RPA and Smart Automation Case Studies

Medical Billing Claims FPM

A national auto insurance company processes thousands of CMS 1500 forms each month for medical claims billing. This process is extremely manual and takes hours of the billing department’s workday, causing the company to incur high expenses for data entry. The primary purpose of automating this function is to process claim forms more accurately and cost effectively, thus minimizing the risk of inaccurate reimbursements and providing greater control over the entire claims processing workflow. To automate this process, ABBYY’s advanced data capture OCR technology was used in conjunction with RPA automatic validation rules to ensure the client’s healthcare claims management department receives and records accurate data

  • Bot Gets File: The Bot scans emails for files and locates the first available bill. Due to high volume, this process involves several bots running at one time; after finding an available bill, the Bot locks it to ensure all bills are processed and none of them are duplicated. After the bill is locked, the bot downloads the file and decrypts it
  • Bot Identifies Bill: The Bot scans the file and classifies whether or not it is a CMS1500 medical claim form. If the form is in fact a CMS1500, the Bot sends it to ABBYY, an OCR engine, for further processing.
  • Bot Uses OCR: Optical Character Recognition engine ABBYY was used to label, read, and extract data from the completed forms. All fields of information from the document are scanned and the relevant data from the document’s 60+ labeled fields, including names, addresses, medical codes and insurance information are extracted and compiled in a standardized method.
  • Bot Creates Blocks to Export: Each field of relevant information gathered by the bot is matched to a prelabeled block for exporting. Because fields are position-based and keyword-matched, the blocks are used to tell the bot which pieces gathered via OCR from the different CMS document fields is the scanned result for each output. For example, the OCR engine found that the third field on the document is Home Address, and the keyword “Home” is matched on the form to the block’s label, so the text in that field is extracted and put into the appropriate block to be sent back to the RPA Bot.
  • Bot Returns Data: All of the data extracted via ABBYY from each completed form is returned to the RPA bot for postprocessing to ensure data accuracy. Once confirmed, the data is uploaded into the claims processing system for further coding, scheduling, and credentialing.
  • Data is Saved: Both the medical claim request and response are encrypted and saved in the client’s internal system. Once the data is returned, it is encrypted again with an internal vault process and the service response is saved. Each step of the process is encrypted and logged into the database.

Using RPA and OCR to automate this process, the client was able to reduce their medical claims processing time down to 30 seconds per patient as opposed to the hours it took their team to handle the high volume of claims. With the automation of a process involving sensitive medical data, the Accelirate team was able to ensure the security of each customers data by encrypting files and logging information into the client’s database after every step in the automation. Accelirate is well versed in information security in regard to automation and ensures data safety by embedding checkpoints and various security precautions throughout the entire automation journey.

OCR Trained with 20+ Historical Data Documents
Reduced Claims Processing Time to 30 Seconds Per Patient