Client News Coverage

Eating just two slices of deli meat a day was associated with a substantially higher risk of dementia, according to a new review of ultra-processed foods (UPFs) and brain health.

The findings, published in the August 2026 issue of Annual Review of Nutrition, looked at dozens of human and animal studies, including one involving nearly 500,000 people in the U.K. The study found that each additional 25 grams of processed meat eaten daily corresponded with a 44% higher risk of all-cause dementia and a 52% higher risk of Alzheimer's.

Eating just two slices of deli meat a day was associated with a substantially higher risk of dementia, according to a new review of ultra-processed foods (UPFs) and brain health.

The findings, published in the August 2026 issue of Annual Review of Nutrition, looked at dozens of human and animal studies, including one involving nearly 500,000 people in the U.K. The study found that each additional 25 grams of processed meat eaten daily corresponded with a 44% higher risk of all-cause dementia and a 52% higher risk of Alzheimer's.

Every October, physicians hear some version of the same message: ICD-10 is changing, and physicians need to pay attention. That can make the annual update sound like another administrative task added to an already long list, but physicians don't need to memorize hundreds of new codes. What matters is understanding whether the changes affect the conditions they treat and, more importantly, whether their documentation captures the clinical detail needed to support accurate coding.

Healthcare's Artificial Intelligence (AI) conversation continues to center largely on clinical applications. Ambient documentation, generative AI assistants, and clinical decision support systems have captured headlines and investment dollars alike. These innovations are important, but they are overshadowing one of healthcare's key operationally impactful uses of AI: medical coding automation.

In  healthcare revenue cycle management (RCM), we’ve long relied on systems that process rules, not judgment. Robotic Process Automation (RPA) has been beneficial, automating repetitive, high-volume tasks such as claim status checks and  data entry. However, its limitations are increasingly apparent. Today’s revenue cycle challenges demand more than just speed and efficiency; they require adaptability, context, and intelligent decision-making.

That’s where agentic AI comes in.

Electronic Health Reporter»

Supplement stacking, fiber maxxing and the carnivore diet are just a few of the many diet trends people on social media can’t stop talking about. That’s on top of the diets that have been making waves for a while, like intermittent fasting, the keto diet, Paleo diet and intuitive eating.

With so many different, conflicting opinions about what it means to eat healthy, it’s hard to know what advice is actually worth following. If one of your goals is supporting your brain health as you age, the dietary advice you choose to follow is crucial.

Revenue cycle management companies are bolstering their executive leadership teams as they accelerate their investments in artificial intelligence and automation.

On Aug. 25, Waystar named former Salesforce executive Amit Khanna chief product and technology officer and promoted Todd Woods to chief commercial officer. CEO Matt Hawkins said in a release announcing the appointments that revenue cycle is entering a “fundamentally new era, where intelligent technology will increasingly orchestrate complex workflows and take action toward resolution.”

In this Q&A, Leigh Poland, vice president of Coding Services, Clinical Quality and Education at AGS Health, examines what healthcare organizations need to do to prepare for the FY 2027 ICD-10-CM updates taking effect Oct. 1.

There are 190 new diagnosis codes, 30 deletions and four revisions for 2027.

Clinical documentation improvement professionals and revenue cycle leaders need to do more than review the new and deleted codes to update the system, according to Poland. The bigger challenge is making sure those changes actually translate into consistent documentation.

For the past several years, the conversation around AI in medical coding has been dominated by a single question: How much of the coding process can actually be automated? It’s an understandable question. Health systems continue to face mounting pressure from workforce shortages, increasingly complex coding requirements, evolving payer expectations, and persistent financial challenges. AI has demonstrated that it can help address many of these issues, particularly by accelerating routine coding tasks and improving consistency.

But in my conversations with healthcare leaders across the country, I have noticed a shift in the conversation. The organizations making the most meaningful progress aren’t asking how to remove people from the process. Instead, they’re asking how to combine AI with the expertise of experienced coding professionals to improve accuracy, strengthen compliance, and create more resilient coding operations.

Electronic Health Reporter »

The healthcare industry is constantly evolving. And with a growing urgency to balance razor-thin margins in a heightened regulatory environment, with evolving payment models and relentless pressure to improve financial outcomes, healthcare leaders need immediate insights from copious amounts of data to steer their ships in the right direction.

CTI Technical Services, based in the Philadelphia area, provides comprehensive IT solutions, including managed services, cybersecurity, network design, and structured cabling for businesses, with a specialization in sectors like dental, education, and hospitality. Pulse 2.0 interviewed CTI Technical Services CEO Erik Eisen to learn more.

Healthcare finance leaders have long operated under a familiar assumption: financial risk becomes visible after a claim leaves the organization. Denials arrive. Audits begin. Payment delays appear. Teams then investigate, appeal, and recover what they can.

That assumption no longer reflects today’s reality. The most significant revenue threats now begin long before a claim reaches a payer.

Of the medical diagnoses that cause anxiety, sorrow, and despair for patients and their loved ones, Alzheimer’s is near the top of the list. An incurable condition that slowly robs people of memory, identity, and independence, Alzheimer’s puts immense financial and emotional burdens on families.

In the complex ecosystem of modern healthcare, the battle is no longer fought only in operating rooms and patient wards. A second front has opened in the back office, a high-stakes conflict over revenue, compliance, and data. Here, healthcare organizations face a relentless barrage of payer audits, complex coding denials, and shifting regulations that threaten their financial stability. In this environment, a new class of defensive technology is emerging, and recent data suggests it’s having a decisive impact.

MDaudit, a company specializing in AI-powered risk monitoring, recently received an overall performance score of 94 out of 100 in a “First Look” report from KLAS Research, a firm renowned for its independent, provider-funded evaluations of healthcare technology. This score not only surpasses the Best in KLAS software average by nearly 13 points but also comes with A+ ratings from customers for partnership, innovation, and likelihood to recommend. While impressive on its own, this validation points to a much larger trend: the critical role of AI in building more resilient financial systems within our most essential institutions.

Brief Glance Intelligence»

At first glance, the April 1, 2026, ICD 10 update from CMS and NCHS looks deceptively quiet. ICD 10 CM adds no new diagnosis codes, retires none, and leaves the Official Coding Guidelines untouched. It reads like a maintenance cycle, but that surface-level stability masks a more meaningful shift.

The 2026 update is less about what codes exist and more about how coders are expected to use them. It subtly changes the internal logic of classification, shifting decision-making away from structured hierarchies embedded in tabular instructions and toward greater reliance on clinical judgment and encounter context.