Quiz połączony z przewodnikiem · Średni Poziom

Sztuczna inteligencja w quizie dotyczącym zarządzania odmową roszczeń

Testuje routing odmów w oparciu o CARC, różnicę między odrzuceniami a odmowami oraz limity CMS dotyczące algorytmów płatnika w decyzjach dotyczących zasięgu Medicare Advantage.

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Pytanie 1 z 8

In the MRI example, what did the prediction model detect before submission?

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Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.

  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    • The claim used an outdated code set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
    • Są tym samym
    • 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
    • Nie czyta plików PDF
    • 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