Have you noticed an uptick in pended claims due to codes: M35.81 - Other specified systemic involvement of connective tissue and M35.89 - Multisystem inflammatory syndrome? These were two of the new codes CMS released on December 4th, 2020, as part of their off-cycle ICD-10-CM update, to support COVID-19 related care. Normally (meaning, pre-COVID times), CMS would release new code updates in the month of June, giving payers three months to get them configured and updated in claim systems by October 1st. But alas, we are living in different times.
If you happened to catch the CMS COVID update, and were able to get it expedited through your change management process, you were ready to accept claims starting on the effective date of January 1st, 2021. If you did not get this updated in time, you could have claims pending as the configuration for these new codes may have not made it to your claims processing system before the claims started coming in.
The cost of inaccurate reference data
If you work for a Payer, you know that pended claims are not good, but you may not recognize the financial leakage that the organization may be experiencing as a result if one of these new codes come in and is not detected. An auto-adjudicated claim costs about $.90 to process, whereas a claim that requires manual intervention costs about $20 per claim. And while best practice is to have an auto-adjudication rate of about 85%, this is typically a stretch goal due to the significant inaccuracies of the claim data. These challenges then have dramatic impacts on the health plan margin, but also the relationships with their providers (provider abrasion), and even contribute to member dissatisfaction.
Sometimes the financial leakage within a payer organization is not easily detectable. For example, after CMS released the new COVID-19 ICD-10-CM codes, did you know that code M35.8 - Other specified systemic involvement of connective tissue was no longer a billable code as of January 1st? If you did not, then your claims are still likely adjudicating, and you will not see a decrease in your first pass rate. Unfortunately, that means you are paying for a code that is no longer valid, resulting in lost revenue. The best way to solve this is to have a source of truth for your codes, that includes the historical billable indicators and ensure your claim system is receiving the most current list of billable codes.
When claims are being processed the health plan can pay the full amount, deny the claim entirely, or reduce the amount paid. Ideally, this adjudication process is automatically determined based on smart applications that seamlessly determine claim resolution without human intervention. It is estimated that 60-70% of provider submitted claims have incomplete or inaccurate data. Identifying those issues as quickly as possible by verifying the codes submitted with the billable information for the service date of the claim can help identify some of the inaccurate data as quickly early as possible in the adjudication process. There are times where a code is pre-authorized, and a claim is submitted but a more specific code is used on the claim. It's important that you recognize these scenarios as this is not inaccurate data submitted by the provider but instead a situation you need to account for when defining your claims processing rules. Another situation similar to this is you may have additional codes submitted for items required by the procedure that was pre-authorized. Making sure you have the reference data to identify the list of codes that should be accepted when you pre-authorize a particular procedure will ensure that you can separate the inaccurate data from the correctly submitted claim data to help ensure you auto-adjudicate the claim and reduce provider abrasion.
Semantic interoperability for claims processing
So, how do we fix it? Ultimately, it comes back to having a strong reference data management solution. Healthcare terminology is the Rosetta Stone of common meaning, so the codes between systems, processes, and stakeholders must be semantically interoperable. Having high quality terminology and common meaning to health care data enables payers to pay claims more accurately and efficiently, lowering administrative costs, facilitating positive collaborations with providers, and ultimately supporting value-based reimbursement models.
Connect with us today to learn more about the Health Language Reference Data Management Solution (RDM) and discover how we can help optimize the claims processing workflow.