Faces of Digital Health

When Demetri Giannikopoulos was diagnosed with multiple sclerosis, his community neurologist handed him a sheet with fifty medication options and told him to pick one. That was a long time ago. Today he's the Chief Innovation Officer at RadAI, overseeing how artificial intelligence gets deployed in radiology across US health systems — and he's spent two decades learning how to navigate a healthcare apparatus that, in his words, "is not designed for sick patients."

In this conversation Demetri explains why the most valuable thing AI has done for him as a patient isn't clinical — it's the 50 pages of insurance underwriting documents he fed into ChatGPT to save several thousand dollars on a plan that looked, on paper, worse. He walks through his "red team" prompting technique, the error he caught in a radiology report where legacy speech-recognition software had dropped the word "no," and why he thinks the regulatory debate around AI in healthcare should look less like drug approval and more like how we regulate nuclear power. If you want a ground-level view of what AI can and cannot do inside the American medical system, this is where to start.

Additional resource with prompt tips: https://aipatients.org/
Additional resource: Scanxiety toolkit: https://edge.sitecorecloud.io/americancoldf5f-acrorgf92a-productioncb02-3650/media/ACR/Files/Clinical/Patient-Family-Centered-Care/PFCC-Scanxiety-Toolkit-Brochure-Digital-Version.pdf Full Agentic Patient series: https://www.facesofdigitalhealth.com/agentic-patient-blog

Detailed summary and tips from Demetri: https://www.facesofdigitalhealth.com/agentic-patient-blog/red-teaming-your-health-plan-demetri-giannikopoulos-on-responsible-ai-the-cures-act-and-what-patients-should-actually-do

6 tips on AI use for patients: https://fodh.substack.com/p/the-agentic-patients-are-here

Diana Ferro works at a major pediatric hospital in Italy, working on AI infrastructure, rare diseases, and — importantly — the International Alliance of Pediatric Centers on AI. Unlike the patient voices earlier in the Agentic Patient series, she sits on the other side of the consulting-room door. Her concerns are sharper, more specific, and more uncomfortable. She is not against patient AI use. She is watching what happens when desperate parents, teenagers in crisis, and sycophantic chatbots meet in a pediatric setting and she is trying to build the guardrails in real time.

Diana frames AI in pediatric medicine as a two-front problem. On one front, Italian hospitals are racing to build the data infrastructure — EU-funded — to share research across institutions and turn billing data into diagnostic and predictive tools. On the other front, patients and families are already ahead of the system, using consumer LLMs in ways that clinicians are not trained to respond to.

She describes three specific, observed harms she's seeing in pediatric practice:


parents using AI to deny rare-disease diagnoses,


adolescents using AI as a pro-eating-disorder coach by telling it they want to "lose weight to be healthy,"


young people with weak support systems finding AI easier to talk to than a clinician — including, she notes, in contexts tied to self-harm.

The Agentic Patient Series: https://www.facesofdigitalhealth.com/agentic-patient-blog

Agentic Patient 6 tips: https://fodh.substack.com/p/the-agentic-patients-are-here

Russ was diagnosed with bowel cancer in late 2021 and simultaneously with smoldering myeloma, aged 40. The smoldering myeloma has been inactive; the bowel cancer has progressed through multiple surgeries (bowel, liver, lung) and is now stage 4, on active chemotherapy. He runs AI for the business he works for, so his day job is adjacent to the technology. He blogs publicly about his disease at fcancerwith.ai and on LinkedIn. He is British; cared for by the NHS with some private care around the edges. He is articulate, technically fluent, and willing to pay roughly £200 a month for AI subscriptions.

This is the first episode of a special series called The Agentic Patient, which is a series about how real patients are using AI to navigate their health. We go into details, how do patients make AI help them do better, not worse, and what should we all be mindful of along the way? Which tools do they use? Which prompts? What's working, what isn't? It is not just patients on the series, it's also researchers and clinicians. These discussions are intended for informational purposes only, and should not be relied upon as a sole source of medical information or as a substitute for professional medical advice, diagnosis, or treatment.

In the first episode, you will hear from Dale Atkinson. Dale was a financial crime investigator before his terminal cancer diagnosis. This is important understanding the research he did on his cancer.The skills required for a compliance officer trained him to read dense regulated documents, which is a transferable skill for medical literature. He is a compelling interview subject and, simultaneously, a survivorship-biased sample of one.

Key insights:

1. ChatGPT confuses popularity with authority.

2. Clinician dismissal produces concealment, which produces real harm.

3. Most advanced-stage cancer patients are using AI in secret.

4. Use AI to narrow the search, not to summarize the answer. Read the papers yourself.

5. Context hallucination is the subtle killer not invented studies, but correctly-cited studies applied to the wrong disease.

6. Concealment is a safety emergency caused by clinician posture, and disclosure is non-negotiable regardless.

7. Custom GPTs with closed corpora are the step up from consumer chat, and require real time investment.

8. A clinical team you can bring AI findings to is a prerequisite, not a nice-to-have.

9. Clinician language and clinician posture shape patient behavior — agency begets partnership begets better care.

10. n=1 is n=1. Dale's outcome is extraordinary; his method is instructive; the two must be reasoned about separately.

This episode explores how Denmark’s 2024 health reform is accelerating an already mature digital health ecosystem, with a special focus on Copenhagen’s municipality-led elderly and community care services.

Speakers Anders Elken Sønderby and Rikke Saltoft Andersen from City of Copenhagen, explain how the reform responds to demographic pressures: a growing elderly population, increasing chronic disease burden, and workforce shortages. Rather than representing a radical shift, the reform acts as an acceleration layer on top of long-established digital health infrastructure.

The discussion dives into how municipalities support home care, nursing, rehabilitation, prevention, and care homes, all digitally connected with hospitals and general practitioners through Denmark’s long-standing MedCom interoperability framework. A strong emphasis is placed on care continuity, ensuring data follows citizens across hospitals, care homes, and home-based services.

A standout theme is Copenhagen’s effort to include relatives and informal caregivers in care planning through digital dialogue tools and telemedicine, improving health equity and patient support.

The conversation concludes with the city’s AI ambitions, particularly a proof-of-conceptwhich uses speech-to-text, summarization, and structured categorization to reduce documentation burden for care workers and improve data quality across 10,000 staff members.