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 AI-RCM ERRORS
WHAT AI CAN GET WRONG

Patient Access/Registration 

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Demographics, coverage, guarantor, plan selection, eligibility interpretation ​​​​​​​

Eligibility/Benefits 
Verification

Incorrect benefit interpretation, deductibles, coverage status, authorization requirements

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Prior Authorization Systems

Incorrect procedure criteria, payer rules, medical-necessity determinations and authorization status​​

Clinical Documentation Integrity (CDI)

Unsupported diagnoses, missed diagnoses, incorrect clinical indicators, or severity assumptions

Computer Assisted Coding (CAC)

Incorrect ICD-10-CM, ICD-10-PCS, CPT, HCPCS, modifiers and E/M levels

Charge Capture Systems ​

Missing charges, duplicate charges, incorrect units or services

 Charge Description Master/   (CDM) Logic

Incorrect Code-to-Charge mapping, pricing, or procedure association ​​

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Denial Prediction Systems

Incorrect probability, reason, or prioritization 

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 Denial Management Systems

Misclassification of denial cause or recommended corrective action

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