S1, E37 - Danny van Leeuwen, MPH, RN, Health Hats: Patient's POV on AI Tools

Summary

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Practical AI in Healthcare, S1 E37:

Danny van Leeuwen, MPH, RN – "Health Hats: Patient's POV on AI Tools"
Date: May 17, 2026
Host: Dr. Stephen Lapkoff (with Leon Rozenblit, JD, PhD, absent)

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EPISODE OVERVIEW

In this episode, Dr. Stephen Lapkoff welcomes Danny van Leeuwen, a nurse, patient advocate, technologist, and host of the Health Hats podcast. Danny brings a multifaceted perspective as a patient, caregiver, clinician, and digital health innovator—uniquely positioned to discuss the real, practical impact (and limits) of AI in healthcare from a patient’s point of view. The conversation candidly explores the promise and pitfalls of digital health tools, how to leverage AI for personal health management, the importance of meaningful data and human connection, and Danny’s "Three T’s and Two C’s" framework for evaluating new technologies.

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DANNY'S ORIGIN STORY & PERSPECTIVE

• Background of Advocacy and Nursing ([03:08])

  • Child of Holocaust survivors; early exposure to civil rights movement.
  • Became a draft counselor during Vietnam War era, learning the value of changing systems from within.

• From Aide to Nurse ([04:07])

  • Chose nursing over other jobs to avoid having to cut his hair:

    "I could have read water meters or become an aide at the Detroit Psychiatric Institute. Reading water meters paid more, but I didn’t want to cut my hair, so I got the job as a nurse’s aide." ([03:32] — Danny)

  • Early career focused on home care and physical rehabilitation, culminating as the first male public health nurse in Western Massachusetts in 1976.

• Systems Thinking Shift

  • Experience across specialties (ED, ICU, pediatrics, behavioral health), then moved from individual health to organizational health, leading EHR implementations and consulting.

• Patient/Caregiver POV

  • Diagnosed with MS in 2009, retrospectively for 25 years; episodes misattributed to family cardiac history:

    “The pattern of what was going on was in my records for 25 years, but nobody had synthesized it.” ([06:51] — Danny)

• Multiplicity of Roles: “Health Hats” ([08:01])

  • Patient, caregiver (for family members), nurse, advocate, informaticist, podcast host:

    "Wearing many hats has gotten me a seat at many tables... But really, I wasn't there for the seat itself. My goal was always to open seats for people who weren't there yet." ([08:28] — Danny)

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DIGITAL HEALTH & AI: EARLY PROMISES, REAL WORLD GAPS

• First Encounters with Digital Health
  • Active in the "Blue Button Plus" initiative—pushed to add a caregiver field and patient-relevant nuance (“what works for me when I’m afraid or in pain”). Had some success:

    “The caregiver field got added... but they were only interested in putting a name in the field, not doing anything with that information.” ([10:43] — Danny)

  • Early adopter, but deep skeptic:

    "I've probably tried over 100 health apps and I would say that I've used five more than three times." ([11:40] — Danny)

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CHALLENGES: MEDICAL DATA OVERLOAD & (MIS)USE

The Problem with Patient Data ([13:09])

• Patient-Reported Data is Crucial

  • Personal health goals = "Best health" (not 'cured', but optimal for circumstances):

    "To get there, I need my own health data. Not just what's in my clinician's chart, but what I know about myself, my circumstances, my environment, my history, my habits." ([13:40] — Danny)

• Medical Record Access = Firehose, Not Fountain

  • Attempted to obtain all his health records (2011-2025): received a four-pound box of unordered paper ([15:48]).
  • "Access" ≠ "Usable": 300 pages of PDFs are not patient-friendly or helpful.

• Key Quote:

  "Access to data and access to usable data are really different." ([16:48] — Danny)

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PATTERNS, PREPAREDNESS, & THE ROLE OF AI

What Patients Actually Need from AI ([18:00], [22:56])

• Seeing Patterns to Formulate Better Questions

  "I want to see patterns that take my circumstances, my environment, my habits, my treatment over time... Patterns are how I formulate the right questions." ([18:00] — Danny)

• Nursing Angle: Technology Should Return Time

  • Goal as a nurse: “Put myself out of a job”—i.e., empower the patient/family.
  • Free up time from charting/data hunt, enable deep nurse-patient presence.

• Undercaptured Realities: Pain, Fear, Cognition

  • Patient reality is not just labs; data often excludes what matters:

    “Pain changes what you can do and what you can decide. Fear closes your heart, it closes your mind... Cognition varies...” ([20:57])

• AI's Real Promise (and Limits):

  • Should support pattern-recognition, personalization, and communication.
  • But, as a skeptical adopter, finds most tools don’t deliver on this everyday utility.

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DANNY'S OWN AI/TECHNIQUE TOOLKIT

Practical Uses ([22:56]–[28:18])

• Personal Tracking & Experimentation

  • Tracks steps, music played, falls, weight, clinician visit audio recordings, symptoms.
  • Uses LLMs (like Claude) to analyze these personal data/journal entries for patterns.

• Examples of Insights ([26:46])

  • Claude (LLM) offers suggestions:
    • Ex: "Have you thought about seeing a physical therapist?"—which matches his own pattern.
    • Caught possible medication side effect impacting mood, confirmed by neurologist.

• On Surprising AI Recommendations:

  “Does it surprise you that it comes up with stuff you didn’t see?”
  “No, no, no. I mean, to me, you know…” ([28:18] — Danny)

• Importance of Asking the Right Questions

  • Thanks to connections like Amy Price, refined ability to interrogate AI from different angles:

    "That's where the unexpected comes up." ([29:18] — Danny)

Notable Moment

"You’re describing yourself as being AI literate—understanding how to use the tools, being skeptical, interpreting the information... those are all components of AI literacy." ([29:40] — Dr. Lapkoff)

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AI LITERACY—FOR PATIENTS & PROVIDERS

• Most People (Even in IT/Clinical Roles) Lack True AI Literacy ([29:40])

• Danger if Patients or Providers Don’t Know How to Query or Interpret:
  Misapplied tools = risk to care quality.

• Skepticism is Always Necessary:

  “You could say that same thing about doctors... There's a tremendous variation, and it’s very different when I am... directive in the conversation... I get a very different output than when I’m not. And I still have to be skeptical of what doctors tell me. Until I build trust...” ([31:04] — Danny)

• Holding On to Patient Agency:

  "There are certain decisions I don't want to give to the doctor or to AI. Like, I don't want to mess with my pathological optimism. I want to progress as slowly as possible, and I want to keep playing my horn. These are really important things to me..." ([31:49] — Danny)

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AI IN THE CLINICAL ECOSYSTEM: PROVIDER PERSPECTIVE

• Are His Team Members AI Literate?
  • Unsure; they use built-in tools in Epic. But even digital-savvy clinicians aren’t always organized in useful ways.
  • Example: Claude analyzes his neurologist's 10-year note, finds and surfaces a tracking scale. Danny uses this to open dialogue with the doctor about what he needs in documentation ([33:31]).

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AI AS A RECORD DIGESTER: REAL-WORLD UTILITY

• Summarizing and Organizing Records ([34:15]–[35:40])
  • Both agree LLMs can "digest" and summarize massive, poorly organized records better than most humans.
  • Caution: Initial amazement, but on review, can miss key points or make basic errors; always keep "human in the loop."

“My rule is sleep on it and check it again. And then it’s like, oh, my god, this... got some very basic things wrong. And then I’ll say, oh, you missed this and you missed that, and it’ll go, oh, you’re right, I did.” ([35:11] — Danny)

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THE “THREE T’S AND TWO C’S” FRAMEWORK

Danny’s Practical Rubric for Evaluating Digital Health Tools ([36:30])

• Time:
  • For learning, planning, real conversation/trust-building.
  • "The clock isn't the enemy, it's the wrong things filling the time."
• Trust:
  • Takes time, can be quick, but erodes fast.
  • "Most digital health tools and AI have a trust deficit... because the people who use them don't trust them."
• Talk:
  • Need for authentic, joint decision-making conversations.
• Control:
  • "I trust more when I have power in a situation."
• Connection:
  • Human connection is irreplaceable. AI can extend, but not manufacture it.

“I use that framework when I’m evaluating any digital health technology.” ([39:04] — Danny)

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PARTING ADVICE FOR PATIENTS & DEVELOPERS

Advice for Patients:

• Use AI, experiment, “find a buddy,” and talk to your clinician about it ([39:35]):

  “Advocate for humans in the loop. I don’t care what the study says. It’s about humans. We are human. Keep humans in the loop.”
  “Find a buddy and experiment... If you’re comfortable, mentor; be the buddy.”

Advice for Clinicians, Developers, Systems:

• Involve patients, caregivers, and practicing clinicians at the beginning of product design.
• Build tools for real-world needs, not just VC excitement or developer convenience.

"You need to have patients, caregivers, and practicing partner clinicians in the design... so it solves the problems people have, not the problems that the developers think are there or the venture capitalist thinks are going to make money.” ([40:40] — Danny)

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MEMORABLE QUOTES & MOMENTS

• “I want to be clear that I’m a privileged white old man with MS living in Boston. But I’m an N of 1 and I don’t represent other patients. I’m representing myself.” ([13:13] — Danny)
• “There’s a gap between what’s promised with digital technology and what’s useful for people.” ([11:53] — Danny)
• “Drink water is by far the most successful intervention across all my symptoms. It’s so cheap, so easy.” ([23:23] — Danny)
• “Access to data and access to usable data are really different.” ([16:48] — Danny)
• “Three T’s and Two C’s: Time, Trust, Talk, Control, and Connection.” ([36:34] — Danny)

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KEY TIMESTAMPS

• [03:08] Danny’s path into nursing, advocacy, system change
• [06:51] Living with undiagnosed MS for 25 years, bias in clinical reasoning
• [08:01] “Health Hats”—multiple perspectives as patient, caregiver, nurse
• [10:43] Blue Button Plus; the limits of current digital health design
• [11:40] “Over 100 health apps, used five more than three times”: gap between promise and value
• [13:40] Best health: importance of patient-generated data
• [16:48] The difference between data access and usability
• [20:57] Pain, fear, cognition—critical patient variables not yet captured by most EHRs
• [22:56] How Danny uses spreadsheets, journaling, and LLMs for self-management
• [26:46] AI insight about medication side effects: practical benefit
• [29:40] AI literacy, skepticism, and importance for patients/providers
• [31:49] Maintaining agency as a patient: optimism, purpose, joy
• [33:31] Reorganizing clinician notes using AI
• [35:40] AI summaries need rigorous checking—never “set and forget”
• [36:34] The “Three T’s and Two C’s” framework for evaluating health tech
• [39:35] Closing advice: use, experiment, advocate, collaborate, and include all voices in design

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FINAL TAKEAWAYS

Danny van Leeuwen’s lived experience both inside and outside of healthcare gives him a rare vantage point: as a person with MS, as a nurse, as an advocate, and as someone still experimenting with AI tools—he brings hard-won skepticism and hope to the AI-in-healthcare conversation. His “Three T’s and Two C’s” framework underlines the real-world, human-first considerations that underlie successful technology adoption: time, trust, talk, control, and connection. No matter how advanced AI becomes, it must serve these fundamentals—and always keep a human in the loop.

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“Advocate for humans in the loop. I don’t care what the study says. It’s about humans. We are human. Keep humans in the loop.”
— Danny van Leeuwen ([39:36])

Transcript

[Dr. Stephen Lapkoff]

Welcome to Practical AI in Healthcare, the podcast that cuts through the noise to

[Podcast Host / Narrator]

spotlight real world solutions delivering real world value. From patient care to clinical research, from life sciences to patient engagement, we focus on what's truly moving the needle in healthcare. No hype, no theory, just practical insights where AI is making a true impact. Welcome aboard and let's get to it. As many of our listeners know, Leon and I work very closely with the DCI Network Division of Clinical Informatics at Bethesdril Deakin's Medical center in Boston. This June, the network is hosting Patient powered Digital Health 2026. The conference will bring together patients, innovators, industry leaders, healthcare providers and policymakers to shape the next generation of real world patient centered solutions. The meeting will run from June 22nd to the 24th in Boston at Harvard Medical School. We've arranged for our listeners to get a discount on registration to the meeting. If you register between now and May 15th and use promo code PracticalAI June no spaces, you'll receive 30% off your registration fee. You can learn more at dcinetwork.org patients2026. In addition, we're always looking for sponsors. If you or your company are interested in becoming a sponsor, please reach out to admincinetwork.org see you in Boston.

[Dr. Stephen Lapkoff]

Hello and welcome to this week's edition of Practical AI in Healthcare. My name is Dr. Stephen Lapkoff and this week I'm actually on my own because my partner, Dr. Leon Rosenblit is actually on spring break with his kids. So I am covering for him and he'll be back in the next week. This week we have a guest who we met at a conference in Boston a few months ago at the Beth Israel. At the DCI Network, we have Danny Van Leeuwen. Danny is a nurse. He has background in giving actual physical care to patients. He actually runs his own podcast called the Health Hats and he's been using AI in both his personal life and in his professional life very extensively. Also, Danny has a significant medical condition and I'll let him explain that in the course of the discussion because it's with that lens that we got introduced at our Patient Centric AI conference. And that's why we thought it'd be a good idea to have Danny come and have a chat with us. So welcome to the podcast. Danny, how are you today?

[Danny Van Leeuwen]

I'm good, thank you. Thanks for having me. I appreciate it.

[Dr. Stephen Lapkoff]

So Danny, as you probably have heard because you've helped us with our podcast and for that I want to say thank you for those who are listening in. Danny runs actually a group that actually helps folks running podcasts improve their podcasts. And he's had Leon and I on many times to listen to critiques and feedback. It's been very, very helpful. Danny, we often start our podcast with asking for folks origin stories like how did they get their cape and their superhero tights? What did you do to get you to this point in your life? And just tell us the background of what brought you here.

[Danny Van Leeuwen]

Thanks. So I'm a child of Holocaust survivors and my parents. When I was young, my parents were active in the civil rights and fair housing movement in the 60s. And when I was 16 and I was thinking about the war in Vietnam and worried about getting drafted, I wanted to learn what I could learn about the draft and how I could protect myself and manage. And I went to a church in downtown Detroit and I went for a session of draft counseling. As, you know, a little precocious at 16. And I found it fascinating, and they found me fascinating, and they encouraged me to become a draft counselor. And so I actually took their course and became a draft counselor. And what I learned is that you change systems from the inside, not the outside. And I learned how the sausage was made, and that really pointed me in a direction. The way I got into nursing is really because I didn't want to cut my hair. I had an opportunity for a job at one point, and I could have read water meters or become an aide at the Detroit Psychiatric Institute. And reading water meters paid more, but I didn't want to cut my hair, so I got the job as a nurse's aide. And while I was there, they introduced me to the idea of going to nursing school, which was amazing.

[Dr. Stephen Lapkoff]

It was more. You got paid more to read meters, water meters than you did?

[Danny Van Leeuwen]

Yes.

[Dr. Stephen Lapkoff]

That's unbelievable. Life gives you some real interesting turns and twists, doesn't it?

[Danny Van Leeuwen]

It does. And I was really fortunate because my first jobs in nursing or in physical rehabilitation and home care, I just happened to be in a place where the Hoyok visiting nurses was dying to hire a guy, and I was a brand new nurse and they ended up hiring me. And so my first introduction to nursing was not in acute care, it was in home care. And actually, I was the first male public health nurse in western Massachusetts in 1976. And really what I learned there was that most healthcare does not occur in the medical system. It incurs outside the medical system. And so when I ended up getting into medical care, it was always so interesting to me that everybody there thought this is where, you know, health happened, which it doesn't. So over the 20 years of working as a nurse, I've worked in, other than rehab and home care, I've worked in the emergency department, I've worked in ICU, I worked in pediatrics, behavioral health. And after about 15, 20 years, I shifted from becoming a student of individual health to a student of, of organizational health. And what I mean by that is I got into performance improvement. I led a couple of electronic health record implementations, I had a couple of gigs in the C suite, I did some consulting. Now, in 2009, I was diagnosed with multiple sclerosis. And when I was diagnosed, I learned that I had had it for 25 years. And since my father died young, he died at 45 when I was 19 of his second heart attack. And so every time I would have some kind of episode, I would get a cardiac workup. And by the time the cardiac workup was done, you know, the episode was over. And this went on two, three, four times a year for a long time. And there was a pattern there. And nobody was connecting the dots for 25 years. That's very important to me because the pattern of what was going on was in my records for 25 years, but nobody had synthesized it.

[Dr. Stephen Lapkoff]

They may have been biased. Right, because of your family history and having these episodes. You know, as a clinician, you get very biased by family history, and that can actually lead you down roads which may not be correct. And it sounds like that's precisely what happened with you.

[Danny Van Leeuwen]

So I, I want to bring in the caregiver role because I have been a caregiver for my grandmother, my mother and a son in their end of life journeys. So I've been on many sides of very difficult decisions. As you said that my shtick is health hats, and I'm health hats because I'm a patient, I'm a caregiver, I'm a nurse, I'm an advocate, I'm an informaticist, I'm a podcast host. I wear a lot of hats. And wearing many hats has gotten me a seat at many tables because they can check off boxes. When it was really different to be bringing patients on board, I was an easy choice. I was at the table for technical expert panels, at cms, at National Academy of Medicine, at ahrq, ahrq, National Quality Forum, pcori, Patient Centered Outcomes Research Institute. But really, I wasn't really there in it for the seat itself. My goal was always to open seats for people who weren't there yet. Now, let's Build the bridge. Since this is a podcast about AI, let's build that little bit of that bridge. So my first, like, serious experience with. Well, I don't know about my first. I was involved in something that you probably are familiar with, which was the Blue Button plus program. And my goal in that I was there both as a patient and as somebody who was working with people with disabilities. I was VP of Quality for an organization that supported about 40,000 people with disabilities. And my goal for that couple of years of weekly or every other week, I can't remember calls, was to add a caregiver field to the data set and to also introduce the idea that what people needed was information that would be able to say what works for me when I'm in pain and what works for me when I'm afraid, which was an issue for me and it was an issue for the organization that I was working with at the time. Now I have to say that the caregiver field got added, so I felt some success in that. But as a nurse leader in the informatics group I was part of, really, they were only interested in putting a name in the field, not doing anything with that information, which I said, just collecting the data.

[Dr. Stephen Lapkoff]

They didn't care what the data was used for. Is what you're saying correct?

[Danny Van Leeuwen]

Yeah.

[Dr. Stephen Lapkoff]

Yeah.

[Danny Van Leeuwen]

And I couldn't. Got no traction on the pain and fear, which now that I'm older, I understand why, how difficult that is. Nevertheless, it's something that's important to patients and caregivers. So I think I would close this section with that. I am both an early adopter of technology and a rapid skeptic that I'm kind of making this number up. But I've probably tried over 100 health apps and I would say that I've used five more than three times.

[Dr. Stephen Lapkoff]

Okay.

[Danny Van Leeuwen]

And so I think there's a gap between what's promised with digital technology and what's useful for people. So that's really why I'm here and what's guiding for me in this.

[Dr. Stephen Lapkoff]

So let's take it to the next step in our pre call. I didn't even know about your personal background to that degree. We can take that one offline later about the Holocaust survivor issues. We have family. I have family in that same situation, frankly. Let's change gears and talk about the challenges that you've seen. You opened the door a little bit on that a few minutes ago in terms of people wanting to collect data, but not necessarily doing much with the data, not being able to understand the True value of the data to some degree. And you said it yourself, people weren't connecting the dots. Yeah, medical records have always been complicated. They've always been bulky, they've always been full of information, some of which is really relevant, a lot of which is not so relevant. And connecting the dots to making that an important information source is not always an obvious task. So what was the particular angle on that challenge that you were trying to gun at?

[Danny Van Leeuwen]

Well, I think we have to take a step back and think about what is. I'm just going to speak for myself. Okay. I know that I often, you know, as I said, I get asked to sit at the table because people can, you know, check boxes like, is that I'm a patient. I want to be clear that I'm a privileged white old man with Ms. Living in Boston. But I'm an N of 1 and I don't represent other patients. I'm representing myself here and my perspectives, my goal in terms of my health is best health. And what I mean by best health is optimal health and function, physical, mental, spiritual. Not a cure, but best health for where I am, what I have right now. And to get there, I need my own health data. Not just what's in my clinician's chart, but what I know about myself, my circumstances, my environment, my history, my habits. Not just my medical history, my life history, my treatment responses. And so that's like patient reported data. And that's stuff that only exists because I observe it and sometimes I record it, and that's where it falls apart right away. You were just alluding to some of it, that there's all this medical data. And what's useful about that, I think Dave Debrancker was a guest on your show. He was, and when he launched his Gimme My Damn Data campaign, I responded to him with watch what you wish for. You'll be trying to drink dirty water from a fire hose. And that was years ago and it's still true. So six months ago, I've been on a mission to gather my medical data. And I've been with my primary care practice since 2011. And I wanted all that data from 2011 to 2025. This was like in December, I started on this crusade of trying to get my data. And actually two months later, I got a box, a four pound box of paper. And it was paper that was not in chronological order. And it's just sitting right here. I've scanned it in. It's not.

[Dr. Stephen Lapkoff]

Was it a printout of Epic or something?

[Danny Van Leeuwen]

Or was it actual It's a computer printout. It seems like it's a vendor that they use to.

[Dr. Stephen Lapkoff]

It wasn't digital. They sent you literally sent you a box of paper.

[Danny Van Leeuwen]

Yeah, it was a box of paper. And then I use a lot the Beth Israel Leahy Mont. Auburn system. And I asked for the last three months of my records and I got 296 pages of redundant non searchable PDFs and I got that in 15 minutes. I see a lot of doctors, so maybe I had seen. I think I had maybe eight or nine visits and it just happened to be a three month period that was busy for me. But I got 296 pages. And so that really adds to your comment, which is that access to data and access to usable data are really different.

[Dr. Stephen Lapkoff]

Oh absolutely. And yeah, I'll tell you, in my world, I think you know that I've worked in the life sciences for many, many years and we are consumers of healthcare data on many levels. We consume medical claims, we consume electronic medical records. And one of the hardest things about using medical records for research or for outcome studies and things like that is the very fact you're describing, which is the data tends to be sparse, it tends to be poorly organized. It doesn't always come in an encoded fashion. Thank God most of what we get these days is at least digital. No boxes of paper for us these days. But it wasn't so long ago that when it was all paper we couldn't get that data in the first place. It just wasn't even gettable. So at least you've made some progress. And I know that you sit on some national level boards around outcomes and you can talk about that in a moment. But those are, you know, those boards are trying very hard to come up with outcome studies and ways of. Let me back that up. They're coming up with ways of using data to perform outcome studies by harmonizing and distilling down to usable forms of this EHR data, which is so challenging.

[Danny Van Leeuwen]

I think what's. I think I'd like to focus on my data. And so what I want to do is I want to see patterns. I want to see patterns that takes my circumstances, my environment, my habits, my treatment over time. And because I think that these patterns are how I formulate the right questions. So the right questions before I go into a clinical encounter, they're how I track when something is actually working. And it helps me to coordinate across care teams that don't talk to each other and make decisions that I can live with that help Me attain this goal of best health. So that's the job. Formulate better questions, seek better answers, make better decisions. And AI is the tool that I try to use to do it. Now, whether it's up to the task or not is different. I want to stick in the nursing angle, if you don't mind. Okay, yeah. So, you know, one of the things that I learned the way I got started in nursing is that my goal as a nurse was to put myself out of a job. So that sounds counterintuitive, but what I mean is from minute one with a patient and family, I'm planning my exit. And to do that, I need maximum facetime. I need real present, real conversation, real relationships. Not less charting. I was going to say not charting, not documentation. So that's just ridiculous. But less, you know, the way you do that, I think, is, you know, less charting, less documentation, you know, not hunting through information you can't find. And that's where nursing, that's a genuine promise. So pattern recognition across specific cohorts of patients. So as a nurse, even though I worked a lot of different places, in each place I worked, there was commonalities when I lived in West Virginia and I was an ER nurse in a super rural hospital. If I had had more information about my patients, their family, families, I could get an AI, could help me surface those patterns that exist for the people that I'm taking care of. I think I could get time back as a nurse. And if the nurse gets time back, then the patient and family gets the presence of the clinician. So that's the trade that I'm interested in. I want to go back to that thing about pain and fear. I want to add what I've learned working on the blue button. Plus I want to add cognition. So when you think about it, the data almost never captures the variability of pain, fear and cognition. And those things are really important because pain changes what you can do and what you can decide. Fear closes your heart, it closes your mind. And so when you're scared in a clinical encounter, you're not making good decisions, you're just saying yes to end it. And cognition is, you know, it varies. Like, I can absorb better at 10 in the morning on a good day compared to 3 o' clock in the afternoon when I'm spent. You know, you can extrapolate this to other people. They have their own particular patterns and circumstances. But I think what I'm trying to get at in all of this is it isn't first about the data, it's first about what? About life. And what about the things that are important to people, patients, caregivers, and the clinicians that they partner with and how can AI help them?

[Dr. Stephen Lapkoff]

So you've explained to me in the pre call that you're doing some of this work so maybe you can unpack a little bit about what it is you're actually doing with it and how it's helping or some cases not helping those efforts.

[Danny Van Leeuwen]

Well, what have I done? I. I've done different things. One of the things that, that I've done is to try to build my toolkit. You know, so when I say build my toolkit, I'm a, I'm a conglomeration of symptoms. I mean, you know, I'm, I'm not ms, I'm not my symptoms, but they're big and they're there. And I feel like I'm trying to figure out for anything that I have to deal with, whether it's any of the different kinds of pains I have, my, my anxiety, my bladder, you know, my mobility. I have challenges and I, I need a toolbox. I need a toolbox. And the way I think is I need at least three things that will work so that when they happen, I got something I can go do. And pretty much the most common thing is drink water. Drink water is by far the most successful intervention across all of my symptoms. It's kind of amazing. It's so cheap, so easy. It isn't the drugs. Okay, but so how do I do that? Well, for me, I've done that partially just in my head, partially. I've done that by keeping lists. Like, I keep track of the steps I take, I keep track of the amount of time I play music, I keep track of my falls, I keep track of my weight. And so I use digital tools to do that when I can. I also record my clinician visits.

[Dr. Stephen Lapkoff]

When you say record, you mean like audio record or.

[Danny Van Leeuwen]

Yeah, okay, yeah, audio record. Right. And until recently, I used a bridge, which is a company that.

[Dr. Stephen Lapkoff]

How did you get to use Abridge? I thought the bridge is only selling basically into doctor's offices from the clinician side.

[Danny Van Leeuwen]

So I was before that. Ah. And they started as a patient facing product and actually they sponsored my podcast for three years. So I was pre that.

[Dr. Stephen Lapkoff]

Okay.

[Danny Van Leeuwen]

So putting all that together. So I play with, you know, trying to put into Claude. There's nothing magic or special, you know, it's me playing, just trying stuff, you know, some of it, you know, my wife will say, hey, she sees a pattern. My kids will see a Pattern or

[Dr. Stephen Lapkoff]

give us an example of what this looks like. I mean, you're saying you're giving Claude or another LLM a series of symptoms or you're giving it a series of plus your day, like unpack it and let us know. Yeah, okay, so what system and how's it working for you?

[Danny Van Leeuwen]

I've done a couple of different things. One is, you know, I have a spreadsheet and I just put the spreadsheet in, you know, as a document or whatever you call it when you have a project and you know, you load. I load my spreadsheet, I keep an annual summary and I keep the year that I'm working on. And I will have fits of journaling. You know, this is not something that I am like super consistent on. But I'll. Especially when I'm struggling with something, if I'm struggling with my blood pressure or I'm struggling with my mood, I have a progressive mobility thing going on. And I'll put that in and I'll prompt. I'll say, can you. Do you see a pattern in this? You know, and I've gotten, you know,

[Dr. Stephen Lapkoff]

given you some insights. Is it like, give me an example of some of the insights it's actually given you that you didn't see yourself?

[Danny Van Leeuwen]

Well, I've gotten like. It's kind of humorous but. But I've gotten like, you know, have you thought about seeing a phys therapist? And I, I have, you know, I have a physical therapist that I don't go to very often. You know, my relationship with her is I go for a tune up but they'll. I want. It'll show. Like I'll do my sort of things are clearly I'm not walking as far. I fell on a few times, you know, and I'll get this suggestion, you know, I also. What else have I done? Oh, oh, um, once I had a medication that I was taking for neuropathy and I was. My mood had like changed considerably and you know, I got a thing on that might be a side effect, you know. Have you talked to your doctor about the LLM?

[Dr. Stephen Lapkoff]

You fed heroin and it suggested it was a side effect, which you didn't figure out.

[Danny Van Leeuwen]

I didn't. A neurologist said that he thought. He said it sounds like you have an allergy to it. And you know, he wanted it to be listed as an allergy because he thought it was very possible that he's had people that have had a problem.

[Dr. Stephen Lapkoff]

When you tell me that you've loaded your data, you give the LLM your Signs your symptoms, you give it your labs, you give it what's in the system, and it comes up with a recommendation that you hadn't thought. Now, you're a clinician, you're a nurse. You've been a nurse for many, many decades.

[Danny Van Leeuwen]

50 years.

[Dr. Stephen Lapkoff]

50 years. And does it surprise you that it comes up with stuff that you didn't see?

[Danny Van Leeuwen]

No, no, no, no. I mean, to me, you know,

[Dr. Stephen Lapkoff]

to be honest with you, if I did what you just said and it came up with something completely radical that I never thought of and it was right, yeah. I would be scratching my head and thinking, okay, that's. That's beyond interesting. I better pay more attention to this. And maybe I want to use it differently because not. It's not just use. Using it. Like people around everywhere are starting to use it for the same thing in the same exact way. So that is in the medical system, right?

[Danny Van Leeuwen]

It does. I mean, like, when I tell my neurologist, he laughs and he's like a whatever works kind of guy, you know, that he feels like he doesn't have all the answers and that he likes those stories. I feel like I've learned. I think you know Amy Price, right?

[Dr. Stephen Lapkoff]

Yeah, very well.

[Danny Van Leeuwen]

Yeah, we're buddies. And so one of the things that I've learned from her is how to query and how to be skeptical and how to ask questions from different angles from different perspectives. So that you. And that's why I think that's where the unexpected comes up.

[Dr. Stephen Lapkoff]

Well, you're describing something that we did at the conference. I don't know if you were in the room, in the working group that we did this on, but you're describing. And actually we're submitting a paper on it very shortly on AI literacy. And you didn't label it as such, but you're describing yourself as being AI literate and understanding how to use the tools. Most importantly, that we skeptical of the answers, how to interpret the information that's being presented to you, and that those are all components of literacy, of AI literacy specifically. One of the things I'm finding in my world is that painfully few people are indeed AI literate. Even the folks in IT departments in large life science companies or hospitals who even work in this space and think that they're good at it and are literate, sometimes are not. That has other implications, which are if people are taking on these really impressively powerful tools and they don't quite know how to use them as well as they should, and if they query them incorrectly. To your point earlier, about making good queries. The responses that come out may or may not be to point. And if patients use that information inappropriately because they didn't know how to ask the right questions to start with, that could have deep implications to the healthcare system.

[Danny Van Leeuwen]

You could say that same thing about doctors.

[Dr. Stephen Lapkoff]

I will say it about doctors, not

[Danny Van Leeuwen]

about AI, about the advice that doctors give. There's a tremendous variation, and it is very different. When I am feeling good enough to be organized and to be directive in the conversation with the clinician, I get a very different output than when I'm not. And I still have to be skeptical of what doctors tell me. And until I build some trust and. And then I, you know, then there's just too many decisions to make. When you're a person with chronic illness, it's like putting in a kitchen. There's so many decisions to make. And I'm happy for the doctors that I trust to make the decisions for me. But there are certain decisions I don't want to give to the doctor or to AI Like, I don't want to mess with my pathological optimism. I want to progress as slowly as possible, and I want to keep playing my horn. These are really important things to me, and I don't give those decisions that affect that. I don't give up. But all the rest of it, I do. And I've worked really hard to build the team that I have that appreciates me and my strangeness and my assertiveness, and they're not threatened by it.

[Dr. Stephen Lapkoff]

Is your team AI Literate? Do they also use these same tools in your care?

[Danny Van Leeuwen]

I don't know. I mean, AI Literate is huge. I mean, that's just such a big, big thing. Do they use AI? Yes. Do I know how they use AI? Well, you know, they use what's attached to epic. I know that. I mean, look, my neurologist, who I just love, he thinks like, he uses the portal well, because he just keeps adding things to the end of the A note. And so he feels like, well, I don't find his notes at all useful. And I tell him that. I tell him what I really want to know is, how am I doing? Am I getting better? Am I getting worse? Am I stable? What should I be paying attention to in the next six months till I see you again? And I can't find that in his note. Now, on the other hand, I've taken his note and asked Claude and say, here's the note. How am I doing? You know, have I progressed? How is he measuring it? Oh, well, then I find he's using this scale, right? And it'll come up with looking through this note, which is like 10 years running, and it'll find. I can't remember the name of it, but there's a scale that he uses. And then we'll go back and I'll say to him, oh, you're using this scale? And he goes, yeah. And I said, well, why don't you like put that at the top of your note, you know, so that I can find it, you know, so we have that kind of conversation that AI has helped.

[Dr. Stephen Lapkoff]

Well, that's actually an interesting perspective that AI is helping to reorganize things is one of the use cases that has been discussed at length actually, and was discussed at our conference is using AI to digest medical records. And when I say digest, it's not about like ingesting them, which is slightly different, but digesting, which means find all the different pieces, put them together, come up with a narrative that summarizes perhaps 300 pages of information, which may be sparse and may be poorly organized, and bring it all together. And that's actually a task that AI is actually turning out to be pretty darn good at. And that again, changes the nature of the healthcare system and the healthcare journey.

[Danny Van Leeuwen]

And it does a fair job. You say it's really good at it. It's better than I could do.

[Dr. Stephen Lapkoff]

It's better than I.

[Danny Van Leeuwen]

Yes, well, you're not. First of all, that's not your training and you don't have the time for it. And you still have to review it.

[Dr. Stephen Lapkoff]

Yeah, of course.

[Danny Van Leeuwen]

Because I have never used AI that gave me a, oh, this is great. I mean, the first time I read it, pretty much every time, I think it's amazing. And then, you know, my rule is sleep on it and check it again. And then it's like, oh, my God, this. First of all, it either just said nothing very fancy or it got some very basic things wrong. And then I'll say, oh, you know, you missed this and you missed that, and it'll go, oh, you're right, I did.

[Dr. Stephen Lapkoff]

Well, that also speaks to the concept of keeping a human in the loop, which is something that you espouse and many folks in the healthcare AI world do espouse, ironically. You know, Adam Rodman, I think he was at our conference, he spoke, he's done a study which shows actually having a human in the loop in some cases actually makes the conclusions worse, believe it or not, which is a non intuitive finding. You would think that the two together would be better than either one alone. But so that's now relatively. It's not even that new anymore. That information came out about a year ago. So we got to start wrapping up in a few minutes here. So, you know, we didn't cover the concept around outcomes, around your three T's and two C's. Maybe we can cover that in the last bit here and then we can get to closing.

[Danny Van Leeuwen]

Okay, so I feel like one of the questions that you've asked is how AI helped, right? And so what I need to tell you is the framework that I've developed over the years, which I've actually shared in my AI Claude project, that's Danny's Health, what I call the three T's and the two C's. And this is like the framework I use to evaluate any digital health technology. And so they are time, trust, talk, control, and connection. What I mean by that is time is, you know, you need time to learn to plan, to talk, to build trust. So I say the clock isn't the enemy. It's the wrong things filling the time. So the time, the second is trust. You know, trust can take a really long time. It can happen really quickly. Sometimes you never have it, and you know in your gut when you don't have it. And most digital health tools, AI, have a trust deficit, I think not because they're untrustworthy, which maybe they are, but it's really because the people who use them, use the tools, don't trust them. I think it's really important. You can't shortcut trust in the use of any tool. I think talk is really important. It's woven through all of it, real conversation. There is nothing like actual conversation that is making decisions together, which is a lot of what healthcare is about, is making decisions. AI can help you prepare for it, and it can help process it, and then control. I trust more when I have power in a situation. So if I'm feeling like an ant ready to be crushed, I'm not making good decisions. And finally, I would say connection is. It's the human lifeline. You know, when somebody greets you, when you cross a threshold, that's a connection. When someone's been where you're going and they can say, oh, that helped me. AI can extend that connection. They can help people find communities. They're available at 3 in the morning, but you can't manufacture it. I think that connection is really important. So that's where I, you know, time, talk, trust, control and connection. And I use that framework when I'm Evaluating.

[Dr. Stephen Lapkoff]

And that framework gives you a better, you know, how do I say this right? It gives you a. Like a rubric, if you will, to go through the information that's coming out of it. Danny, we're going to have to wrap up here in a second. Are there any last comments you want to make that. That will, you know, help other patients in the. In the space in terms of how they might want to think about adopting an AI tool in their world?

[Danny Van Leeuwen]

I think that I would say use it. Use AI, Keep using it, experiment with it. That. That just like anything else, it takes time to learn. It takes time to be comfortable with it. Use it. I would say advocate for humans in the loop. I don't care what the study says. It's about humans. We are human. Keep it. Humans in the loop. I would say find a buddy, you know, do this with somebody else. Find a buddy and experiment. I would say, yeah, talk to your clinician about it. It's a good barometer of a physician. If they don't want to talk or blow you off, that tells you something.

[Dr. Stephen Lapkoff]

Absolutely right.

[Danny Van Leeuwen]

And I would say, if you're comfortable with it, mentor, you know, be the buddy. And for clinicians and for systems and developers, I would say you need to have patients, caregivers, and practicing partner clinicians in the design. They need to be there from the beginning, and, you know, so it solves the problems people have, not the problems that the developers think are there or the venture capitalists thinks are going to make money. Money, you know, and if you have an opportunity, join, you know, participate.

[Dr. Stephen Lapkoff]

All good advice. Well, Danny, I want to thank you very much for your participation in today's discussion. Hopefully that there are other patients out there who listen to the podcast. They'll take something away for the clinicians out there who are listening. You know, you've heard it straight out from a patient who happens to be a healthcare provider himself, and he's got very strong perspectives on how this can be used in a positive and productive way. And I think the framework that he's put together is very useful. Danny, I want to just say thank you for all the help that you've provided helping this podcast get off the ground. That's been really incredibly generous of you and your friends who have helped us a lot. And a lot of the things that have happened on our podcast for improvement's sake have come directly from those conversations. So thank you for that. I want to thank you for being a guest and sharing your journey and sharing your experiences here and for the rest of us. I'm going to say thank you for joining us and we will see you again next time on another episode of Practical AI in Healthcare. Thank you for listening.

[Podcast Host / Narrator]

Thank you for joining us this week on Practical AI In Healthcare. If you're ready to go beyond buzzwords and hype and explore how AI is truly transforming healthcare, stay tuned for more conversations that get us to what works. Until next time, stay practical.

[Dr. Stephen Lapkoff]

It.