Healthcare is experiencing an AI revolution amidst rising costs, labor shortages, and declining margins. Recent analyses show a significant increase in insurance claims denials, with initial denials jumping 11.9% year-over-year and Medicare Advantage denials rising 56% between January 2022 and June 2023. For hospitals still recovering from Covid-19’s financial impact, managing denied claims is crucial.
AI has enormous potential to revolutionize denials management. It can streamline claims processing, enhance coding accuracy, and extract essential information from medical records and payer contracts to address denial root causes. AI applications in revenue cycle management include selection models for prioritization, workflow acceleration, improved price accuracy, and predictive trend analysis.
Implementing AI for denials management requires consideration of technical, data, talent, and operational factors. Creating effective AI models demands high-quality data, specialized data scientists, robust platforms, and understanding of evolving standards and regulations. Collaboration with established RCM innovators can expedite a healthcare system’s path to stronger financial health.
Large Language Models (LLMs) offer great potential but come with uncertainties. Major tech companies are developing healthcare-specific LLM platforms to mitigate risks. Healthcare organizations should start small, using AI to address their most challenging issues. Interoperability is crucial, requiring a robust data infrastructure to integrate AI models into operational workflows.
As the healthcare industry faces various challenges, embracing AI can empower revenue cycle professionals to envision a future with reduced denials, optimized revenue, and improved financial health. The urgency is clear, as delays can result in potential revenue loss. AI is becoming an indispensable asset in strengthening the financial revenue cycle structure for healthcare providers, especially as payers increasingly use AI to process claims.
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