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The Use of Machine Learning & Artificial Intelligence to Address the Prior Authorization Bottleneck
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The Use of Machine Learning & Artificial Intelligence to Address the Prior Authorization Bottleneck

When: Tuesday, November 12, 2019
1:00 PM
Where: United States
Contact: AAOE

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As the U.S. healthcare industry approaches 20% of the Gross Domestic Product, payers are seeking various ways to control the cost of patient services by tightening test and procedure order requirements for medical necessity addressing patient care. This process is part of the payer’s utilization management protocol and requires hospitals and physicians to seek approval before ordering certain types of tests or procedures. Hospitals and physicians refer to this process as prior authorization. The process seems appropriate until you are a patient caught in the prior authorization bottleneck or the orthopedic physician that is seeking approval for a patient’s treatment. 


From a financial standpoint, the prior authorization process is negatively impactful. According to a 2017 American Medical Association (AMA) Prior Authorization Physician Survey, physicians and practice staff spend 14.6 hours securing 29.1 prior authorizations, per physician each week. The negative impact continues downstream causing patient dissatisfaction due to wait times, at a time when healthcare is moving into more of a consumerism type model.  In December of 2017, the AMA identified:


·         92 percent of the patients requiring pre-approval experience a delay in treatment

·         84 percent of physicians reported high or extremely high UM/PA burden, with 86 percent of physicians reporting this burden has increased over the past five years

·         30 percent of physicians reported waiting at least three business days to receive UM/PA decision from health plans


Prior authorization has become an administrative burden for orthopedic practices and has had a negative impact on patient experience. By leveraging advanced technologies that utilize machine learning and artificial intelligence (AI) for prior authorization, the burdensome administrative workflow is streamlined, allowing you to collect more revenue,while increasing patient satisfaction.


Learning Objectives:

·         How automation and AI is impacting prior authorization in the orthopedic industry

·         How AI is made actionable in a prior authorization solution

·         How AI impacts patient satisfaction through faster prior authorization turnaround times

·         How machine learning and AI work together to determine if a prior authorization is required








About the Speaker

Navaneeth Nairis the VP of Product at Infinx Healthcare and has been in healthcare technology for more than 16 years, focused on patient experience and access with some of the largest healthcare payers in the industry. Navaneeth has spent the last 7 years focused on the application of AI to engage patients and amplify business process improvements.






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