Multiple guidelines recommend ongoing breast cancer risk assessment for women, beginning by age 25, to identify individuals at increased risk who may need enhanced breast cancer screening.1,2. A risk-based approach to breast cancer screening has been shown to be both acceptable and preferred.3. Further, digital cancer risk assessment tools, such as Ambry Genetics’ validated CARE platform,4, have made breast cancer risk assessment more accessible than ever. Here, we share three important insights from our 5+ years of experience implementing digital cancer risk assessment at breast imaging centers across the U.S.
Health systems have no shortage of successful AI pilots. Ambient documentation, revenue cycle automation, clinical decision support — individual use cases have delivered real results in individual departments.
By the time Dr. Jason Van Wagenen and Dr. Ken Ence sat down with Elevate Dental Partners in late 2021, they had already built something rare in dentistry: a long-established Denver practice with a 25-year patient base, a non-judgmental clinical culture, and the kind of community trust that only gets built over decades.
Early in my career, I remember when the transition from dental school to practice became very real. I had the clinical foundation and understood the science. What stood out quickly after becoming an Aspen Dental-supported practice owner was how much more there was to learn once I was responsible for diagnosing, treatment planning and delivering care independently every day.
Healthcare has spent years building digital front doors. The organizations pulling ahead are finally figuring out how to get patients to walk through them. As patient volumes rise and demand for seamless access grows, the call center alone can no longer carry the load. Every interaction that stalls, an unanswered call, a failed self-service attempt, an appointment that never gets booked, is a gap throughput. According to a 2025 Becker’s Healthcare survey, 60% of healthcare leaders cite patient experience as the primary driver of technology investment. The pressure now is delivering on that promise at scale.
June 3, 2026 – Peoria, IL and Clearwater, FL — hellocare.ai, a leading provider of AI-assisted virtual care and intelligent hospital room technology, today announced an expanded strategic partnership with OSF HealthCare to deploy the hellocare.ai platform across inpatient environments throughout the organization.
For payers still relying solely on claims data, the margin for improvement is shrinking. One regional health plan’s experience offers a blueprint for what’s possible when clinical data is put to work.
My mother is in long-term care.
When I show up to work every day, I’m not working from theory. I know what it feels like to trust a facility with someone you love. And after more than 30 years in healthcare—from the emergency department to community-based care to where I sit now—I also know how often the system makes that trust harder to earn than it needs to be.
In most industries, the last mile is where complexity—and cost—quietly accumulate. Healthcare payments are no different.
Hospitals and health systems have spent years optimizing front-end workflows like prior authorization and denials management. But one of the most persistent sources of friction lies further downstream—in the handoff between a payer’s decision and a provider’s ability to actually use that reimbursement. It’s the final leg of the relay. And as in any race, the outcome often comes down to how cleanly the baton is passed.
As healthcare systems navigate the transition to precision genomics, many are seeking partners who can help operationalize this shift at scale. Natera’s health system team works alongside health system leaders and providers to integrate advanced diagnostics into clinical workflows, improve operational efficiency, and enable data-driven insights — helping organizations move from vision to execution in delivering more personalized care.
Clinicians across the country are using AI tools their organizations never approved, often to solve real, urgent problems. The phenomenon, known as shadow AI, sits at the center of a governance challenge that is growing faster than most health systems can keep pace with.
Health systems are entering a new era of financial pressure, one where margin is no longer recovered downstream, but protected upstream.
Across the industry, leaders are navigating shrinking reimbursement, evolving payer behavior and rapid AI adoption. The question is no longer whether transformation is coming, but whether organizations are structurally prepared to act on it.
Patients today consult three or more online resources before scheduling an appointment, yet still find it difficult to get to the right provider.
According to RevSpring, nearly 40% report frustration trying to understand what care will cost, and one in four will delay or avoid care entirely because of cost concerns. For health systems, these aren’t just patient experience problems, they’re revenue problems that begin far upstream of the billing department.
Healthcare AI is leaving its experimental phase behind — most organizations are already using it, and 43% are piloting or testing agentic AI.
There are numerous success stories where healthcare organizations deployed AI in pilots or applied AI in a single department. These successes — which may have involved ambient documentation or use of AI in the revenue cycle — have demonstrated AI’s potential to improve clinical outcomes, decrease costs and deliver positive ROI.
15 to 20% of all first-time claims are denied, 65% of those denials are never resubmitted and 86% were entirely avoidable. The math adds up to $36 billion in annual revenue losses for U.S. health systems, plus an additional $20 billion spent trying to recover it.
Health plans are navigating rising medical costs, intensifying regulatory demands, margin pressure, evolving member expectations, and growing operational complexity, all while being expected to improve outcomes, affordability, and experience.
Health plans’ operations have historically been managed in silos, with each silo using different data. This has impeded efficiency and consistency for utilization management, payment integrity, member outreach, and other critical healthcare decision-making processes.
Payers nationwide are striving to operate more efficiently, while maintaining high levels of member and provider satisfaction. Success stems from reducing the friction and costs associated with core processes, like utilization management, appeals, medical necessity research and documentation for newly diagnosed patients.
Health systems are facing an escalating emergency department (ED) boarding crisis, driven in large part by the surge in behavioral health patients seeking care. Since COVID-19 pandemic, demand has intensified while capacity and coordination have struggled to keep pace.
Health systems today are caught in a familiar squeeze: shrinking primary care margins, a physician workforce stretched thin by burnout and patients increasingly seeking out more personalized care options. For a growing number of health system leaders, concierge medicine has emerged as a practical — and low-risk — way to enhance revenue, improve physician satisfaction and strengthen recruitment, all without disrupting existing operations.