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I wouldn’t say I like lousy marketing towards me. Actually, in general, I’m not too fond of marketing. I don’t particularly appreciate receiving ads. If there’s ever an ad that comes on, I shut off the sound. I turn off the video; I turn away. I’m so anti-marketing, but I do appreciate targeted marketing and something that is well-targeted. Most of it, I think, is not. I see the number of ads for things like geriatric stuff, and I’m like, “Yeah, I’m not geriatric.” Or there are things I can’t say that pop-up, and I’m like, “Wait, what? This has nothing to do with me. Trust me!”

Target ads

I got a targeted ad on LinkedIn. They suggested that I’d be interested in this newsletter about data science trends and analytics, and I thought, “Wow, great! This is spot on. Perfect!” I clicked through, and I was happy to do that. I’m thinking about subscribing. I’m reading through this first article that says, “Which industries are hiring data scientists in 2021.” The first one on the list is healthcare. They have other ones: Hospitality, transportation, education, and all kinds of other things.

Going back to health care for a moment, I thought, “Okay, cool! Healthcare is, I don’t know if it’s number one, but it’s not only the number one.” I looked at what they talked about and where people were going: artificial intelligence, personalized care, connecting patients with doctors, better patient care, data-driven choices and technology, better experience in the hospital environments, monitoring patient health, again, better care, ease of data access to help providers make better clinical decisions. They list a bunch of healthcare startups.

The clinical side of things

What struck me was that 100% of what they talked about was clinical. I understand that the business of healthcare is effectively clinical. That is the output; that is the service that’s being provided. Yet, there is a financial side to that business. I mean, they have to get paid. They want to get paid well. There are all these sorts of things, and there’s this horrible push-pull tension between this third-party system of payers and providers where you get to get money out of somebody else, not the patient. 

This is just another reinforcement that machine learning, artificial intelligence (big data, analytics, data science) in healthcare is almost all focused on the clinical side of the business. I’m not discounting it. There’s real value in doing that because we need so much help when it comes to healthcare.

Abbreviated names

I have gone through some experiences, one with a child just two years ago where they had no clue what was going on. My daughter almost died. In the end, after spending days in the hospital and just trying to rule that kind of stuff out, they concluded they had no idea what it was.

In this odd sort of way, they made it sound like they did know what was going on by coming up with a name that meant they didn’t know what it was. “Idiopathic” was part of the name. “Idiopathic” means that they have no idea. I love that they name it. They even give it an acronym. For those of you in the clinical, you can probably figure out what this is. They come up with a name, give it an abbreviation, and pretend like they’ve diagnosed it when, in fact, the diagnosis is a non-diagnosis. It’s the most ironic thing you could think of in healthcare.


Notwithstanding, we need much help when it comes to the clinical side of the business. Yet, for those of us in the financial part of business, it seems like nobody’s paying attention to this. And there are many opportunities here. I just wanted to remind everybody that machine learning can be applied to financial data and artificial intelligence. There is excellent money to be made on that front, just on the clinical side.