Brandon Tang
@drbrandontang.bsky.social
General Internist and Assistant Professor at University of Toronto | Med Ed at Harvard Medical School | TEDx Speaker | Editor in Chief, Vancouver Notes: https://brusheducation.ca/brush-catalogue/p/vancouver-notes-for-internal-medicine
#MedEd #BigData
#MedEd #BigData
The #GEMINIMedED team aims to leverage ‘big data’ to help answer these important questions #MedEd
More on our program of research here: harvardmacy.org/blog/data-dr...
@harvardmacy.bsky.social @uoftmedicine.bsky.social
4/4
More on our program of research here: harvardmacy.org/blog/data-dr...
@harvardmacy.bsky.social @uoftmedicine.bsky.social
4/4
Harvard Macy Institute - Blog - Shaping the Future of Medical Education through Data-Driven Learning
harvardmacy.org
December 20, 2024 at 7:17 PM
The #GEMINIMedED team aims to leverage ‘big data’ to help answer these important questions #MedEd
More on our program of research here: harvardmacy.org/blog/data-dr...
@harvardmacy.bsky.social @uoftmedicine.bsky.social
4/4
More on our program of research here: harvardmacy.org/blog/data-dr...
@harvardmacy.bsky.social @uoftmedicine.bsky.social
4/4
Some residents admitted 3 times as many patients with pneumonia than their peers
Most differences persisted when controlling for time
- What does this mean for readiness for unsupervised practice?
- Should and how could we account for this variation in educational design?
3/
Most differences persisted when controlling for time
- What does this mean for readiness for unsupervised practice?
- Should and how could we account for this variation in educational design?
3/
December 20, 2024 at 7:17 PM
Some residents admitted 3 times as many patients with pneumonia than their peers
Most differences persisted when controlling for time
- What does this mean for readiness for unsupervised practice?
- Should and how could we account for this variation in educational design?
3/
Most differences persisted when controlling for time
- What does this mean for readiness for unsupervised practice?
- Should and how could we account for this variation in educational design?
3/
Methods: Over a 10-year period (2010-19), we linked senior IM residents to the patients they cared for during overnight call
Then we measured case exposure variables across 6 domains (eg volumes, acuity)
We observed large differences in resident experiences
2/
Then we measured case exposure variables across 6 domains (eg volumes, acuity)
We observed large differences in resident experiences
2/
December 20, 2024 at 7:17 PM
Methods: Over a 10-year period (2010-19), we linked senior IM residents to the patients they cared for during overnight call
Then we measured case exposure variables across 6 domains (eg volumes, acuity)
We observed large differences in resident experiences
2/
Then we measured case exposure variables across 6 domains (eg volumes, acuity)
We observed large differences in resident experiences
2/
I’m a huge sports fan and envision that physician training #MedEd can one day incorporate analytics in the same way they do in professional sports
I’m coming from *other* social media platforms in search of bluer skies @bsky.app #BlueSky
pubmed.ncbi.nlm.nih.gov/38109661/
I’m coming from *other* social media platforms in search of bluer skies @bsky.app #BlueSky
pubmed.ncbi.nlm.nih.gov/38109661/
Finding Medicine's Moneyball: How Lessons From Major League Baseball Can Advance Assessment in Precision Education - PubMed
Precision education (PE) leverages longitudinal data and analytics to tailor educational interventions to improve patient, learner, and system-level outcomes. At present, few programs in medical educa...
pubmed.ncbi.nlm.nih.gov
December 12, 2024 at 9:42 PM
I’m a huge sports fan and envision that physician training #MedEd can one day incorporate analytics in the same way they do in professional sports
I’m coming from *other* social media platforms in search of bluer skies @bsky.app #BlueSky
pubmed.ncbi.nlm.nih.gov/38109661/
I’m coming from *other* social media platforms in search of bluer skies @bsky.app #BlueSky
pubmed.ncbi.nlm.nih.gov/38109661/