This article is sponsored by Medtelligent. In this Voices interview, Senior Housing News sits down with Medtelligent CEO and founder John Shafaee to learn how the company’s assisted living machine learning solution, ALIS, is empowering caregivers, why Medtelligent is hyper-focused on length of stay and how ALIS helps communities achieve performance, efficiency and satisfaction.
Senior Housing News: You founded Medtelligent 10 years ago. Prior to that you spent many years working for UBS and Hostway. What are the most important lessons that you draw from in your role today?
John Shafaee: There are a few. The first is that ease-of-use is extremely important because it leads to adoption. If software is not easy to use, people will find ways to avoid using it. Once you have adoption though, you can focus on empowering the user. And the last lesson that has stuck with me, and led me through what we do in Medtelligent, is going deep on a business challenge. I saw this at UBS groups that were successful. They were hyper-focused on a specific business challenge and they saw that all the way through versus trying to create something generic that would go across the entire organization.
Tell us about Medtelligent. What does it do and what market need did you see that led you to found it?
We are a software company. We provide software — ALIS, pronounced “Alice” — to help operate assisted living, memory care and independent living communities. We’re very strict in our focus. We do not do skilled nursing or in-home health or hospice, for example.
How we got into it is that a friend of mine, roughly 10 years ago, coming out of real estate, jumped right into assisted living. He thought it was going to be more of a real estate deal, as most people assume, and quickly found himself in the middle of a very delicately complex business to run.
In meeting with him, I realized there were going to be more folks like him jumping in. There was such a divide between his understanding of assisted living and memory care and the reality. I wanted to give him and his staff a tool that would help them provide the best care and outcomes for their residents. That’s where we got our start.
You’re now launching a product designed to monitor changes in resident condition using machine learning. What is the product and how does it support care and improve outcomes?
It’s called the ALIS Wellness Index. We’ve trained a machine to look at changes to each resident’s wellness. First, we determine what an individual resident’s wellness actually is, and have a definition of that based on data from multiple sources. Then, the product monitors any change in their wellness from their baseline.
The goal here is to have the machine highlight residents who may need extra care or monitoring by staff so that you can avert incidents and move-outs. The residents in the community outnumber the staff, and with high staff turnover, a lot of the current information about the resident tends to leave the community.
My goal is for our software to mimic having a highly experienced nurse or practitioner in each care staff’s pocket. Imagine walking into a community being a care staff member. How do you get oriented? How do you know who these people are and who needs what attention? Some of our communities have 120 residents. How do you know who to focus on and what to do for each of them? It’s daunting. I thought it would be a fantastic application of machine learning to have an assistant with you who can guide you along that path.
Who are your customers and what do you hear from them in terms of what they’re looking for?
We serve assisted living, memory care and independent living communities coast to coast. Our customers pick us mainly because of ease-of-use. [These operators] don’t have a lot of time and money to spend on training people to use software.
The second most common reason customers select ALIS is that they feel familiar with our software right from the first demo. Every workflow, every nuance in assisted living is captured in our product. Because I don’t have to support skilled nursing or home health workflows, I’m able to build something that looks very familiar. The business driver for using our product is not just an easy-to-use tool to collect data — it’s really to move the dial on length of stay.
We are very focused on this concept of increasing residents’ average length of stay. It’s a much more sustainable model for growing a healthy assisted living community versus focusing on the sales side only. This concept of increasing length of stay is aligned with the problems of AL communities, which is to keep residents safe, socially connected and living their most optimal life. Longer lengths of stay also result in increased top-line revenue. Bottom line numbers are hard to manage in businesses with very thin margins.
Focusing on this one KPI — on length of stay — helps everyone: the residents, the staff, the operations, the value of the building.
What is unique about your solution, if you had to pick one thing?
If I could pick one thing, I’d say it’s our customer service. The traditional software-as-a-service playbook is that you go online, you buy a package and — good luck. We concentrate on adoption. We want people to actually use our product, and the only way to do that is to be an extension of their community. Some of the communities literally think of us as their IT department. They call us for things beyond our product offering. We provide the same level of care to the folks who use our platform that they do to the folks who live in the community.
What does an operator need in order to implement a machine learning system?
The bottom line is you need high quality data, and a lot of it. It does not matter who you buy your machine learning solution from or what solutions have machine learning in them, because if you don’t have a large amount of high quality data, that solution will be useless. There is no magic answer. At the end of the day, all we’re doing here is trying to get the computer to mimic a human activity.
There are a lot of people in senior housing who understand the value of machine learning, but there are plenty of others who might view it as a buzzword, or worse, a frightening intrusion. How does machine learning enhance caregiver capabilities?
My mission is to cut through the fog and explain what machine learning actually is. It’s a building block. It’s nothing more than training a computer to mimic human activity or behavior. Just like you train a child to put away clothes or to make lunch, you’re teaching a computer in the same way to do a specific task.
These capabilities can help increase the effectiveness of staff. Communities that have adopted solutions that have machine learning are going to improve residents’ health and experience longer lengths of stay. They’re going to have more satisfied residents. They’re going to have more consistent operations. They’re going to be able to boost their staff’s capabilities. What you’re doing is getting a computer to assist you in identifying the anomalies, and the interventions that work so you can be there at the point of decision with the care aid.
What’s next for Medtelligent in 2021?
We’ve had a lot of success focusing on length of stay. We’re going to double down on that. In the next year we’re also going to be focusing on personalized pricing. That’s another reason why folks leave a community: They get priced out. A lot of that happens due to inaccurate care pricing. Some people are paying for more care than they receive and some receive more than they pay for. Our analysis shows that improving pricing models is another area where a machine can really be put to use to help come up with optimal values for residents, optimizing their care plans and the fees that they pay for the care that they receive.
We’re also working on projects that help provide interventions. Now that we’ve got good penetration on not only the product, but some of our AL-specific machine learning models, we can start to see patterns between communities that do well and ones that don’t. We can start to help the communities that are not doing so well pick up interventions learned from the communities that are more successful.
Editor’s note: This interview has been edited for length and clarity.
Medtelligent makes ALIS: software purpose-built for clinical management, billing and operational reporting in assisted living communities. To learn more about what ALIS can do help your community solve some of your most important clinical and operational challenges, including increasing length of stay, visit Medtelligent.com.
The Voices series is a sponsored content program featuring leading executives discussing trends, topics, and more shaping their industry in a question-and-answer format. For more information on Voices, please contact email@example.com.