There's a lot of talk about automating credit balance resolution, here's our two cents as a team of credit balance experts.
Automation is a hot topic in revenue cycle management and for good reason, it can dramatically improve efficiency and accuracy as well as reduce cost when used effectively. So how about credit balances? Shouldn’t healthcare providers just automate the identification and resolution of credits? Sadly, automation is not yet mature enough for this to work and likely won’t be for a very, very long time. Let me explain…
The thesis behind automating credit balance resolution seems sound; use all the data available within your EHR to identify debits and credits, match credit balances against debit balances, then either automatically transfer the balance or issue a refund. In theory this sounds simple, but in practice it exposes healthcare providers to substantial risks.
Robust analytics and automation can be helpful, but credit balance resolution still largely requires an (expert) human touch. Automation cannot yet solve COB issues requiring research, retro-termed plans, posting errors, outdated contracts, patient discounts, birthday rules, state laws, and countless other factors that complicate each individual credit balance account.
If not validated, automation like mass-adjustments can actually create more issues that require humans to go back, review and make corrections. Not to mention that by automating “quick fixes”, you are ignoring the root causes of credits, treating symptoms instead of finding a cure. Automation is a valuable tool which must be used surgically. Over-utilization or reliance on automation is a recipe for disaster and collateral damage.
In summary, automation can help improve credit balance resolution, but it should not be used as a substitute for human oversight. Healthcare providers should still review and verify credit balance reports to ensure accuracy and compliance with regulatory requirements.
As specialized experts in credit balance resolution, we have yet to see a comprehensive approach that does not include surgically applied automation paired with highly skilled analysts working with purpose-built technology to enable their productivity and effectiveness.