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Feb 18, 2015 · 25m · mad

Ron Gutman, HealthTap // On-Demand Medical Care // Data Driven NYC (FirstMark Capital)

Ron Gutman · 20m spoken Matt Turck · 2m spoken
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At Data Driven NYC, HealthTap founder Ron Gutman joins host Matt Turck to discuss how HealthTap leverages mobile technology, machine learning, and intuitive design to deliver on-demand digital healthcare and empower physicians.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 13.1% of the talking time here. How this is scored →

Matt as informed peer 3.4 Guest teaching 2.8 Guest disagreement 1.4 Matt pushing back 3.0
05100:0010:0020:003:29–6:46 · Matt as informed peer 1/10 Overview of HealthTap's End-to-End Digital Healthcare Platform The host opens with a broad prompt asking what HealthTap does. Ron delivers a length overview of HealthTap's end-to-end platform and doctor network without host interruption.6:46–10:18 · Matt as informed peer 4/10 Patient Privacy, Machine Learning, and Contextual Personalization Matt probes into the risks of trusting machine learning for patient data routing in high-stakes healthcare scenarios. Ron clarifies that ML only handles attribute matching while doctors review and answer everything.10:18–15:34 · Matt as informed peer 6/10 Triage Capabilities and Physicians as Future Data Scientists Matt quotes investor Vinod Khosla's prediction that software and AI will replace 80 percent of doctors' diagnostic and prescription work. Ron responds by reframing the future role of physicians as data scientists using decision support systems.15:34–21:33 · Matt as informed peer 5/10 Enhancing Physician Interfaces and Overcoming Technology Resistance Matt pushes back on Ron's optimistic view by citing historical rejections of evidence-based medical decision support systems by doctors. Ron counters by emphasizing user experience design and noting how critics previously doubted doctors would answer online questions for free.21:33–25:19 · Matt as informed peer 1/10 Audience Q&A: Integrating Wearables and Implicit Contextual Data Matt moderates an audience Q&A session where an audience member asks about wearable device integrations. Ron explains how implicit browsing data and explicit wearable metrics combine to provide contextual intelligence for doctors.3:29–6:46 · Guest teaching 2/10 Overview of HealthTap's End-to-End Digital Healthcare Platform The host opens with a broad prompt asking what HealthTap does. Ron delivers a length overview of HealthTap's end-to-end platform and doctor network without host interruption.6:46–10:18 · Guest teaching 3/10 Patient Privacy, Machine Learning, and Contextual Personalization Matt probes into the risks of trusting machine learning for patient data routing in high-stakes healthcare scenarios. Ron clarifies that ML only handles attribute matching while doctors review and answer everything.10:18–15:34 · Guest teaching 4/10 Triage Capabilities and Physicians as Future Data Scientists Matt quotes investor Vinod Khosla's prediction that software and AI will replace 80 percent of doctors' diagnostic and prescription work. Ron responds by reframing the future role of physicians as data scientists using decision support systems.15:34–21:33 · Guest teaching 3/10 Enhancing Physician Interfaces and Overcoming Technology Resistance Matt pushes back on Ron's optimistic view by citing historical rejections of evidence-based medical decision support systems by doctors. Ron counters by emphasizing user experience design and noting how critics previously doubted doctors would answer online questions for free.21:33–25:19 · Guest teaching 2/10 Audience Q&A: Integrating Wearables and Implicit Contextual Data Matt moderates an audience Q&A session where an audience member asks about wearable device integrations. Ron explains how implicit browsing data and explicit wearable metrics combine to provide contextual intelligence for doctors.3:29–6:46 · Guest disagreement 1/10 Overview of HealthTap's End-to-End Digital Healthcare Platform The host opens with a broad prompt asking what HealthTap does. Ron delivers a length overview of HealthTap's end-to-end platform and doctor network without host interruption.6:46–10:18 · Guest disagreement 1/10 Patient Privacy, Machine Learning, and Contextual Personalization Matt probes into the risks of trusting machine learning for patient data routing in high-stakes healthcare scenarios. Ron clarifies that ML only handles attribute matching while doctors review and answer everything.10:18–15:34 · Guest disagreement 2/10 Triage Capabilities and Physicians as Future Data Scientists Matt quotes investor Vinod Khosla's prediction that software and AI will replace 80 percent of doctors' diagnostic and prescription work. Ron responds by reframing the future role of physicians as data scientists using decision support systems.15:34–21:33 · Guest disagreement 2/10 Enhancing Physician Interfaces and Overcoming Technology Resistance Matt pushes back on Ron's optimistic view by citing historical rejections of evidence-based medical decision support systems by doctors. Ron counters by emphasizing user experience design and noting how critics previously doubted doctors would answer online questions for free.21:33–25:19 · Guest disagreement 1/10 Audience Q&A: Integrating Wearables and Implicit Contextual Data Matt moderates an audience Q&A session where an audience member asks about wearable device integrations. Ron explains how implicit browsing data and explicit wearable metrics combine to provide contextual intelligence for doctors.3:29–6:46 · Matt pushing back 0/10 Overview of HealthTap's End-to-End Digital Healthcare Platform The host opens with a broad prompt asking what HealthTap does. Ron delivers a length overview of HealthTap's end-to-end platform and doctor network without host interruption.6:46–10:18 · Matt pushing back 5/10 Patient Privacy, Machine Learning, and Contextual Personalization Matt probes into the risks of trusting machine learning for patient data routing in high-stakes healthcare scenarios. Ron clarifies that ML only handles attribute matching while doctors review and answer everything.10:18–15:34 · Matt pushing back 4/10 Triage Capabilities and Physicians as Future Data Scientists Matt quotes investor Vinod Khosla's prediction that software and AI will replace 80 percent of doctors' diagnostic and prescription work. Ron responds by reframing the future role of physicians as data scientists using decision support systems.15:34–21:33 · Matt pushing back 6/10 Enhancing Physician Interfaces and Overcoming Technology Resistance Matt pushes back on Ron's optimistic view by citing historical rejections of evidence-based medical decision support systems by doctors. Ron counters by emphasizing user experience design and noting how critics previously doubted doctors would answer online questions for free.21:33–25:19 · Matt pushing back 0/10 Audience Q&A: Integrating Wearables and Implicit Contextual Data Matt moderates an audience Q&A session where an audience member asks about wearable device integrations. Ron explains how implicit browsing data and explicit wearable metrics combine to provide contextual intelligence for doctors.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 12.2% · guest 87.8%0:00 · Matt 12.2% · guest 87.8%3:00 · Matt 1.4% · guest 98.6%3:00 · Matt 1.4% · guest 98.6%6:00 · Matt 20.8% · guest 79.2%6:00 · Matt 20.8% · guest 79.2%9:00 · Matt 14.1% · guest 85.9%9:00 · Matt 14.1% · guest 85.9%12:00 · Matt 18% · guest 82%12:00 · Matt 18% · guest 82%15:00 · Matt 24.6% · guest 75.4%15:00 · Matt 24.6% · guest 75.4%18:00 · Matt 0% · guest 100%18:00 · Matt 0% · guest 100%21:00 · Matt 17.2% · guest 82.8%21:00 · Matt 17.2% · guest 82.8%24:00 · Matt 5.3% · guest 94.7%24:00 · Matt 5.3% · guest 94.7%
Sharpest disagreement ▶ 15:55 Reframing physician technology resistance

Ron dismisses skeptical claims about doctor tech adoption by pointing out how critics wrongly predicted doctors would never answer patient questions online for free.

 Hardest push from Matt ▶ 15:34 Host challenges doctor adoption history

Matt challenges Ron's vision of doctors as data scientists by raising the historical failure of clinical decision support systems due to physician rejection.

 Biggest teaching moment ▶ 8:56 Clarifying machine learning limits in clinical care

Ron corrects the host's assumption that machine learning makes autonomous care decisions, clarifying that human doctors author and review 100 percent of medical content.

 Matt holds his own ▶ 11:59 Citing Vinod Khosla's thesis on AI disrupting healthcare

Matt demonstrates deep industry knowledge by citing investor Vinod Khosla's specific prediction about AI automating 80 percent of physician diagnostic work.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Overview of HealthTap's End-to-End Digital Healthcare Platform 1210 The host opens with a broad prompt asking what HealthTap does. Ron delivers a length overview of HealthTap's end-to-end platform and doctor network without host interruption.
Patient Privacy, Machine Learning, and Contextual Personalization 4315 Matt probes into the risks of trusting machine learning for patient data routing in high-stakes healthcare scenarios. Ron clarifies that ML only handles attribute matching while doctors review and answer everything.
Triage Capabilities and Physicians as Future Data Scientists 6424 Matt quotes investor Vinod Khosla's prediction that software and AI will replace 80 percent of doctors' diagnostic and prescription work. Ron responds by reframing the future role of physicians as data scientists using decision support systems.
Enhancing Physician Interfaces and Overcoming Technology Resistance 5326 Matt pushes back on Ron's optimistic view by citing historical rejections of evidence-based medical decision support systems by doctors. Ron counters by emphasizing user experience design and noting how critics previously doubted doctors would answer online questions for free.
Audience Q&A: Integrating Wearables and Implicit Contextual Data 1210 Matt moderates an audience Q&A session where an audience member asks about wearable device integrations. Ron explains how implicit browsing data and explicit wearable metrics combine to provide contextual intelligence for doctors.

Statements from this episode (9)

Assertion Partly supported
Gutman: Over 50% of patients do not take prescribed treatments or medications
“Ah, more than 50% of people that get a certain treatment or a certain medication, whatever it is, actually don't take it.”
Ron Gutman Feb 18, 2015 ▶ 1:24
Assertion Not checkable as stated
HealthTap network includes over 66,000 licensed U.S. physicians
“We have a network with more than 66,000 physicians, ah, U.S. Licensed physicians in good standing”
Ron Gutman Feb 18, 2015 ▶ 3:48
Assertion Not checkable as stated
HealthTap has served over 2.6 billion doctor answers
“We serve more than 2.6 billion doctor answers to date.”
Ron Gutman Feb 18, 2015 ▶ 3:59
Disclosure
Gutman: HealthTap patients are always anonymous
“So first of all, patients on HealthTap are always anonymous,”
Ron Gutman Feb 18, 2015 ▶ 7:13
Assertion Not checkable as stated
Gutman: 100% of HealthTap content is doctor-created and peer-reviewed
“Always, a hundred percent of HealthTap, all answers, tips, news, app reviews are created by doctors and reviewed by other doctors.”
Ron Gutman Feb 18, 2015 ▶ 8:56
Assertion Contradicted
Gutman: 74% of nighttime ER visits are unnecessary
“74% of people that go to ERs at night don't need to be there.”
Ron Gutman Feb 18, 2015 ▶ 11:46
Prediction Not checkable as stated
Gutman predicts doctors will increasingly become data scientists
“I think that in the foreseeable future, we will see doctors becoming more and more data scientists.”
Ron Gutman Feb 18, 2015 ▶ 12:38
What-if
HealthTap could have been profitable in 2014 by serving ads
“HealthUp, HealthUp could have been profitable more than a year ago by serving ads on the pages, which was everyone, when we were on University Avenue in Palo Alto, and everyone around us is doing ads, right, so it's like the easiest thing in the world, turn it…”
Ron Gutman Feb 18, 2015 ▶ 17:54
Insight
Contextual data helps physicians identify depression hiding behind physical pain complaints
“Sometimes patients come and complain about pain, but what they really are talking about is depression. And if you had some context about where they're coming from, you would not look for the source of pain, you would look for why they're depressed.”
Ron Gutman Feb 18, 2015 ▶ 22:56
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