In US more than 184 million Prior Authorizations are processed yearly between Providers and Payers. IBM Consulting offers a solution to streamline and automate that using Azure OpenAI.
Prior Authorization involves multiple stakeholders and requires both simple and complex processing to achieve end-to-end automation potential.
“Complex Processing” utilizing structured data pertaining to Provider, Patient, Procedure, etc AND unstructured EMR / clinical attachment data to digitize, understand, and rationalize clinical information to render decisions (i.e., Criteria-Level and Case-Level Decisioning). Data extracted can also enhance simple processing capability and drive improvement in 360 degree understanding of the patient.
For complex medical procedures which require Prior Authorization, payers have established clearly outlined "Medical Necessity" documents and criteria.
When providers submit patient medical records, finding specific information related to each medical necessity criteria is difficult and time consuming.
IBM Consulting's Prior Authorization solution provides the automation using Azure OpenAI for
Speed to Value: Improve time to process prior authorization requests; reduce administrative burden
Improve Clinician Experience: Decrease Clinician Burden (Provider & Payer) by reducing "think time" by utilizing job aid to support decisioning
Enable MDs/Nurses to operate at Top of their License: Focus on the complex criterion and cases requiring their expertise
Assist in Approval / Denial Communication: Apply Generative AI to create an initial approval and/or denial letter for review
Explainability: Provide reasoning and reference to the Clinical documentation. Deliver evidence-based traceability to build trust
Conversational Engagement: Quickly find and display answers in natural language for each determination criteria
Foundation Model Benefits
Model Training Acceleration: Improve time to train AI compared to “traditional” NLP (Clinical) models
Criterion Extraction Acceleration: Automate extraction of criterion from policy documents
Computational Efficiency: Ability to support process sequencing in parallel