Prior authorization reviews require clinicians to interpret medical records and insurer criteria, an intensive, error‑prone process. While AI can help, healthcare demands accuracy, consistency, and privacy, making unconstrained generative models risky. This session introduces SAS Document Analysis for Health Records, a hybrid AI approach that blends NLP, machine learning, and rule‑based NER to produce repeatable, clinically relevant outputs. See how results are transformed into semantic triples for use in knowledge graphs to enable structured comparison against medical‑necessity rules. This framework improves efficiency while preserving transparency and trust—key requirements for responsible automation in prior authorization.
Presenter: Greg Massey, SAS
Watch the recording
