HFMA

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Revenue cycle management in healthcare is the process of tracking revenue from patients, including patient registration, claim submission, reimbursement, and communication with insurance companies, and is essential for providing a positive patient experience.

When is it OK to have financial discussions with patients? A reasonable attempt should be made to have the discussion as early as possible, before a financial obligation is incurred (i.e., before care is provided). Timely discussions

HFMA presents a detailed summary of the proposed rule issued by CMS updating payments under the hospital outpatient prospective payment system and the ambulatory surgical center payment system for CY 2025.

HFMA presents Part I of three detailed summaries of the proposed rule relating to the Medicare physician fee schedule for CY 2025 and other revisions to Medicare Part B policies.

Managing the healthcare revenue cycle is more challenging — and more critical — than ever. Amid sluggish margins, ongoing staffing challenges and rising costs, providers feel unprecedented pressure to optimize their revenue cycles. Addressing the ever-increasing issue of denials is a great place to begin. The latest data on denials and proven strategies to reduce…

HFMA presents a detailed summary of the CY 2025 proposed rule updating payment rates for home health agencies.

Learn about how Provider Practice Benchmarking allows medical group leaders to directly measure their performance across more than 150 physician and advanced practitioner specialties in a number of areas from a single reporting platform.

While healthcare organizations rely on native EHR functionality for certain revenue cycle management (RCM) tasks, they increasingly look to third-party solutions for others. But what questions should they be asking? Check out key takeaways in this research report.

UChicago Medicine discovered that they are ahead of other healthcare institutions in their use of AI for revenue cycle, and they are focusing on using AI to strengthen business outcomes, supporting a culture of AI innovation, implementing a governance framework, and measuring and optimizing performance.