Unlocking healthcare productivity with AI is now a necessity

The rapid evolution of technologies such as robotic process automation (RPA), cloud, blockchain, and artificial intelligence (AI) in the 21st century has upended healthcare functions. Significant regulatory changes, including the Affordable Care Act, Cures Act, and price transparency rules, helped expand healthcare access to consumers while slowing the rate of cost increases. Yet, there is more to be done to meaningfully impact the triple aim of care (reducing costs, enhancing experiences, and improving health outcomes); life expectancy has declined in the US while the prevalence of chronic conditions increased after the pandemic exacerbated prevailing conditions.

Many service providers have been on a journey to leverage technologies to address the triple aim of care in some form or shape. The advent and evolution of AI have spurred connecting the possibilities with the reality of impacting health outcomes.

Balancing the opportunities and risks across the AI continuum in healthcare

There is reason to be optimistic about the possibilities of AI in healthcare for improving productivity, based on ample evidence from operations regarding improved claims management to an increase in personalized medicine (34% of FDA new drug approvals in 2022). As AI becomes ubiquitous, the possibilities for preventing disease, improving diagnosis accuracy, and identifying care pathways with the highest efficacy will only improve. As research to enhance AI to perform at the human level takes shape, it is important to realize that in healthcare, it is likely and perhaps required to always have a human in the loop to ensure empathy and humanity in care delivery.

I believe that AI is an empowerment mechanism. Self-insured plans and TPAs want to compete and win. They want to innovate to provide customized solutions, wherein they can drive member experience.
They need the lowest cost structure with the highest quality and the best experience.
They’re looking for technology solutions like our proprietary low-cost AI platform that can be implemented very quickly to scale up and differentiate in the marketplace.
GenAI healthcare solutions are no longer a hype, they are a reality.

– Shashi Yadiki, CEO, Smart Data Solutions

Enterprises and suppliers must recognize that they must balance the optimism and possibilities of AI with data privacy, security, and the use of ethical algorithms. The increase in global bad actors and the less-than-stellar security track record (541 breaches impacting more than 100 million health records in 2023) of health plans and providers will necessitate greater vigilance by enterprises and service providers. AI also must ensure that it does not perpetuate individuals’ and communities’ biases that could dampen access to healthcare and worsen the efforts to improve the triple aim of care.

Exhibit 1: Leaders will be discerning in their deployment of AI to realize maximum benefits

Source: HFS Research, 2024

A further challenge service providers must continue to address is the force of entrenchment that seeks to maintain the status quo. That status quo is reflected in a lack of imagination in applying sophisticated technologies to yesterday’s challenges instead of leveraging AI and generative AI (GenAI) as catalysts to reframe the challenges. Healthcare enterprises must partner with service providers to explore the right challenges to deploy the continuum of AI, including machine learning, natural, language processing, and GenAI, that could positively impact the triple aim of care (see Exhibit 1).

Self-insured employers are driving the disruption of legacy processes and exploring real partners

Increasing self-insured employer enrollment (see Exhibit 2) will be a critical disruptor of legacy healthcare processes. Over the last decade, employers have become the default health insurer for their employees by underwriting their medical risk. In 2023, that was reflected in the approximately 84 million lives covered. This shift by self-insured employers has been driven by the acute need to reduce the cost of care, explore new health and care delivery paradigms to improve health outcomes, and differentiate themselves as employers of choice.

Exhibit 2: Self-insured employers are driving innovation in new health and care delivery paradigms

Data: CMS, US Dept of Labor, CBO, Kaiser Family Foundation
Source: HFS Research, 2024

While the self-insured employers segment is the largest, these employers don’t buy collectively. Instead, they buy individually, and their buying profile is reflected in five archetypes of employers. The archetypes are driven by employer culture, employee demographics, size, service, and more, and each has a different appetite for experimentation and approach to adopting non-traditional pathways.

There is a recognition that there are about five different generations in the workforce today, and each generation has a different set of needs that current paradigms do not support. AI could personalize care across these generations, allowing the members to define how they want to receive care, not to be dictated by the payers or providers. Plus, CFOs recognize that a sick employee equals cost and healthy employees equals revenues, so new models are a financial imperative.

The market to address self-insured employers is extremely competitive, with health plans bringing their core healthcare strengths, TPAs (third-party administrators) bringing robust provider networks and efficient operations, and private equity players increasingly exploring the same with AI-enabled platforms. As employers expand their awareness and grow bolder to adopt new models, TPAs and service providers with the right AI investments and genuine partnership models will likely be the big winners in the space.

There is still room to address non-medical costs

The maturity of AI and the buzz surrounding GenAI have reenergized opportunities for addressing administrative costs. Research and reality show an approximately 30% improvement in productivity by deploying AI. Many of these improvements are driven by leveraging platforms to reduce paper in mail rooms, incorporate interoperability, and streamline back-office processes.

The opportunity to revisit the value chain remains strong as new regulations that impact price transparency and prior authorizations need attention. There is an argument that prior authorizations must be the exception reserved for high-cost or rare disease therapy, not the norm for routine care, such as eye drops or Metformin. Nearly all—95%—of all prior authorizations are approved, consuming time and money that can utilized elsewhere.

Reimaging the healthcare value chain to address contemporary and future challenges in the context of a wide variety of enabling technologies will help reduce non-medical costs.

The Bottom Line: The AI continuum is a generational opportunity to positively, sustainably, and meaningfully impact the triple aim of care.

While technology is not the only solution to all that ails healthcare, it is certainly a therapy that can cure many of the issues that impact the triple of care. An ecosystem approach that can combine reengineering the healthcare value chain with the continuum of AI as the enabler will address the health and care needs of diverse demographics.