1/ Is it possible for a machine-learning clinical intervention to align patient preferences and spending reductions?
In @NEJM_AI, we report on one of the first economic evaluations of a ML-based intervention as part of a prospective trial.
Link: https://t.co/4A6Aiwk8Ds
Imagine 4 new anticancer drugs Pallituzumab, Geriatriximab, Symptomab, & Exercizumab hit the market. They should dominate the plenary sessions at ASCO & command billion-dollar revenue. But they don't because they're nonpharmacologic & shame on us.
Read our opinion piece in @JCO_ASCO
https://t.co/UFuxuDI3sn
Radiation oncologists are trained to deliver safe, high-precision radiotherapy as part of a #cancer care team. We follow the best available evidence & develop customized, cost-effective plans. Science guides our treatments, but humanity guides our practice. 1/2
The @HAClab_ has a Marshall Scholar in the house! Congratulations to @TejAPatel_, who has contributed to research around #AI policy, economic analyses of #AI impact, and #oncology alternative payment models.
Big congrats to Tej Patel on being named a #MarshallScholar! From research in top journals to founding a think tank tackling health equity & policy, Tej is now heading to the UK for fully funded graduate study. Future MD/MPP in the making! @vfung10 https://t.co/IRAmfJ9Gdw
Elated to announce that I was named a Marshall Scholar this past November! Looking forward to extending my passions in healthcare, policy, and AI at the @UniofOxford, where I hope to pursue Masters in Global Health Science & Applied Digital Health!
https://t.co/3UyoQsMp4H
Delighted to announce today the 2025 @MarshallScholar winners!
This incredible group of future American leaders will travel to the UK next year to study at many of the UK’s top universities. Congratulations!
“Start low, go slow,” a strategy to tailor treatment dosing in older or vulnerable adults with advanced solid cancer: A systematic review and meta-analysis led by @PennCancer fellow @chefaleixomd in @JGeriOnc
https://t.co/Lxal4L4FBI
In their new Forefront article, @TejAPatel_, @BhavJain_, + @KedarMate from @Penn, @StanfordMed, + @TheIHI discuss how CMMI can encourage better practices by launching cycles of testing and learning that seek to evaluate optional extensions of APMs. https://t.co/H9uuVIAeqX
Excited to share our latest in @Health_Affairs! We discuss how an improvement science framework that emphasizes continuous revision can change the way we construct value-based payment models. Honored to collaborate with @BhavJain_ and @KedarMate on this!
In their new Forefront article, @TejAPatel_, @BhavJain_, + @KedarMate from @Penn, @StanfordMed, + @TheIHI discuss how CMMI can encourage better practices by launching cycles of testing and learning that seek to evaluate optional extensions of APMs. https://t.co/H9uuVIAeqX
Published open-access today in @BMJOncology a very important paper describing the cancer burden in SAARC region consisting of 8 LMICs in South Asia contributing to a quarter of the world population. Super proud of @EChrisDee@Urvish_Jain1 and team for taking this project past the finish line.
Also, proud of our team. We wanted to do #globaloncology the right way by collaborating with colleagues from each country who also contributed as coauthors. You’ll see that our authorship team has colleagues who are from or have worked in all these 8 countries (only Maldives is missing in affiliation but some of our colleagues have worked in oncology in Maldives). Our colleagues’ local experience was paramount to put our data into perspective.
https://t.co/tyC4fq6r1y
Can we TALK about this truly phenomenal group of trainees, each with an #ASCO24 poster and/or oral presentation? Their work highlights important equity gaps in vulnerable populations. Their passion about improving cancer care is clear.
The future of oncology is BRIGHT. 😎
A machine learning intervention for serious illness conversations saved over $13 million for patients with cancer by reducing end-of-life therapy and outpatient costs. Read the full study results by @TejAPatel_ et al.: https://t.co/r2At56NFoF
7/ Be on the lookout for more real-world evaluations of AI-based interventions coming out of @HACLab_UPenn! Grateful to @ravi_b_parikh, @PC3Innovation, @PennMedicine, and co-authors for their unwavering support and mentorship!
1/ Is it possible for a machine-learning clinical intervention to align patient preferences and spending reductions?
In @NEJM_AI, we report on one of the first economic evaluations of a ML-based intervention as part of a prospective trial.
Link: https://t.co/4A6Aiwk8Ds
6/ While better conversations and not cost savings was our goal, we hope that studies like these can align patients, health systems, and payers to pursue responsible use of ML when it's indicated!