| 4 Min Read

Mid Revenue Cycle Management: How to Measure, Manage, and Minimize Leakage


Key Takeaways:

  • Clear, consistent and complete documentation is crucial to the bottom line: it drives the final reporting of codes, enables accurate reimbursement, and minimizes denials
  • Every step of the documentation review process presents opportunity for leakage, meaning leakage occurs even with high functioning CDI teams
  • Staffing shortages require CDI teams focus their work on the cases with the greatest likelihood of discrepancy between the clinical evidence and documentation – but without technology identifying these cases is an exercise in futility
  • Artificial intelligence and machine learning based on large data sets is the best kind of technology to assist in this space: it can understand patterns and recognize what’s happening in the clinical care

Iodine Intelligence tackles a new challenge in healthcare’s mid-revenue cycle every month, shedding light on problems and solutions and sharing valuable insights from industry experts. Listen to Episode 1: Mid Revenue Cycle Management: How to Measure, Manage, and Minimize Leakage to learn more.

As healthcare providers operate on tighter and tighter margins, paying close attention to both efficiency and appropriate use of resources becomes more crucial than ever. This necessitates greater accuracy and depth in documentation, and while the answer may seem to be daily patient record reviews to identify discrepancies between the clinical evidence and the documentation, the reality is there aren’t enough trained, human resources to do this. The challenge becomes: where do I deploy the staff that I do have, and how do I prioritize which cases to review.

However, between changes in clinical definitions, documentation and coding guidelines, annual updates, and quality metrics and benchmarks, knowing what to focus on and which area has the greatest return can be a daunting task for CDI teams.

“We can’t be targeting a particular metric or condition saying ‘This is how I’m going to solve all problems,’ because it’s only solving a very small problem. Documentation integrity is no longer just important to a single payer or a single type of patient, it’s important in every case”
– Fran Jurcak, Chief Clinical Strategist

Technology may hold the answer for overwhelmed CDI teams. Artificial intelligence (AI) coupled with machine learning (ML) can look for discrepancies between the clinical evidence and what is actually documented, and then highlight those cases for CDIS to review. Software solutions can introduce efficient and automated workflows. Leveraged appropriately, this trifecta allows CDI specialists to focus on the right charts, find discrepancies, and fix any problems.

‘Its not about replacing people it’s about augmenting their ability to do their job well. Creating efficiency in their workflow and really allowing them… to really focus in on what they can do to help. Because in the end it’s about ensuring that we’re able to provide quality care to patients” – Fran Jurcak, Chief Clinical Strategist

Interested in Being on the Show?

Iodine Software’s mission has been to change healthcare by applying our deep experience in healthcare along with the latest technologies like machine learning to improve patient care. The Iodine Intelligence podcast is always looking for leaders in the healthcare technology space to further the conversation in how technology and clinicians can work together to empower intelligent care. if that sounds like you, we want to hear from you!