When new signals show up in real use, we like share a few from the Lumeris Lab so you can see what’s influencing our roadmap. Feedback from 400 Americans surfaced practical ways to improve AI’s utility and usability in primary care. These insights move quickly into product decisions so that Tom is built with an understanding of real patient needs and expectations. Here are the takeaways worth a closer look.
Methodology
28-question survey to U.S. adults (18+), fielded via a research firm in Oct 2025; n=400. Margin of error ±5% at 95% confidence. Balanced across gender, race, income, education, urban/suburban/rural, age, and life stage; respondents skew slightly toward people managing chronic conditions.
Most people aren’t scared of AI—they’re impatient for it to fix the parts of care that feel slow and impersonal. Your product roadmap should start there.
Findings
Top improvements people expect from AI in healthcare
Personalized information (32%), faster information (20%), reduced wait times for care (15%).
Top worries
Misdiagnosis/wrong advice (46%), data misuse/privacy breach (31%).
So what? Build for speed and relevance, and show your work (sources, provenance, human oversight). That’s how you balance usefulness with trust.
Lumeris learnings
- Make personalization visible: include name, condition context, and a “Best Next Action” with links to evidence. (Brand guidance: Tom augments clinicians, surfaces guideline-aligned insights; physicians remain decision-makers.)
- Reduce time-to-care: collapse steps from question → scheduling → prep; expose “you’re scheduled / refill confirmed” states.
- Cite and summarize: concise answers with citations build confidence and reduce fear of “wrong advice.”
Research facilitation provided by Savvy Cooperative.
