RPA and Smart Automation Case Studies

Insurance Claim Error and Correction Processing

A National Health Insurance Provider is preparing to receive a large number of insurance claims that need to be adjusted using their internal Facets system. These claims were originally kicked out of Facets because they contained errors that needed to be corrected. However, due to company policy these claims are labeled in a way that denies changes to the claim. To circumvent this, a copy of the original claim is made that will allow corrections to be made, as the edits will be made to the copy, not the original. The original claim and copies are then returned to the Facets database with no changes to its information or status. Prior to automation, a SME was responsible for processing insurance claims submitted via email, making a copy of and correcting the claim, and then resubmitting each one to the appropriate final destination and internal record systems. They also had to determine whether it was an ITS claim or a Local claim, as each kind requires a different revision process. Instead of dedicating FTEs to this manual process, the Health Insurance Provider sought out Accelirate’s help in automating the task in its entirety.

ITS Claims Process

  1. Extract Email Information: The Bot receives the emailed lists of insurance claims that need correction.
  2. Match Claim: Bot matches the extracts claim information from the emails, logs into the internal record system (Facets) and locates the matching claim. The claim is searched for by the claim ID and the Bot is directed to the appropriate claim area based on whether the ID signifies it as a Medical or Hospital Claim.
  3. Copy Claim: The Bot makes a copy of the claim, not to harm the original document, and changes the current Received Date in Facets to the Received Date provided in the email. This date should be the same for every claim being processed. A Note Attachment is then added to the copy of the claim and this note is completed using the attachment description extracted from the email.
  4. Bot Updates Table: Once the attachment is added, the Bot updates and corrects the claim copy. If any errors cannot be corrected the Bot adds them to another queue to be processed by a human SME.

Local Claims Process

  1. Extract Email Information: The Bot extracts information from emails containing Insurance Claims with errors in them.
  2. Locates Claim: The Bot logs into the record system, locates the master Insurance Claim list, and searches for each individual claim that needs correction based on the claims emailed to the Bot.
  3. Corrects Claim: The Bot makes the appropriate corrections to each claim and then attaches a note and an Explanation of Benefits (EOB) code to the claim, so a human claim agent can accurately accept or deny the claim based on the holder’s policy benefits.
  4. Notifies SME: The Bot notifies the SME of the completed claim corrections and notes if any errors were encountered.

This repetitive task was ideal for automation as it was time consuming, manual, and prone to error. With automation, the process for ITS claims correction is now on average four minutes faster per claim and 2.5 minutes faster per local claim.

Results

ITS Claims
1,600+ Monthly Man Hour Savings
1 Minute Automated Claim Processing Time

Local Claims
1,300+ Monthly Man Hour Savings
2.5 Minutes Automated Claim Processing Time