You could recover millions of dollars in revenue by efficiently retrieving and abstracting medical records, identifying missed diagnoses,and accurately reporting additional hierarchical condition category (HCC) codes in risk adjustment filings for CMS. But you could also incur penalties if you cannot support your diagnoses.
Here are four ways to use Medicare risk adjustment to improve revenue forecasting:
1) Verify coding accuracy
Because risk adjustment payments ultimately depend on your ability to substantiate the Hierarchical Condition Category (HCC) relevant diagnoses that you submit to CMS, on going audit of your data, especially with chart reviews, is critical.
Forecasting revenue with any degree of certainty requires a high degree of coding accuracy.
Review your plan’s filtering logic against that which CMS publishes and uses on EDPS. Routinely check to make sure your claims processing system working with an updated version of the National Correct Coding Initiative Edits. Look for claims with missing or incorrect information.
Improve accuracy by managing processes, programs, vendors, staff, and providers based on data-driven performance. Pay close attention to coding-related updates in CMS regulations to ensure continued compliance and accuracy. The more accurate your coding is, the less likely you are to receive overpayments from CMS, which means you can project revenue with more certainty.
2) Integrate data
You must reconcile complex information from disparate sources (i.e., enrollment, eligibility, benefit, claims, care management systems, EMRs) in order to improve Medicare risk adjustment.
Manage revenue integrity holistically by investing in systems and tools that facilitate collaboration with revenue management, care management, provider services, IT and other disciplines.
Streamline processes and improve access to data so that you can simultaneously address quality and risk adjustment. Consolidate responsibility for both types of initiatives into a single position or clearly delineate roles within your organization so that improvements in either area can benefit the other, such as in the form of improved revenue forecasting due to advancements in quality measurements.
3) Track your performance
Metrics can help you project revenue. Create reports around factors that affect risk adjustment payments, such as plan enrollment and chart reviews.
If you can assess your risk adjustment performance at any given time, you can evaluate the potential impact of any decisions before they are made and quantify them afterward. You should be able to tell how well you are validating existing risk adjustment factor scores as well as your progress in identifying and substantiating new diagnoses as they arise, for example.
4) Blend initiatives
You cannot rely on one type of risk adjustment alone when forecasting revenue. Mix prospective, concurrent and retrospective initiatives to get more accurate risk scores and stronger predictors of revenue.
Retrospective data can also help you perform better in a prospective model by assisting you in identifying providers who can improve documentation and in targeting members for better care. Determining how and when to treat members will improve health outcomes and risk scores.
A multi-faceted Medicare risk adjustment strategy that is built upon complete, accurate and timely data will allow you to project financial performance with a reasonable degree of certainty. Follow the four steps above to improve your revenue forecasting.