Radiologists Need AI That Works Where They Work, Not Standalone Software
Current AI tools often increase the disruption that radiologists already experience from using non-integrated platforms.
Healthcare IT Isn’t Broken — But How We Design It Might Be
Healthcare needs systems that work for providers, for health plans, and most importantly, for patients. And that starts with designing not just for technology, but for the people who depend on it, people who need to trust it will work when it matters most.
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The Healthcare Payments Industry Has a Perception Problem
Healthcare payments are no longer about transactions. It’s about controlling the revenue cycle. And increasingly, that control is not sitting with ISOs.
Executing Biologics Technology Transfer through Integrated Operating Models
As biologics modalities diversify and processes grow complex, the success of tech transfer depends on integrated execution rather than each procedural completion.
DPC Is Scaling — The Financing Architecture Isn’t Ready
Growth without structural discipline creates risk. And the risk that has gone largely unexamined in the DPC advocacy space is the one that matters most to the broader healthcare system: what happens to insurance risk pools when healthy lives migrate out of them?
Weaving a Unified Fabric of Care Will Heal the Patient-Provider Relationship
Healthcare can transform only when strategy, workflow, data, and human connection operate together with a single purpose: strengthen the relationship at the center of care.
Healthcare’s AI Illusion: Why Integration, Not Algorithms, Will Define the Next Decade
Healthcare’s next transformation will not come from algorithms that try to replace doctors but from infrastructure that connects their tools.
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Top 7 Modern AI-Powered EAP Providers for Global Workforces in 2026
Discover the top AI-powered EAP providers for 2026. Compare platforms like Kyan Health and Spring Health on triage speed, global reach, and clinical quality to transform workforce wellbeing.
Why Traditional EMRs Are Holding Healthcare Back
Instead of creating new opportunities, traditional EMRs are constraining AI’s potential in healthcare.
The Integration Opportunity: A Blueprint for Reliable Device Data
A clinically led, cross-functional team approach is essential during medical device integration projects to close data gaps, overcome common project pitfalls, complete optimal testing, and ensure proper oversight.
Making AI Count: 3 Ways Healthcare Leaders Can Drive Real ROI
Providers stand to gain a lot by making smart AI and automation decisions, but that value depends on investing in the right places. It may be tempting to plug in a single-point solution to fix an immediate challenge, but a more strategic, long-term approach will unlock greater value.
Upholding “Do No Harm” in the Age of AI
As AI tools continue to evolve, they promise to empower clinicians and administrators with actionable insights, improve patient outcomes, and create more resilient healthcare systems.
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The Power of Real World Data to Study Women’s Health at Scale
Veradigm examines key clinical trends, comorbidity profiles, and treatment trends across adolescence, reproductive years, and peri-/post-menopause. Download it today!
The Hidden Cost of Disconnected Quality Systems: Why Hospitals Should Modernize Now
The case for modernization isn’t solely about improving efficiency. It’s about equipping hospitals with the resources necessary to manage risk proactively, respond to negative trends quickly, and prioritize patient safety with high reliability.
The Future of AI in Healthcare Demands Transparency, Trust, and Human-Centered Design
As real-time inference overtakes training-centric approaches, a pivotal question emerges: how can the human element remain central in an increasingly autonomous ecosystem?
Payments Simplified: The 4 Key Features of Modern Healthcare Payment Platforms
Simplifying payments isn’t just about transactions; it’s about building better relationships and ensuring financial health through protection, payment choice, scale, and integration.
First Principles Thinking for Healthcare IT: AI Integration and Life Sciences
The right AI model applied to the right problem exponentially enhances our ability to match patients with potentially life saving treatments faster and more effectively. The only “trick” required for truly successful AI integration — in life sciences or any other facet of the healthcare industry — is clarity of purpose.
Why Playing Nice is a Competitive Advantage
When systems integrate better, every minute saved by removing roadblocks is a minute given back to clinicians and patient care. It’s time for vendors in this space to treat interoperability as a core business strategy rather than a buzzword or another box to check as they’re going through the motions.