Future-forward RCM: deterministic at the core, agentic at the edge
The future of revenue cycle management combines traditional automation for routine tasks with agentic AI to resolve complex reimbursement issues, escalating cases to human experts when judgment is needed.
The hospital of the future runs on connected intelligence
Healthcare’s future depends on connecting AI, people and workflows to reduce administrative burden, improve operational and financial performance, and give clinicians more time to focus on patient care.
Patients, ‘the fastest-growing payer,’ could also be the best-performing one
Purpose-built AI can simplify patient billing by clarifying financial responsibility, resolving payment issues and building trust, improving both the patient experience and provider reimbursement.
The autonomous mid-cycle keeps the patient story intact
AI-powered platforms can improve revenue cycle accuracy by connecting clinical documentation and coding across the patient journey, allowing healthcare professionals to focus on cases requiring human judgment.
AI must earn its place in healthcare operations by showing its value
Healthcare leaders should evaluate AI and automation investments based on measurable outcomes, organizational priorities, and their ability to improve revenue cycle performance and workflows.
Capex surges to highest since 2008
Hospital and health system capital expenditures in fiscal 2025 reached their highest since the start of the financial crisis in 2008, according to Fitch Ratings Capital expenditure (capex) as a percentage of depreciation expense surged to 142.7% in fiscal 2025, the highest since it was 154.4% in fiscal 2008, among the hospitals and health systems…
Hospitals confront nursing opposition to AI
Health systems’ adoption of artificial intelligence to improve productivity increasingly is meeting opposition from their nursing staff. Nurse opposition to AI has become most visible in nurse strikes, where limits and guardrails on AI deployment for clinical and administrative uses have emerged. Sixty-five percent of hospitals reported using AI or predictive models integrated with their…
AI moves beyond revenue cycle
An AI tool helped to cut emergency department (ED) lengths of stay (LOS), a recent study found. That improvement demonstrates the technology’s potential to drive operational efficiency, says one of its authors. The prospective study, which was published last month in the journal Nature, used an AI model to predict hospital admission risk for ED…
Predict, prevent, perform: The AI evolution of denials management
Healthcare providers continue to face escalating denial rates that erode financial performance and operational capacity. In 2025, denial rates averaged near 12%, with many organizations experiencing even higher volumes — each percentage point representing millions of dollars tied up in unresolved claims. The growing volume and complexity of denials are no longer manageable with legacy,…
How to use an enterprise approach in implementing AI in RCM
Revenue cycle transformation has long been framed as a matter of technological advances. But in the AI-fueled era, the differentiator is shifting from individual technologies to enterprise operating model redesign, according to leaders from Mayo Clinic and Jefferson Health. They described how their organizations are repositioning revenue cycle as a core component of care delivery,…