Automated claims adjudication shall provide optional process steps for the automated processing of larger claim volumes once the claim has been submitted to the payer organization. Three levels of verification should be available at the payers side:
Artificial Intelligence level: Automated verification of claims through a decision support model that was generated with machine learning algorithms.
Manual level: Manual review of claims by reviewers at the payers side.
Sample configuration of an automated claims adjudication process
The payer organisation shall have the choice of how to implement the claims adjucation process using Configurable Workflows. A possible implementation of an AI supported claims adjudication process could be as follows:
when the claim is verified, it is submitted to the payer.
At the payers side, the rule based engine reviews all claims (which could have been submitted by an external system without prior verification) according to the rules from the Configurable Claims Review Engine.
invalid claims are flagged for manual review
valid claims go to the AI level.
The AI level verifies all claims that passed the previous rule based step according to a previously trained decision support model.
suspicious claims are flagged for manual review.
a certain percentage of unsuspicious claims is retained for manual QA processes to estimate the validity of the AI model.
all other unsuspicious claims are being released for immediate payment.
Human reviewers review flagged and QA claims from step 2 and 3.
either the flagged claim is cleared immediatly and released for payment
or the flagged claims are sent back to the health service provider in a claims dispute process
or the claim is rejected directly
The above example is on possible configuration that assumes a reduction of costs for the insurance company by directly paying unsuspicious claims. Of course this estimation is only valid, when the loss through falsly released payments is far less than the loss through high costs of human reviewers. To control this effect, a continuous QA process from 3.b. is needed.
Technical requirements for the AI component
The AI component shall ideally be part of the official openIMIS distribution, but should be designed in way that it can operate independently though data exchange via the FHIR APIs of openIMIS.