Our work around Claims processing started in 2002 with one of the “Blues”. Improving the workflow, automating as much as possible in order to de-risk frauds, increase the number of processed claims, and optimise the claim handler’s time. One of our favourite projects was Medical Charts Review with a goal to improve quality management and oversight.
Claims Review
- calculate claim risk score
- Duplicate claim detection
- related claims matching
- physician notes processing
- auto assign logic
- Discrepancy check
Challenge
Natural Language Processing (NLP) and other machine learning technologies are rapidly becoming a major ingredient in modern healthcare IT systems. Payers, providers, and pharmaceutical companies are all seeing applicability in their areas and are taking advantage of ML today.
However, bringing the ML system into the production is often a challenge for many organizations.
Development of such systems can be time consuming, expensive and very often with hard to predict outcomes.
Finding a way to quickly and cost efficiently develop, test, evaluate and deploy ML solutions is a goal for many organizations that realize the potentials and benefits of these technologies.
OPPORTUNITY
By leveraging various publicly available and production ready API’s, we were able to create a proof of concept of an NLP solution in less than a week. Our PoC was an NLP application for extracting and categorizing medical and PHI information from physician notes.
By using the Box Cloud Content Management platform with its Skills module and configurable and user friendly Workflows, we were able to quickly utilize Amazon Comprehend Medical solution and custom business logic module.
VICERT SOLUTION
Claim records selected for review are exported in a suitable file format and uploaded to the Box CCM. Box Skill processes the claim and orders the medical chart and physician note for that claims form the vendor.
When physician note is uploaded to the Box CCM by the vendor, it is processed by Box Skill and Amazon Comprehend Medical to extract all relevant medical information. This information is stored in file’s metadata and compared with the claim’s data.
In case of comparison discrepancies, a task is created in Box Workflow and assigned to the user for manual review and resolution.
High Level Architecture
Provider
A provider of a service who sent the claim for processing.
Vendor
A vendor responsible for providing the medical charts and physician notes for claim review.
RA/RI Database
Internal database used to store the claim, member and provider information.
Provider Claim Review App
The application that enables a user to review the selected set of claims and compare the claim data with notes data.
Once the physician note is uploaded to the Box CCM platform by the chart vendor, it is processed by another Box Skill which invokes Amazon Comprehend Medical service in order to extract the structured information of diagnoses, symptoms, signs, medications, treatments and procedures that apply to a given patient record.
The solution presented above is an NLP application for extracting and categorizing medical and PHI information from physician notes. Learn more about this solution by diving deeper into the Claims Review technical overview document:
