Ron Li
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Building new tech-enabled care models within a health system

AI and virtual care are the building blocks for the next generation of care models and health systems can lead in this transformation. I’m often struck by how little the fundamental architecture of care has changed in over a century — we still ask patients to come see a doctor in a clinic when they have a problem, and in hospitals, we still round room to room much as we did a hundred years ago. The Covid pandemic accelerated digital modalities such as telehealth, but the underlying ar…

Reposts 0 2d

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What if we had to care for twice as many people at half the cost?

Scarcity-driven thinking may be what is needed to unlock needed innovation. Scarcity-driven thinking may be what is needed to unlock needed innovation.

Reposts 0 Jan 18

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When AI outshines doctors

AI might be becoming better than doctors at diagnostic reasoning. What now? In 2009, Charles Friedman proposed a “Fundamental Theorem of Informatics” that stated “A person working in partnership with an information resource is ‘better’ than that same person unassisted.” This was the underlying principle for the value of informatics in medicine: clinicians armed with the right data driven tools will always be better at taking o…

Reposts 0 Nov 23

Substack
Empowering individual health systems to validate AI models

Few would have expected Epic to be a first mover in the decentralization and democratization of AI in healthcare. Epic recently announced an open source “AI trust and assurance software suite” that health systems can use to validate and monitor ML models integrated into the EHR. This tool automates the most time-consuming and replicable steps of model validation, such as collecting, aggregating, and mapping data and metrics. By streamlining these processes, it en…

Reposts 0 Jun 2

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Monthly Roundup: Summarizing clinical information with LLMs, digital care models bypassing traditional healthcare providers, user centered design for designing AI tools

Takeaways from articles about research, case study spotlights, and industry trends Large language models perform better than medical experts in summarizing clinical information

Reposts 0 Mar 7

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Monthly Roundup: ChatGPT and CDS, virtual specialty care and payers, unified financial platforms

Takeaways from articles about research, case study spotlights, and industry trends this month. Takeaways from articles about research, case study spotlights, and industry trends this month.

Reposts 0 Jul 5

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Monthly roundup: price transparency integration, large language model pilots, explainable AI for clinicians

Takeaways from articles about research, case study spotlights, and industry trends this month. Takeaways from articles about research, case study spotlights, and industry trends this month.

Reposts 0 May 27

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AI and physicians as “thought partners” with large language models

Our work in medicine is driven by narratives.

Reposts 0 Feb 15

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Clinical trials matching: how the Epic EHR is becoming a platform

Epic is ramping up its platform play.

Reposts 0 Sep 27

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AI and physicians as “thought partners”: a use case in endoscopic colorectal cancer screening

“Integrating AI into clinical practice” has been the holy grail in the field of AI in healthcare. With ML models becoming increasingly ubiquitous and accurate, solving the “integration” problem would substantially move the field forward towards real impact on patient care. But what does “integration” truly entail?

Reposts 0 Aug 20

Substack
AI enabling new workflows to expand access to care (part 1)

Originally published on 4/25/2022 on byte2bedside.com Examples of AI in healthcare typically involve machine learning (ML) models that can perform the same task a human expert performs manually (eg. diagnosing pneumonia on a chest X-ray). The hope is that these systems can be useful for augmenting (or even replacing) existing workflows for clinicians, but more or less preserve the same structure and approach towards diagnosing and treating disease.

Reposts 0 Apr 25

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How electronic health record systems are becoming healthcare platforms

Two seemingly unrelated headlines caught my attention recently: one is the widely discussed Oracle acquisition of Cerner, and the other is an article in NPJ Digital Medicine describing key challenges and opportunities for leveraging the electronic health record (EHR) to enhance the

Reposts 0 Dec 21

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Remote patient monitoring: a technology or a care model?

I recently came across a nice publication describing an example of a real world implementation of remote patient monitoring (RPM) for patients with Covid-19 at the Mayo Clinic. There are a few aspects of this paper that I particularly liked that I will discuss, but it also led me to think about a more fundamental ques…

Reposts 0 Aug 19

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“API-Fying” healthcare services

*Reposted* — originally published on 7/12/2021 on byte2bedside.com

Reposts 0 Jul 12

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What can the history of cloud computing teach us about the future of AI?

*Reposted* — originally published on 4/21/2021 on byte2bedside.com There is much excitement about AI in healthcare, but we still don’t quite understand how it can produce impact at a meaningful scale. Discussions about AI often jump to examples of machine learning (ML) models that perform eye catching tasks such as interpreting X-rays and diagnosing disease. However, although there is no shortage of published papers describing highly accurate ML models that predict all sorts of clinical outcomes, there is a dearth of actual AI products that are widely adopted and deliver value.

Reposts 0 Apr 21

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Innovation is greater than the sum of its parts

Why we probably don't yet see the true innovative potential of AI in healthcare Why we probably don't yet see the true innovative potential of AI in healthcare

Reposts 0 Feb 11