Medical claims automation

Case study

Medical claims automation

Our client is one of the best rated pet insurance providers in the USA. They provide insurance plans for dogs and cats and cover illnesses, accidents, cancer care, clinical procedures, hospitalization, and much more.

Requirements

Our client was manually processing a large number of claims for reimbursement on a monthly basis. These claims contain digital copies of medical invoices, received from various hospitals and online stores in different sizes and formats.

The capture and verification of data had to be automated to reduce operational costs, increase operational efficiencies, and lower claims Average Handling Time (AHT).

Challenges

  • The medical invoices were varied in terms of number of pages and formats.
  • The scanned copies of the medical invoices were not of high quality; that is either blurred, distorted, folded, or of low resolution.
  • Unable to automatically associate email or fax claims to policy accounts.
  • Pet and parent names in the claims/medical invoices do not match with the names in the policy account.
  • Lack of predefined formats for invoices or claim forms across hospitals.

Solution

Imaginea came up with a solution to implement an RPA bot, coupled with an OCR (Optical Character Recognition) tool. This enabled the complete automation of the data capture and validation process.

Tech stack

How our solution helped

Accuracy in data
extraction

Reduction in claims
processing time

Reduction in claims
cycle turnaround time

Overall approach

We built the master data set by using the DBSCAN clustering algorithm to scan 8000 invoice samples and categorize them into 170 unique clusters. Further, we established the document layout definitions based on these clusters. The definitions made data extraction, through OCR, much easier.

The diagram below illustrates how the invoice data is extracted and processed through our solution:

Results

  • Reduced claims processing time from 2-3 to same day processing
  • Substantial decrease in data entry time of invoice information
  • Increased process efficiencies
  • Improved outcome quality
  • Reduced transaction time and costs

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