How Targeted Patient Education Improves Outcomes - Stephen Page, SmarterHealth.AI

AI Has the Brain, but Healthcare Still Needs the Heart

My conversation with Stephen Page explores how better patient education can improve outcomes, reduce readmissions and help healthcare organizations use artificial intelligence more responsibly.

Healthcare has never suffered from a lack of information. If anything, patients and clinicians are surrounded by more information than they can reasonably absorb, evaluate or use. The real challenge is making sure people receive information that is accurate, relevant and understandable at the moment they need it most.

That challenge was at the heart of my recent conversation with Stephen Page, founder and CEO of SmarterHealth.AI, on I Don’t Care with Dr. Kevin Stevenson.

During my years as a hospital executive, I saw how difficult effective patient education could be. Hospitals provided discharge instructions, educational materials and access to online resources, but handing someone information was never the same as helping that person understand what to do next. A patient learning about a new diagnosis, medication or procedure may be frightened, distracted or overwhelmed, which makes it difficult to retain everything explained during a clinical encounter.

Stephen believes artificial intelligence can help address that problem by connecting patients with professionally curated information that is easier to understand, available when questions arise and adaptable to different languages and levels of health literacy.

The opportunity is not simply to give patients more content. It is to help them become better informed participants in their own care while extending education beyond the limited time available during a physician visit or hospital stay.

Patient education as more than a patient-experience initiative

Stephen and I also discussed why patient education must be viewed as more than a patient-experience initiative. Hospital executives are operating under enormous financial pressure, so any new technology must solve a meaningful clinical, operational or financial problem. Preventable readmissions provide a clear example of how those priorities intersect.

A patient can undergo a successful procedure and still return to the hospital because medications were misunderstood, symptoms were not recognized or follow-up instructions were unclear. The patient experiences another disruption in care, clinicians face additional demands and the hospital may incur a substantial financial penalty. If better education and continued engagement can prevent even a portion of those readmissions, the value reaches far beyond satisfaction scores by improving outcomes and producing a measurable financial return.

AI’s potential to improve health equity

Our conversation also explored AI’s potential to improve health equity. Patients living in rural and underserved communities often have less access to specialists, reliable educational resources and ongoing clinical support. A platform capable of delivering credible healthcare information in numerous languages could help narrow some of those gaps, particularly when it provides patients with understandable guidance outside the walls of a hospital or physician’s office.

However, the same technology that expands access also creates serious questions about privacy, security and ethics. Stephen described being offered an AI “personal doctor” that requested extensive access to his medical records during the registration process. The potential convenience was obvious, but so was the risk. Patients deserve to know who controls their information, how it will be used and whether it could someday influence decisions involving insurance coverage, employment or other aspects of their lives.

As I told Stephen, AI may have the brain, but it does not necessarily have the heart or ethical judgment required to make every healthcare decision. That does not mean we should resist the technology. It means healthcare organizations must approach it with discipline and ensure that governance, security and clinical oversight are part of the strategy from the beginning.

Embracing AI in healthcare

Some healthcare leaders have enthusiastically embraced AI, while others are trying to keep their distance. Avoidance is no longer a viable strategy because payers, vendors and competitors are already using it. Hospitals of every size need leaders who understand what AI can do, where it can create risk and how proposed solutions should be evaluated. Even small and rural hospitals are forming committees to establish standards and determine where AI can provide meaningful value.

The organizations that benefit most will not necessarily be the ones that purchase the greatest number of AI products. They will be the ones that ask whether a solution improves patient understanding, supports clinicians, reduces avoidable utilization, protects sensitive information and produces measurable clinical or financial results.

Stephen’s message to healthcare leaders was straightforward: AI is coming, and we must learn how to embrace and leverage it effectively.

I would take that thought one step further. AI is not merely coming; it is already reshaping healthcare. Our responsibility is to ensure that it makes care more informed, accessible and human rather than simply more automated.

Consider this question: Where could better patient education make the greatest difference in your organization—in outcomes, readmissions, access or trust?