AI Automation in Healthcare
Audrey's contribution to Citrusbug's feature on AI automation in healthcare: Better Information, Sorted Leads.
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Better Information, Sorted Leads
I optimize the AI tech stack for elective aesthetics practices, everything from med spas to plastic surgery to longevity, and a lot of that work is patient-facing. I've sat through 25-plus chatbot demos at this point. Some are genuinely useful. Some are the thing that makes you close the tab.
Here's where they help. Most plastic surgery websites are still just a contact-us form, which means the person filling it out waits until tomorrow for a callback. But that person is often a mom at 11 p.m. who finally got her kids down and has one question she wants answered tonight: can I trust this surgeon, what's it going to cost, when could I even get in. A good bot answers her right then. And the part I didn't expect the first few times I saw it: people tell a chatbot things they won't say to a coordinator on the phone. Weight they've gained or lost, where they are with menopause, the stuff that's a little embarrassing to say out loud. It's easier to type it, so the practice ends up with better information going into the consult.
The money isn't really in the bot booking someone that night. It shows up the next morning. Instead of the front desk treating every web lead the same, they wake up to leads already sorted by intent. This one came back three times and asked about a mommy makeover, call her first. This one was price-shopping, she can wait. The bot does the qualifying and the information-gathering, and the coordinator spends her actual attention on the patients and the clinical questions that need a person.
Where it goes wrong is a generic bot bolted onto a site with no customization, one that still tells people to "visit our contact page" and never learns what the practice wants more of. If it isn't built around the practice and it doesn't get better over time, it's a nuisance with extra steps.
Then there's the part nobody can skip, which is that this is PHI. Before a practice signs anything, I have them ask where the data actually lives, what the vendor does and doesn't touch, whether the practice owns its own data, and what happens the moment someone types something that sounds like an emergency: how does it hand off to a human, how fast, and how do you shut it off or update it. Then test it with your own staff and real patients before it ever faces the public.
