August 23, 2023

As the fastest technological adoption in history, ChatGPT hit 100 million users just 2 months after its release.¹ This meteoric rise in the use of ChatGPT has electrified public interest about the current and future use of generative artificial intelligence (AI) and sparked rigorous discourse about its potential and drawbacks. Due to AI’s current influence on health care and its fast-growing potential, employers, employees and health care service providers likely have questions about how advancements in AI may help or hinder the Quintuple Aim.²

This article begins to answer some of these questions by highlighting key ways AI is being deployed in health care, both in clinical settings as well in employer-sponsored programs. The article also includes important considerations about the use of AI, particularly those related to ethics and equity.³

How Is AI Being Used in Clinical Care Today?

With eye-catching headlines like “AI Improves Breast Cancer Detection Rate by 20%,” it may come as no surprise that the use of AI in the health care system is widespread.⁵ According to Grandview Research, the health care market for artificial intelligence is expected to grow globally by 37.5% to reach 143 billion dollars by 2030.⁶

The adoption of AI in clinical settings has shown that it has the potential to help health systems to process vast amounts of medical data-- leading to improved diagnostic accuracy,⁷ personalized treatment plans,⁸ and ultimately better patient satisfaction.^9,10 For example, AI algorithms are being deployed in medical imaging to identify tumors in CT scans; diagnose disease by analyzing patient data to assist with treatment planning, medication management and predict patient outcomes; and power wearable devices so that health care providers can monitor patients' vital signs remotely, detect anomalies and undertake data-informed interventions.^11,12 These examples are in addition to the ways AI is being used to assist health care providers with routine tasks like transcribing patient notes and answering simple medical questions.

A growing body of research is supporting the use of AI in clinical care. A Harvard study found that an AI algorithm was able to instantly identify the type and severity of a specific brain tumor - something that previously took weeks to accomplish.¹³ And a study published in JAMA in 2023 found that chatbots are being met with wide acceptance by patients for general medical questions; when comparing chatbot and physician answers to health questions, patients thought chatbot answers were more empathetic than physician answers, and 79% of patients preferred the chatbot responses overall.¹⁴

How Can AI Support Employer-sponsored Health Care?

Listed below are numerous ways that AI is being used to support employer-sponsored health care.

• Prior authorization and administrative support: AI-powered tools are being used to complete tasks that may enhance the employee and provider experience, including improving the prior authorization process. A McKinsey analysis determined that AI-enabled prior authorization programs had the potential to automate 75% of the process, enabling faster and more accurate decision-making, reducing costs and ultimately, improving the patient experience.¹⁵
• Benefit selection and navigation: Benefit platforms that leverage AI-enabled chatbots can improve employees' understanding of health benefits by addressing their questions and offering personalized guidance and clarifications about available offerings, which can be particularly helpful during open enrollment. These chatbots have been deployed to provide an adaptive, step-by-step tutorial to members walking through the enrollment process.¹⁶
• Health care fraud, waste and abuse reduction: AI solutions are being used by health insurers to combat fraud, waste and abuse, which rose during the pandemic, reaching $300 billion in annual costs.¹⁷ For example, one AI- based business intelligence tool evaluated fee-for-service payments over 2 years in the Iowa Medicaid population and recovered $41.5 million in payments.¹⁸
• Risk identification and early intervention: AI can analyze large datasets from sources like health assessments, wearables and electronic health records to identify and predict potential health issues and trends as a result of certain medical conditions. These conditions, including diabetes, musculoskeletal problems or maternal health complications, may necessitate early intervention.^19,20,21 Additionally, AI is being used to provide personalized recommendations and interventions, such as health coaching and nutrition counseling, so that employees can better manage their health.²²

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“[We must train AI] so that it does not perpetuate and exacerbate existing disparities in health care.”

Sonoo Thadaney Israni, co-author of the National Academy of Medicine’s Special Publication, AI in Healthcare: The Hope, The Hype, The Promise, The Peril, and the executive director of Presence + Program in Bedside Medicine at Stanford University

What Pitfalls Related to the Current and Future AI Landscape Should Employers Keep in Mind?

While AI offers promise for improving the efficiency and quality of health care, its marked growth has occurred quickly and without coordinated oversight and regulation. As AI technologies continue to advance, it becomes paramount to understand potential risks, which include but aren’t limited to those related to:

Is it Possible to Overcome These Pitfalls to Fully Realize the Potential of AI?

As excitement over the potential of AI builds, experts in the field offer a word of caution, pointing to the “two AI winters” – the first AI winter, occurring in the late 1970s, characterized by reduced funding and enthusiasm due to unmet expectations, and the second AI winter, was in the late 1980s resulting from limited progress and skepticism about the viability of artificial intelligence technologies. “These were two chapters in the not-so-distant past where there was a whole bunch of overpromising and underdelivering, which led to the loss of funding, stagnation, and faith in what could be delivered and how and when,” says Israni. Today, there is hope that a deeper understanding of the perils of AI will help us overcome them and avoid another winter.”

Charting a positive path forward will require, among other things, transparency, due diligence and the development of a consistent regulatory framework. These are essential to understand and validate the reasoning behind AI-generated insights, ensure that they integrate appropriately with other technical and legal requirements and importantly, to correct missteps when they occur. For employers, this may involve requiring vendor partners to disclose and explain the ways AI is being used to augment benefits and programs, the practices they have in place to protect confidential patient and program data, approaches to identify and rectify potential biases or missteps, and how they take corrective actions to address any issues or discrepancies that may arise.

The path forward will also require a focus on human-centered design and collaboration, including partnerships between employers and the health and well-being companies they work with. As summarized by Israni, “Collectively, we must conscientiously develop this technology: to humans, for humans and by humans to build an AI-augmented world, where the human experience is complemented by AI technology.”

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“Collectively, we must conscientiously develop this technology: to humans, for humans and by humans to build an AI-augmented world, where the human experience is complemented by AI technology.”

Sonoo Thadaney Israni

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