So the goal of this edition is to give you some practical ideas for how you can start implementing AI in your practice(s).
And each of these is already being used by healthcare businesses around the world.
So let’s get into them.
Idea 1: Personalized Appointment Reminders
According to Naimish Patel, head of Healthcare at Red Cell Partners, AI agents focused on the patient journey will see the most adoption (especially in the short-term).
This is mainly because AI is well-suited for such use-cases, and they’re also relatively low-stakes.
Now when it comes to personalized appointment reminders, the gist is pretty straightforward: using AI to draft personalized messages when following up with patients to lower no-show rates.
But this isn’t your traditional “set and forget” email/SMS follow-up sequence that you blast to all of your patients.
Each sequence of messages is tailored to individual patients based on their information.
Not only that, but say you run a small dermatology practice with 3 different providers, for example.
Each provide might do a different set of procedures (maybe only one of them is a Mohs surgeon).
An advanced AI system can offer appointments to patients based on the procedures each doctor does and tailor reminders accordingly.
So these systems can be personalized for both patients and providers.
Two examples of companies selling agentic systems to improve the patient journey are InTrivio and Artera (not affiliated with either).
Idea 2: Predicting No-Shows For Targeted Marketing
A study by Toker et al. created a model to predict no-shows based on prior data from patients who didn’t show up to their appointments.
The crazy part?
The model was able to predict 92% of no-shows accurately!
The beauty of systems that leverage such models is that they enable you to send targeted marketing campaigns to patients who are the most likely to be no-shows.
As a result, you can increase the likelihood that these patients follow through, directly bumping up your bottom-line.
Unless you’re a tech wiz, a good way to acquire such an application would be by partnering with a vendor in some capacity.
Such vendors can train AI applications using your own data and create a scoring system to rank which patients are the most likely to be no-shows, allowing you to plan your marketing efforts accordingly.
Idea 3: Automated Inventory Triaging
According to McKinsey, early adopters of AI-enabled supply chain management have improved logistics costs by 15%, inventory levels by 35%, and service levels by 65% compared to slower-moving competitors.
How?
Well, if you have an AI system that can:
- keep track of when stock of a particular supply is low
- look at your upcoming appointments to determine which supplies you need most urgently
- prioritize them for you so that all you have to do is order them (or let the system do that too after setting a budget)
the returns start to make sense.
You don’t have to sort through it all yourself, you don’t need to worry about overstocking or running out of supplies, and it’s cost-effective on top of it all.
For simple versions of such systems (just to try it out), you can honestly put something together using some no-code and low-code tools like Zapier, Make, N8N, etc.
But if you want a scalable system, you’ll probably have to pay a vendor or purchase an enterprise subscription.
Of course, the investment makes more and more sense as you scale to additional locations, which is when the burden of inefficiencies becomes significant ($$).
This is especially the case for multi-speciality groups with so many different inventory requirements.
TL;DR
- Idea 1: Personalized Scheduling Management
- Idea 2: Scoring Probabilities of No-Shows for Targeted Marketing
- Idea 3: Automated Inventory Management
Hopefully this has gotten you thinking about where else you can use AI within your practice 🙂
That’s all for this week.
See you next Saturday.
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