Tom Leary, Senior Vice President at the Healthcare Information and Management Systems Society (HIMSS), recently addressed the Society for Women’s Health Research Policy Advisory Council on where digital health is headed. His framing was global — “realizing the full health potential of every human” — and his priorities were specific: ethical AI, digital health transformation, cybersecurity, and workforce development.
It was a useful conversation. And it pointed to exactly the kind of structural optimism that the digital health sector does well, and the blind spots it still needs to reckon with.
What HIMSS Is Tracking Correctly
Leary was unambiguous about urgency in one area: cybersecurity. Health care data has become one of the most valuable and most targeted assets in the digital economy, and the consequences of breaches fall disproportionately on patients — particularly those whose data is most sensitive. That HIMSS is centering cybersecurity as a governance issue, not just a technical one, is exactly right.
On AI, Leary cited a 2024 HIMSS survey finding that 86 percent of health care and IT professionals now use AI in their organizations, and that 60 percent recognize its ability to “uncover health patterns and diagnoses beyond human detection.” Remote monitoring, real-time flagging, earlier intervention — the applications are real and the potential is significant.
His framing of the “human in the loop” question — where should human oversight remain, and where can it be responsibly removed? — is one of the most important governance questions the sector faces. HIMSS has been working on this for years. That institutional attention matters.
What the Sector Still Gets Wrong About Women
Here is where the optimism needs to be stress-tested.
AI trained on biased data reproduces biased outcomes. If the data sets used to train diagnostic algorithms underrepresent women, women of color, and women with atypical presentations — and historically, they do — then more sophisticated AI produces more sophisticated error. Faster, more confident error.
Telehealth expands access. It does not automatically improve care. Women in rural areas face physician shortages that telehealth can partially address. But telehealth without the ability to receive a referral, afford a specialist, or access follow-up care is not a solution — it is a first step with nowhere to go. The structural barriers remain.
Wearables and remote monitoring are unevenly distributed. The populations who benefit most from these tools are often the populations least likely to have them. Any serious digital health equity agenda has to grapple with the access gap, not just celebrate the technology.
Maternal health is the starkest test case. More than 80 percent of pregnancy-related deaths in the United States are preventable, according to CDC data. Leary cited maternal health as an area where digital tools can improve outcomes — and he is right. But “can improve” and “will improve” are not the same sentence. AI triage tools deployed in systems where Black women’s pain is consistently undertreated will not save lives unless the clinical culture changes alongside the technology.
A Disruptive Take
The digital health sector has been extraordinarily good at building things. It has been considerably less good at asking whether those things are being built for everyone.
“Realizing the full health potential of every human” is a mission worth having. But it requires acknowledging that the humans who have historically been excluded from research, underrepresented in clinical trials, and undertreated in health systems will not automatically benefit from digital innovation just because the innovation exists.
The companies, institutions, and policymakers who are serious about this will build diversity requirements into AI training data as a non-negotiable standard. They will fund telehealth infrastructure in the communities that need it most. They will measure outcomes — not adoption rates — by race, sex, income, and geography.
The technology is not the hard part. The hard part is deciding who it is actually for.
