Suggestions
Nikhil Krishnan
Founder of Out-Of-Pocket
Nikhil Krishnan is the founder and "Thinkboi" at Out-Of-Pocket, a platform aimed at making healthcare more accessible through humor and relatable content. He has a background in sustainable development and business management, having graduated from Columbia University in 2014. His professional experience includes roles such as the Strategic Partnerships Manager at TrialSpark and Senior Industry Analyst at CB Insights, where he focused on digital health and biotechnology trends.
At Out-Of-Pocket, which he founded in February 2020, Krishnan uses memes and humor to educate people about the complexities of healthcare operations. His approach aims to demystify the healthcare system and engage a broader audience.14 He is also active on Substack, where he publishes a newsletter that has gained significant traction, reaching tens of thousands of subscribers.23
In addition to his current venture, Krishnan previously founded Get Real, a platform designed to facilitate structured online-offline friendships, and has held various internships in organizations like Uber and the Earth Institute.14 His work emphasizes a blend of humor and critical analysis of healthcare, making complex topics more digestible for the general public.
Highlights
one of my hopes is that open-sourcing this Medicaid claims dataset is that it exposes regularly people to weird the actual underlying claims data actually is
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The chaos of trying to sort out NPIs from intermediaries vs. people delivering care
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how modifiers get used in billing data that make it extremely difficult to parse out what services were actually delivered
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how not having the actual records data from an encounter makes it nearly impossible to figure out what things happened vs. what's simply being documented for insurance purposes
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How wacky the billing becomes when you change the site of are itself (e.g. inpatient vs. outpatient)
There are a lot of bad analyses on here that don't understand the context around how billing works today or assume it's similar to something like payments data.
But maybe those analyses will also make it clear that many of the suspected frauds pointed out are because billing is so convoluted, and we should ACTUALLY fix how billing is done
I think pictures are underutilized in current healthcare journeys
When I went for my last dental checkup, they used an iTero machine to essentially take a picture of each tooth. They then walked me through each tooth, what's happening, and how it compared to the last time they took a picture.
This obviously took a long time, but I thought it was pretty interesting. Also made me realize how (in my experience) we use relatively little pictures and ask patients to describe the changes they've seen in areas over time (e.g. stool, changes in skin conditions). I think in specialist settings there are more pictures used (e.g. dermatology), but even that feels unevenly used or underutilized.
My guess is the main reasons this hasn't been done historically have been:
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time taken to read every single image is enormous
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treatment course probably wouldn't change a ton even with pictures
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not enough time in the visit to go through the changes in the pictures
But today AI tools can probably do the guidance + triaging of these pictures, and only escalate to the doc if it's something particularly interesting and relevant. In fact analyzing pictures of health issues feels like one of the specific areas I go to LLMs for help with.
It would be cool if pictures just became part of patient intake forms and attached to the record, and changes tracked over time.
