI in Healthcare Comes After Approval
Typically, software placed on the market will undergo changes and updates after its initial release. In the case of healthcare AI, changes can occur, often unexpectedly, even when the developers have not updated the model.
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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.
AI Didn’t Reduce Clinician Burden — It Just Moved It
Documentation tools have value. They solve a visible pain point well. But solving a visible pain point is not the same as solving the right one.
The Dangerous Illusion of the “Two-Week AI Expert”: A Call to Action Against Superficial Medical Education
If we choose the quick fix, let us be honest about the consequences: when an unexamined algorithm leads to a fatal diagnostic error, the blame will not lie with the black box. It will lie with us, because we were too reckless to teach the fundamentals when we still had the chance.
When Medicaid’s Data Can’t Verify Eligibility, Members Shouldn’t Lose Coverage
When verification fails and an eligible member loses coverage, treatment can be interrupted, medications can go unfilled and manageable conditions can become medical emergencies.
Work Requirements Put New Pressure On Medicaid Member Retention
By using existing data to better understand members and implementing retention strategies, plans can remain sustainable and members can get the care they need.
Why Pharma Companies Should Look To Social Media For Better Patient Insight
Healthcare decision-makers, especially at pharmaceutical companies, must prioritize patient input. Data collected from social media listening is a significant step in the right direction.
A Market, Not a Mandate, Is the Fastest Way to Bring AI Into Hospitals
The cost of waiting is not evenly distributed. Rural and critical access hospitals report under 50 percent adoption of even basic predictive tools, compared with 86 percent among top-tier system-affiliated hospitals. Every year without a bridge widens that gap, and it widens it fastest for the hospitals with the least room to absorb it.
Congress’s Patient Matching Fix Won’t Work — Here’s What Would
The MATCH IT Act aims to reduce patient matching errors. But a model used by vital records systems could provide a better solution.
Why SDoH Programs Fall Short — and What It Takes to Make Them Work
Throwing more money at SDoH programs isn’t going to magically fix them. Instead, plans should be focusing on building out these three specific capabilities that, together, can noticeably alter the playing field.
Your Product Works — So Why Does It Still Fail in the Real World?
A patient's automated risk score was reassuringly green. Pulling from a sparse medical record and infrequent acute visits, the model flagged him as low risk and routed him to the default, low-touch outpatient pathway — so why was the patient actively deteriorating?
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The AI-Native Clinician Is Already Here. Medical Education and Health Systems Need to Catch Up.
Medical students, residents, and fellows are not waiting for formal guidance on artificial intelligence before putting it to use.
The Impending End of Cross-Subsidization
There is no single solution to the cross-subsidization problem. But here are some strategic actions that can make a health system’s economics more sustainable.
How AI Is Connecting MedTech’s Data Without Compromising Compliance
The connected, agent-ready enterprise is the model that wins, where compliance and intelligence operate together.
Why the Future of Healthcare Depends on Reinventing Primary Care Access
What is needed is a fundamentally different operating model for primary care, one designed around continuous engagement rather than episodic encounters.
Why Agentic AI Works in Hospitals When You Strip It Down
Many hospitals are now trying to use AI to automate processes and free up staff time, running simultaneous pilots to perform as many tasks as possible. This quickly leads to pilot sprawl — a state where organizations can no longer even say which agents are still in active use.
What Life Sciences Commercial Teams Can Learn from Digital Health
The pace of change in digital innovation has exposed the ever-widening gap between digital health and Pharma commercial teams. As a result, Pharma is missing out on its ability to significantly improve its commercial model, by focusing on efficiencies vs. truly reinventing.