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AI’s Impact on Health Insurance

Artificial intelligence (AI) is set to change the health insurance industry, potentially slashing costs and boosting revenues for payers grappling with economic pressures. As insurers face rising medical service utilization and provider costs and tightening Medicare Advantage reimbursements, AI and automation technologies offer a possible solution to improve efficiency and profitability.

Payers could reportedly achieve “net savings of 13 percent to 25 percent in administrative costs and 5 percent to 11 percent in medical costs” by leveraging currently available AI technologies, according to Mckinsey & Co. Furthermore, the report projects a potential “3 percent to 12 percent higher revenue” for insurers who fully embrace these innovations.

AI in Claims and Authorizations

For a growing number of doctors, AI chatbots that draft letters to insurers in seconds are reportedly expediting the fight to approve costly claims, achieving in minutes what years of advocacy have not. This technological shift comes as significant insurance companies face class-action lawsuits for allegedly using their technology to deny large batches of claims swiftly. Experts warn this could lead to an AI-driven “arms race” in the prior authorization process, where bots battle bots over insurance coverage.

The use of AI to deny healthcare claims is also under scrutiny. A class-action lawsuit claims that health insurer Humana used an AI model called nHPredict to wrongfully deny medically necessary care for elderly and disabled patients under Medicare Advantage, a plan managed by private insurers. Another recent lawsuit alleges United Healthcare also utilized nHPredict to reject claims despite knowing that approximately 90% of the denials were erroneous and overrode patient physicians’ determinations of medical necessity.

The AI Opportunity Across Insurance Operations

The recent McKinsey study identifies several key areas ripe for AI-driven transformation. Claims processing, network and contracting, utilization management, care management and information technology all stand out as domains AI could significantly impact.

Marketing and sales emerged as one of the areas with the highest potential for AI-driven improvements. The report suggested that AI could enhance targeted marketing efforts, improve customer acquisition strategies and optimize pricing models.

“To capture full value, payers must reimagine the end-to-end processes of each domain,” the report said, emphasizing that incremental changes will not suffice. This comprehensive approach could lead to significant competitive advantages for industry early adopters. The study noted that these estimates are based on an average-performing payer, suggesting that lower-performing companies could significantly improve by adopting AI technologies.

Despite the promising outlook, the health insurance sector faces hurdles in realizing the full potential of AI. The report noted that payers generally lag behind other industries in AI capabilities, highlighting the need for substantial investments in technology and talent.

To close this gap, insurers must focus on six critical areas identified in the report: developing a business-led digital roadmap, attracting and retaining AI talent, redesigning operating models, upgrading technology infrastructure, improving data quality and accessibility, and successfully adopting and scaling AI solutions.

The report poses challenging questions for insurance industry CEOs, including how they would respond to “a competitor with 20 percent lower administrative costs or one with 10 percent lower medical costs.” It also urges executives to identify the most promising areas for AI implementation within their organizations and to ensure they have access to the necessary talent and technology infrastructure.

Promising Use Cases for AI

Industry experts have identified several promising use cases for AI in health insurance. In claims processing, AI can automate adjudication, reducing processing time and errors while identifying potential fraud. Machine learning algorithms can predict which procedures will likely be approved or denied for utilization management, streamlining the prior authorization process.

In care management, AI can help identify high-risk patients who benefit from early interventions, potentially reducing costly hospitalizations. Customer service can be enhanced through chatbots and natural language processing to handle routine inquiries, improving response times and freeing up human agents for more complex issues. AI models can also analyze vast amounts of data to predict individual and population health risks more accurately, leading to better pricing and product design.

The Road Ahead

The McKinsey report suggests that capturing AI’s total value will require more than technological investments. It will necessitate a fundamental rewiring of payer organizations, involving talent strategies, operating models and organizational culture changes.

AI and automation could provide a critical competitive edge as the health insurance landscape evolves. However, the industry’s ability to overcome implementation challenges and adapt to this new technological paradigm remains to be seen.