An employer guide to AI and health insurance
It will come as no surprise that Artificial Intelligence is disrupting and transforming the health insurance industry. The massive volumes of transactions and data associated with health insurance are prime targets for an AI strategy. Core administrative tasks are being completed more efficiently, and science fiction-type ambitions have become reality. At the same time, AI is also transforming how care is delivered. For employers that sponsor health insurance plans — which necessitates spending a lot of money and taking on fiduciary accountability — AI-driven transformation presents important risks and opportunities.
In this post, we’ll discuss what employers should know about the changes taking place in health insurance administration right now – and what may lie ahead in the not-too-distant future.
Core plan administration. It’s reasonable to question whether a carrier should reduce fees as manual processes disappear. Automation of plan administration has been progressing for years as carriers upgrade systems and boost auto-adjudication rates to minimize manual efforts and reduce the risk of human error. Employers should certainly review their administrative fees at renewal, especially in today’s aggressive pricing environment. However, basic administrative activities and fees are not the whole story, by a long shot. The vast majority of medical plan expenses — about 90% — are attributable to medical and pharmacy claims. Clearly, managing that side of the equation offers a lot more in potential savings.
Claim audits. To satisfy fiduciary responsibilities, self-funded plan sponsors often engage a third party to periodically conduct an independent claim payment audit. As insurers transform the lifecycle of a claim, it is especially important to establish an audit cadence now. For decades, the contours of audits remained consistent – roughly 200 claims would be randomly selected using statistical sampling and then an expert would carefully review each of those claims manually to assess whether all the plan provisions and policies were accurately applied. This type of audit offers significant value but is labor-intensive — and the vast majority of claims go untouched. AI is the “next generation” in audits. Now we can first electronically scan every claim to identify material trends or anomalies and then direct review efforts toward a select group of prioritized claims, resulting in much better outcomes. As a caution, audit rights cannot be taken for granted and are part of an administrative agreement. There are a range of positions within the industry on the permissibility of this “next generation” approach to audits.
Fraud, waste and abuse. Emerging technology can continuously monitor claims and transactions, flagging potential issues in near real-time at both micro and macro levels. At a micro level, new technology flags specific claims that are suspect. At a macro level, it allows leading carriers and third parties to question certain providers where their care patterns and frequency of certain procedures are out of line with normative proportions. One of the hidden drivers of trend has been efforts by certain entities to “up code” and charge more for the same care. AI-driven audits and analytics are a promising avenue for identifying this type of change in billing tendencies. Leading carriers are making large investments in these capabilities — while third parties are offering to provide oversight on top of existing carrier capabilities. Employers need a thoughtful strategy to maximize new opportunities in this area, including a full understanding of the capabilities and fees of carrier or third-party solutions — and a careful assessment of the compatibility of a potential third-party solution with your carrier.
Advanced data analytics. Continual annual health benefit cost increases that are higher than inflation or revenue growth are a taxing — and stubborn — problem for most employers. Sophisticated new data analytics are now being used to identify impactful, customized strategies to mitigate a group’s cost drivers, and we believe that incorporating AI's ability to analyze vast amounts of data will be a game-changer. For example, there has been real progress in machine-learning models that can identify high-risk members to tailor wellness programs more effectively, and these capabilities will only get better. For plan sponsors, this can mean more personalized benefit strategies, better risk management and lower trends.
Provider evaluation. The related strategies of non-traditional medical health plans, tiered networks and provider steerage constitute the most significant change in benefit strategy we are witnessing today. These approaches all depend on the ability to identify the highest quality and most efficient providers, and AI-enhanced analytics are increasingly being put to this use. As part of your assessment of any solution that steers members to selected providers, it is important to understand the underlying data sources, the conceptual approach of the algorithms and how quality considerations are being balanced with cost.
Education. The US healthcare system and the world of insurance are both exceptionally complex and constantly changing. Although, at least once a year, employers attempt to explain the insurance options they offer to their employees, few would say that their employees truly understand their health benefits, let alone how much these benefits cost the company. That’s why there is so much enthusiasm for leveraging AI as the ultimate benefits coach. Our own imaginations may be the biggest limitation in finding ways to use new technology to engage employees. If you haven’t done so yet, consider seeking out a talented communications expert to learn how others are modernizing their approach to employee education.
Parting thoughts
Of course, the risks associated with the use of this powerful technology must be considered and addressed as well. Legislators, regulators and courts are increasingly vigilant about the societal risks that AI presents. This article describes a range of legal concerns and suggests actions to take. Recently, the role of AI in prior authorization has drawn attention; this post provides context and an update on efforts to initiate operational efficiencies that improve member satisfaction and understanding of the process.
AI is no longer a futuristic concept; it is actively transforming the health insurance industry today. Plan sponsors should seek insurers and other partners who are leveraging AI to drive innovation. Embracing these changes not only enhances operational efficiency but also positions organizations to deliver more value-driven, personalized health benefits.
