AI in Claim Denial Management Quiz

Answers and explanations appear as you take the quiz.

1. In the MRI example, what did the prediction model detect before submission?
   • The patient's copay was too high
   • A pattern of CO-197 denials when no authorization number was attached
   • The claim used an outdated code set
   • The MRI was performed out of network
2. How is a claim rejection different from a denial?
   • A rejection means the claim never entered processing; a denial is a decision after processing
   • They are the same thing
   • A rejection is always for medical necessity
   • A denial can never be appealed
3. Why does the work queue send CO-16 denials to registration staff rather than coders?
   • CO-16 means the service was not medically necessary
   • CO-16 means the filing deadline passed
   • CO-16 means information is missing, which often comes from front-end data
   • CO-16 denials cannot be fixed
4. What is the main risk of using a language model to draft appeal letters?
   • It writes letters that are too short
   • It cannot read PDFs
   • Payers refuse all typed appeals
   • It may invent policy language or misquote the chart
5. What do CMS Medicare Advantage rules effective in 2024 say about algorithms in coverage decisions?
   • Decisions must rest on the individual patient's circumstances, not an algorithm alone
   • Algorithms are banned from all claims processing
   • Plans must publish their algorithms' source code
   • Algorithms may deny care without any review
6. Which tools are named in lawsuits over automated payer decisions?
   • Epic MyChart and Cerner PowerChart
   • naviHealth nH Predict and Cigna's PxDx
   • ICD-10-CM and CPT
   • The X12 837 and 835 standards
7. Why does model drift matter for denial prediction?
   • Claims get larger over time
   • Models get slower with age
   • When a payer changes a policy, older data stops reflecting how that payer behaves now
   • The 835 format changes every month
8. According to the guide, what gives the most lasting reduction in denials?
   • Writing appeals faster
   • Sending claims more often
   • Switching clearinghouses each year
   • Fixing upstream causes such as registration, authorization and documentation