This post was originally published on The Health Care Blog by Shiv Gaglani, Ryan Haynes, and Dr. Michael Painter.
Earlier this month Shiv and Ryan published a piece in the Annals of Internal Medicine
, entitled What Can Medical Education Learn from Facebook and Netflix?
We chose the title because, as medical students, we realized the tools our classmates are using to socialize and watch TV use more sophisticated algorithms than the tools we use to learn medicine.
What if the same mechanisms that Facebook and Netflix use—such as machine learning-based recommender systems, crowdsourcing, and intuitive interfaces—could transform how we educate our health care professionals?
For example, just as Amazon recommends products based on other items that customers have bought, we believe that supplementary resources such as questions, videos, images, mnemonics, references, and even real-life patient cases could be automatically recommended based on what students and professionals are learning in the classroom or seeing in the clinic.
That is one of the premises behind Osmosis
, the flagship educational platform of Knowledge Diffusion, Shiv’s and Ryan’s startup. Osmosis uses data analytics and machine learning to deliver the best medical content to those trying to learn it, as efficiently as possible for the learner.
Since its launch in August, Osmosis has delivered over two million questions to more than 10,000 medical students around the world using a novel push notification system that syncs to student curricular schedules.
Osmosis is aggregating medical school curricula and extracurricular resources as well as generating a tremendous amount of data on student performance. The program uses adaptive algorithms and an intuitive interface to provide the best, most useful customized content to those trying to learn.
However, as Ryan and Shiv conclude in their Annals article, data can only take us so far. Anyone who has received a baffling Netflix or Amazon recommendation can likely relate to that problem. Ultimately Osmosis will need an even larger database of curated and validated open educational resources (OER) to create a truly useful health education platform, for both clinicians and patients.
To help take this work to the next level, Robert Wood Johnson Foundation (RWJF) recently extended a $150,000 grant to help Osmosis make its platform accessible to all clinical students and, eventually, patients and other public users.
This project will build on RWJF’s ongoing investment
in reimagining medical education. As Michael says, this kind of smart online platform that enables customized, just-in-time learning could be another piece in our search for that giant leap to “free, ubiquitous and utterly fantastic health care education.”
The Osmosis content will be openly licensed under Creative Commons so that students and faculty can continuously improve upon it through the Osmosis crowdsourcing platform. Combined with our recommendation engine, this high-yield content will be made publicly available on www.osmosis.org
Members of the medical community, we need your help. We need clinicians, experts and educators like you to help contribute and review content. We’re counting on the medical community as we develop and curate practice questions, images, videos, mnemonics, and other resources in ten specific areas, from anesthesiology to surgery.
Shiv Gaglani (@ShivGaglani) is a co-founder of Osmosis. An editor of Medgadget, he is currently an MD/MBA candidate at the Johns Hopkins School of Medicine and Harvard Business School.
Ryan Haynes, PhD is a co-founder of Osmosis. He is also an MD candidate at the Johns Hopkins School of Medicine.