Dr. Michael Gao

And you just saw them in bed and wrote two words on a piece of paper and called it a day.

And so I think...

I think some of the reason that we don't feel like there's been progress in terms of simplifying revenue cycle is that we took a process that was built, in a sense, for a much simpler world.

And patients are... And the treatments and everything we do is so much more complex.

And I think if you...

You know, we've had, I remember when I was a resident, we would occasionally have, you know, a few hours of downtime.

And I literally wouldn't even know how to, you know, like compose the solution to deliver a medication because I just don't memorize the percentage of saline versus, you know, kind of like other fluids.

And so I do think that the EMR, you know, has been helpful in that

transformation from manual to digitization.

But at the end of the day, it's still, to go back to what we were talking about in the beginning, it's still a person who has to do all of the cognitive work.

And the care these days is just really complex, especially at these, you know, tertiary academic medical centers or, you know, like these level four trauma centers, as an example.

And so I do think that's where the fundamental problem of how do we find the capacity to do that cognitive labor doesn't get solved by converting something to the digital.

You can have more standardized workflows.

You can have priority lists.

But I think that's why AI is sort of so exciting for its potential to transform this.

Yeah, I think that's I think that's fair.

There's a little bit of a confounding factor, which is that the sort of larger health systems are the ones that tend to have higher acuity and they're better resourced.

Their teams are bigger and they're just more sophisticated.

Yeah, they're more sophisticated in general.

But I think even with that, that is still true.