Outlabs
As a pre-med student, I worked in a few different offices and clinics that used lab tests. When I started looking into how much these test cost for patients, I was surprised to learn how much money could be saved if there was a different business model available. Patients without insurance might pay hundreds of dollars for basic panels, despite the clinical cost often only being a few dollars.
Since the unit cost of these tests are so low, patients are really paying for the labor and overhead of the diagnostic labs. However, from working in low-resource clinics, I learned that expensive lab equipment can often be sourced secondhand through corporate or small business sell-offs online. But to truly democratize diagnostics, clinics also need biomarker models, which can often be held as proprietary algorithms to specific labs.
Outlabs is a data science project I'm building to provide clinically-validated Python models that estimate biomarkers from blood tests. These tests are unavailable or unaffordable in rural clinics, low-income healthcare systems, and developing countries.
Outlabs provides validated mathematical models that estimate these biomarkers from routine blood tests that clinics already perform and can afford. By helping make diagnostics more accessible, I'm hoping not only to save patients money, but also educate low-resource hospitals and global health organizations worldwide.
This project is in progress, but you can test the models and check out the Github repo here. Currently working on adding more models to the list and more rigorous clinical validation.