Innovative practices that add the missing rev cycle KPI of Encounters per Hour to their practice dashboard recognize that a critical part of radically improving coder productivity is a mindset shift for their team. Improved productivity and throughput are in addition to, not in place of coding accuracy. Historically, coders focused all of their attention on accuracy and productivity suffered as a result. Most coders were trained that the only way to ensure coding accuracy was to review every single encounter personally. This training and execution methodology is outdated, and practices that continue to use this workflow are overpaying for their revenue cycle outcomes.

What would happen if you could leverage your team’s coding expertise only where it provides the most value? Instead of spending time reviewing the 48% of encounters that the average physician codes perfectly, they only intervened on encounters that require their expertise. What if I told you that top-performing practices could further leverage coder productivity through automating practice specific routine coding corrections?

Coding is complicated and very important. The coding process is part art and part science, this is one of the main reasons why most practices are very accurate in their coding, but significantly less productive than top-performing practices. The top-performing practices we work with automated at least 15% of the coding changes needed to correct or modify encounters created by their clinical team. Rather than investing coder time to review every encounter, their coders are investing time in search automation opportunities. Which coding changes can be automated changes from practice to practice, but the process is the same.

Coding automation significantly improves coder productivity and is a big reason these practices are more than 7.5 times more productive than their peers.