Manual Claims Processing is A Major Concern for Payers

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The cost of manual claims processing operations is top of mind for healthcare payer organizations. A survey from HealthEdge found that health insurance  executives cited “High rates of manual processing/need to reduce administrative costs” as a top concern when asked to rank significant obstacles facing their organization. 30% of executives ranked it as their highest concern, and nearly two thirds ranked it as a one of their top two priorities.  

That manual claims processing is a concern is no surprise. The HealthEdge survey also found that the manual adjudication cost for 65% of payers is more than $6 per claim.  So the real question is what can payers do to address these high costs?   

Most of the obvious changes have already been made.  Payers are working on improving auto-adjudication rates, but for those already above 80%, there are few gains left.  Payers are also looking at shifting claims paying to remote workers as a strategy to lower direct compensation costs as well as overhead.

One critical area to reduce costs comes from employee performance optimization.  Many payers lack visibility into the work their claims processors are doing.  Enkata research has found that this lack of visibility can be costly.  Not only is there substantial lost productivity from a variety of causes, but accuracy is also a persistent problem.  Only with visibility into how claims processors are working can employers help them to improve.  

These improvements can quite valuable. Even in just addressing some of the basic causes of lost productivity, employers can achieve output gains of gains of 10% or more.  More importantly, employers can address the causes of errors and overpayments that increase costs substantially.  

Healthcare claims payers are right to be concerned about the cost of manual claims adjudication. It can be an expensive, inefficient process operating substantially below its potential. However, there are concrete steps they can take to reduce costs and errors, and achieve a 10% to 20% gain on productivity.