For years, healthcare organizations have approached Medicare fraud and billing compliance as primarily a retrospective exercise. Claims are submitted, payments are made, audits follow, and organizations investigate problems after they surface.
That model is becoming increasingly unsustainable.
The federal government is moving toward a more aggressive approach to Medicare program integrity, using data analytics, artificial intelligence (AI), and machine learning to spot suspicious billing
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Health IT & Digital Health-Opinion | Op-Eds | Guest Columns | Analysis, Insights - HIT Consultant
Why the RPG Skills Gap Is Healthcare’s True Cybersecurity Blind Spot
Here’s a plausible scenario from the not-so-distant future. It’s 2 a.m. on a holiday weekend, and a hospital’s claims or records system throws an error. This is mission-critical infrastructure we’re talking about, and these systems process mountains of personally identifiable information every hour of every day. Night staff at the security operations center need to know: Is this just a routine glitch or is there an active breach? However, there’s only one person who knows the answer — and she
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From Automation to Agency: Rethinking the Future of Healthcare
For years, healthcare provider organizations have pursued automation to improve revenue cycle efficiency. Rules-based workflows, robotic process automation, predictive analytics, and machine learning have each helped reduce manual intervention and accelerate the completion of repetitive tasks.
But reimbursement for specialty healthcare services, such as laboratory, radiology, pathology, and specialty pharmacy, is becoming too complex for efficiency alone to solve.
The challenge facing
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Clinical Validation Audits Are Putting Hospital Reimbursement at Risk
When was the last time your team won an appeal on a clinical validation downgrade? If you have to stop and think about it, you are not alone.
Payer behavior has made this harder than it used to be. Clinical validation audits are driving a marked rise in Diagnosis-Related Group (DRG) downgrades, forcing hospitals to defend diagnoses that, for years, were accepted on the strength of a physician's documentation alone. As audits grow more frequent and the criteria keep shifting, traditional
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Re-Engineering Workflows to Bridge Healthcare’s AI ROI Gap
Artificial intelligence (AI) has now reached a crucial tipping point in the way U.S. healthcare plans carry out their operations. A study by Everest Group, supported by Sagility, found that 70% of health plans have introduced AI tools to streamline both administrative and clinical activities. Nevertheless, 84% of payer executives say that they have seen limited benefits from these implementations and just 10% have noticed measurable improvements in operations.
The fact that these systems are
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The Biggest Vendor Risk in Healthcare Isn’t in the Operating Room
Over the past two years, healthcare leaders have been forced to rethink what operational resilience really means.
The cyberattack on Change Healthcare demonstrated how dependent providers had become on a single third-party platform for everything from claims processing to cash flow. The attack on Ascension showed how quickly disruptions to technology can spill over into clinical operations, delaying care, forcing clinicians back to paper documentation, and disrupting the day-to-day
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The Missing Line Item in Healthcare AI ROI Is Exception Handling
Healthcare executives often evaluate artificial intelligence with a familiar checklist: model accuracy, integration effort, implementation time, and license cost. That list omits the expense that determines whether an administrative AI project creates capacity or creates another system to supervise. The missing line item is exception handling.
The demand is real. In its 2026 Physician Survey on Augmented Intelligence, the American Medical Association reported that 81 percent of respondents
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Hospitals Need Authority Maps for AI Agents
Hospitals are beginning to give AI systems something more consequential than the ability to generate text: permission to act. That shift is already underway. A September 2026 survey of 250 U.S. healthcare leaders found that 28% of organizations had agentic AI in production and another 44% were piloting it, while 72% reported AI tools or agents deployed without formal IT approval. The problem is no longer simply whether a hospital has an AI governance committee. Health systems need to know, agent
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The Next Competitive Advantage in Drug Development Won’t Be a Better Molecule. It’ll Be Better Patient Selection.
For decades, the industry has organized itself around a single question: how do we discover more, and better, drug candidates? Target identification keeps getting smarter, molecule generation keeps getting faster, and AI has now touched nearly every stage of early discovery. Yet a molecule is only ever as good as the patients it happens to be tested on, and that half of the equation has received a fraction of the innovation investment.
Consider what happened across non-small cell lung cancer
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Evolving the EHR from a System of Record to a System of Action
The EHR is poised to evolve from its original role as a place to store patient information. The next step is for it to take a more active role in the patient care journey.
As more of the journey becomes digitized, the EHR can help move work forward by connecting workflows, surfacing what needs attention, and using AI to reduce administrative burden. This shifts the EHR from a system of record to a system of action.
In ambulatory care, that shift has practical implications. Scheduling,
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