“Injustice anywhere is a threat to justice everywhere. We are caught in an inescapable network of mutuality, tied in a single garment of destiny. Whatever affects one directly, affects all indirectly” - Rev Martin Luther King Jr (1963)
Make a Bond movie MD-PhD: From NIH With Love
📄 paper: academic.oup.com/jamiaopen/ar...
study made possible by the
@UWEmerMed
&
@uwisye
team
big credit to first author Dann Hekman!
#AIinMedicine #NLP #EHR #Falls #HealthcareAI #JAMIAOpen
when we build algorithms on top of these phenotypes, we risk baking in these issues
your cohort definition is your ground truth. if you get that wrong, everything downstream is shaky
its not just about falls
it's a broader reminder about phenotyping: diagnosis codes are easy to extract, but they're often shaped by documentation shortcuts, billing practices, and workflow quirks
the patients missed by ICD codes?
they were sicker, higher comorbidity scores, higher 30-day mortality, and more likely to have a medical illness (like sepsis or AKI) as the cause of their fall
🚨 new JAMIA Open paper on how we define a “fall” in the ED using EHR data
our team ran an NLP algorithm over 50k+ ED provider notes and compared results to diagnosis code-based definitions
nearly half of the falls found by NLP weren’t captured by codes at all 🧵
finally, our findings aren't limited to CDI or infection prevention, it’s foundational work on how we design, implement, and evaluate AI tools that operate inside the hospital.
it’s a blueprint for making clinical AI actually safe & effective
#AIinMedicine #HealthIT #CDI #AI
this was a big, collaborative effort involving physicians, pharmacists, engineers, administrators, and analysts
healthcare AI work takes a village
we didn’t just evaluate performance metrics, we studied implementation:
✔️ usability
✔️ fidelity
✔️ provider perceptions
✔️ engagement across roles
this work builds on our prior studies on both prospective model validation & clinical implementation
while alerts to physicians (via BPAs) weren’t always acted upon, pharmacists did engage.
→ medication reviews led to meaningful de-escalation of high-risk antibiotics and PPIs 💊
→ another win for pharmacist-driven stewardship interventions 🔥
pharmacists really are awesome!
our system was used to flag patients at high risk for CDI, triggering a bundle of interventions:
🧼 enhanced hand hygiene
📋 best-practice advisories (BPAs) for providers
💊 pharmacist-led de-escalation of antibiotics & acid suppression
🍦 yogurt recommendations (yes, really)
we developed a machine learning model to predict CDI risk in hospitalized patients, implemented it into instance of
@hey.epic.com (EHR), and used the outputs to implement a multi-component infection prevention bundle — think of it like AI-powered stewardship
🚨💻🦠💩
our AI-guided system for C. difficile infection (CDI)
prevention study is now live in
@jamanetworkopen.com
new research by: @umichmedicalschool.bsky.social
jamanetwork.com/journals/jam...
🧵 key takeaways from developing + evaluating this real-world hospital AI implementation:
@doximity.bsky.social what’s up with your AI scribe? the promo materials make me want to try it out!
you mean so much to me #ai #valentines
kiddo: i can count to 0
me: go for it
kiddo: oneee
me: 🤪
“The Dishwasher Loading Task (DLT) is one uniquely suited for the skills and intellect of human beings. For this reason Singh et al. have suggested replacing the Turing test with the DLT as the ultimate arbiter of AGI.”
LLMs, despite immense potential, fail at basic reasoning tasks like loading the dishwasher.
it doesn’t make sense to have a single threshold for AGI. human intelligence is wide, varied, & unassured. why should AI be any different?
instead of an fixating on arbitrary definition, we could focus on understanding & improving performance across spectra of useful tasks
“one often hears a commentator call out, in hope, for the arrival of someone to serve as ‘the Newton of the mind.’ … the hoped-for Newton has already come and, alas, already gone. His name is John von Neumann”
youtube.com/shorts/IJQTM...
is the only difference between “gestalt” and “unexplainable machine learning” the involvement of humans?
wah wah waaAaAAaawwWw
hello, world!