Like many others, I’ve noticed that AI is becoming increasingly prominent in our lives, largely due to significant investments from major companies like Microsoft, Google, Meta, and Amazon. While my grammar may not be perfect and my thoughts are not always sequential, I often find AI to be a challenge, attempting to reshape my intentions or enhance my capabilities. Yet, it also transforms me. This doesn’t diminish my excitement for AI’s potential impact on healthcare—particularly in “empowering consumers, enabling providers, and advancing the science”™. This phrase is so integral to our mission that we trademarked it, and it continues to drive our vision for health and wellness.
Recently, Axios reported that AI could add $19.9 trillion to the global economy by 2030, driven in part by its effects on consumer spending and the infrastructure required for AI systems. The future is indeed promising, especially for healthcare, though not necessarily in the ways people expect.
In the past week, I’ve heard from two acquaintances who lost their jobs due to AI’s growing role in healthcare. While I can’t verify these claims, they seem plausible. In one instance, a Case Manager Nurse may have been downsized as healthcare companies, and large providers, are experimenting with AI to manage case loads more effectively. While I question whether this will work as intended, it could enable fewer Case Managers to handle more patients with AI guidance.
Reflecting on my father, I remember seeing him using a manual IBM Selectric III typewriter – he was very fast! He had that typewriter till the day he died. He never got into utilizing the capabilities of a computer. I see a parallel: AI in healthcare is transformative, but we’re still in the early stages—like before the invention of the IBM PC. Much like calculators, AI should be viewed as a productivity tool to enhance our ability to perform math.
Today, the most effective use of AI in healthcare is analyzing individual medical histories longitudinally alongside population health data. From my experience in various healthcare sectors, I don’t see payers or ERISA managers actively using data to uncover missed insights or new treatment options for patients.
While there’s much discussion about the potential of AI in genetic testing, I believe its mass application won’t lead to significant transformation. Although genetic testing can provide valuable insights—97% of the testing did nothing for me, but the pivotal 3% of my own results mattered—it’s essential to contextualize that genetics aren’t the primary health determinants in society. Research indicates that health outcomes are influenced by:
- Lifestyle: 40-60%
- Genetics: 20-30%
- Social/Environmental Factors: 15-20%
- Access to Healthcare: 10-15%
These percentages can vary significantly. For instance, someone with a strong genetic predisposition may be more affected by genetics, while others in resource-poor environments may be more influenced by social determinants of health and environmental – such as clear air and water.
The best approach is to integrate longitudinal health data with genetic testing, providing a comprehensive view of consumer health and relevant social and environmental factors. However, while the government should be incentivized to reduce costs by changing behaviors and improving access to healthcare, it often falls short in investment. In a managed care-driven world, the long-term value of these insights is compromised as individuals typically change insurance providers or employers less than five (5) years.
This places the responsibility squarely on consumers. Our goal is to empower them with a centralized Universal Health Record that utilizes AI to delve deep into data and offer meaningful feedback, ultimately reshaping the dynamics of the largest industry in America, healthcare.
-Noel Guillama, Chairman