Implementing ML in healthcare claims processing workflows
Health insurance companies make money by collecting premiums from their subscribers. Hence, the more subscribers they have, the better it is for their business. However, the larger the subscriber base, the greater the number of claims to process. Not to mention the complexities as a result of managing large health plans and choices. These introduce bottlenecks in claim processing. The good news is that most of the steps in claims processing, as highlighted in the previous section, are repetitive and manual. This provides us with the opportunity to automate some of these tasks using ML. Now, let us look at a few examples of the application of ML in claims processing:
- Extracting information from claims: There is still a large volume of claims that get submitted as paper claims. These claims require humans to parse information from the claim forms and manually enter the details of the claims in a digital claim transaction...
