ELECTRONIC AUTHORIZATION OF PROCEDURES
The process of approving complex medical procedures IN a health care provider consumed a lot of time and effort for the medical team, in addition to generating unwanted delays for both the company, doctors and patients.
Structured and unstructured data were collected on medical procedures and their various characteristics, and their respective analyTICAL results (approved and unapproved) after passing through the medical board. Supervised learning techniques were used to generate a probability score to automatically authorize requests for procedures requested by health plan users.
+40% of the procedures were automated with 99% of accuracy, generating a reduction in the time for approval of procedures, an increase in satisfaction and a reduction in user complaints.