use cases

Predict Prior Authorization

Prior Authorization (PA) delays access to necessary care, Healthcare organizations an leverage AI to streamline PA.


30% of physicians surveyed by the American Medical Association reported that prior authorization (PA) has led to a serious adverse event for a patient in their care (1). 94% state it delays access to necessary care, and an overwhelming majority perceive the process to have a negative impact on patient health outcomes. PA requests are also extremely time-consuming; physicians and their staff report spending an average of two business days each week completing requests (1).

Payers contend that PA is extremely beneficial despite provider complaints. In a recent survey conducted by America’s Health Insurance Plans, 98% of plans surveyed reported that PA improves the quality of care and provides support for evidence-based treatment (2). 91% also reported using PA to ensure patient safety, and 79% report that it lowers healthcare spending. However, payers also grapple with the associated administrative burdens.

Size of the Problem

  • 21% of physicians report that PA delays have led to an avoidable hospitalization (1).
  • 12% of 182 million prior authorizations were fully electronic in 2018 (3).
  • Roughly 50% of requests in 2018 were conducted entirely via faxes and phone calls (3).
  • $25 billion in costs has been attributed to administrative PA processes (3).

Why it matters

PA was designed to act as a patient-safety and cost-saving measure for payers to ensure appropriate provider utilization management, but the massive administrative burden is taxing for both parties. Administrative PA processes have been estimated to contribute as much as $25 billion annually to total healthcare costs and can significantly delay care for patients (3).

The PA request process is complex, laborious, and not standardized. Payer requirements are varied, change frequently, and may even differ across health plans offered by the same payer. Because clinical workflows and billing systems are rarely integrated, providers must manually retrieve pertinent information from a variety of data sources and transfer it into authorization requests. This process is prone to human error, lacks coding consistency, requires clinical staff to manually review individual plan specifications, and frequently takes place over multiple phone calls and faxes that strip away the structure of a patient’s medical record.


Fortunately, Healthcare organizations (HCOs) can leverage AI to streamline PA. With predictive analytics, providers can easily determine if PA is required and quickly surface the necessary information. Payers can exploit AI-based models to identify and automatically approve requests that are highly likely to be approved—substantially decreasing the need for manual reviews. Ultimately, HCOs can leverage AI to dramatically reduce administrative burden, curb costs, and accelerate patient access to approved treatment options.


  • Electronic Health Records: EHR data with comprehensive patient histories of vital signs and symptoms, problem lists and chief complaints, tests results, diagnoses and procedures, and prescriptions.
  • e-Prescribing Data: Data from electronic prescriptions detailing key information about medications, dosage, patient instructions for frequency and timing, and available refills.
  • Medical Claims: Data extracted from health insurance medical claims with details about dates and place of service, diagnosis codes, key procedures, use of medical equipment, and provider specialties.


  1. "2020 AMA prior authorization (PA) physician survey.” American Medical Association. Accessed 6 May 2021.
  2. “Key Results of Industry Survey on Prior Authorization.” America's Health Insurance Plans. Accessed 6 May 2021.
  3. “Moving Forward: Building Momentum for End-to-End Automation of the Prior Authorization Process.” CAQH Core. Accessed 6 May 2021.

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