As technological advancements reshape the health care landscape, industry stakeholders continuously adapt to an influx of new, cutting-edge tools and solutions. With these advancements having the potential to dramatically enhance organizational productivity, streamline efficiency, and significantly improve patient outcomes in unprecedented ways, a lot is riding on selecting accurate and responsible technology.

Most recently, health organizations and their stakeholders have rapidly turned to AI and machine learning to expedite high-quality care delivery and optimize administrative workflows. Leveraging predictive AI with accurate and comprehensive data entry capabilities greatly enhances overall health care efficiency. However, as health care providers and health plans increasingly adopt AI, a new concern emerges around the potential overreliance on AI for critical decision-making, especially regarding its use in optimizing antiquated prior authorization (PA) approval processes.

A recent investigation involving the use of AI-based technology to review prior authorization requests found that hundreds of thousands of pre-approved claims that were denied within a two-month period received, on average, just 1.2 seconds of physician review per request.

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