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Listen: What’s your risk of falling? This researcher is trying to find out.

In the latest installment of our occasional conversations with Fort Worth leaders, Rita Patterson, associate dean for research in the Texas College of Osteopathic Medicine at The University of North Texas Health Science Center, discusses how physical therapy could be used for prevention — and what it takes to calculate your risk of falling. 

This conversation has been edited for length and clarity. For more details, please listen to the audio file attached to this article.

Alexis Allison: When I think of physical therapy, I tend to think of treatment that’s responsive to an injury. But it’s my understanding that you’re working on physical therapy as prevention. Can you share a little bit about that?

Rita Patterson: Yes, I’m super excited about physical therapy or rehabilitation in general as being more of a preventive part of health care. Many people don’t go to see a health provider until they get hurt. But many times we’re down the path of risk of injury before we even know it. I really think that it’s important that we get a physical health checkup. That’s difficult to do in a 15-minute patient encounter when you’re already sick and you need some antibiotics or whatever. I think we really need to work on preventing musculoskeletal injuries, because it doesn’t take very long for muscles to deteriorate or for you to lose strength, and you don’t even know it.

Allison: What would that sort of preventive care look like? 

Patterson: In my own life, I’ve had musculoskeletal injuries. When I went in front of a physical therapist or got rehabilitation, and they gave me one exercise, it was like a game-changer. And it was very simple. I never thought about it, and I work in this space. So sometimes the most obvious things are not obvious to those of us who aren’t health providers. There’s some low-hanging fruit, I think, that many people could do just to stay healthy — and not be a super athlete, or have to go to the gym three times or five times a week, and not necessarily to lose weight — but to get the benefits of aligning your spine and making sure you have good posture, especially when we’re sitting on Zoom all the time.

Allison: I’d like to know one example of the low-hanging fruit if you’re willing to share.

Patterson: I carry a lot of stress in my neck. And I would sit in meetings with my arms crossed because I’m long-waisted, and it’s comfortable. But I didn’t realize that I was really pulling my shoulders forward. And I got to the point where my (chest muscles) were so tight, because my back was so stretched out. I started having pinched nerves in my neck. I got into some therapy, and they got me stretched out, and they showed me how to sit up straight, have good posture and keep my shoulders down. I do that now just to prevent the problems that I had in my neck. I’m just so grateful for one or two little exercises that helped me.

Allison: You’re working on an algorithm to predict how at risk someone is for falling. Can you elaborate on that project? 

Patterson: Sure. We basically have a couple of systems that help us with our balance. One is our eyes — our vision, which helps us locate where we are in space so we don’t fall over. The other one is our vestibular system. In our ears are those semicircular canals that tell us if you’re upside down or not — that’s what makes you get motion sick. And then proprioceptive, which is usually your skin and the bottom of your feet. They tell you where your feet are, and they help you moderate what the surface that you’re standing on is. Any one of those three systems can be out of whack, and you can have problems with your balance. A lot of times, it’s hard to determine which system is the culprit. 

So I said, “Hey, why don’t we go in and take a force plate to the clinic and measure balance on everybody as another clinical vital?” And then if we can get thousands of people, now all of a sudden we can do some machine learning algorithms to create an understanding of what your risk profile would be. It would flag if (your balance) is out of range, just like a blood test. 

That data then is put into a dashboard so I can look and see whatever the demographics are that we have in that patient population. That’s for future research later. But the main goal was to provide the providers with information about their patients. So typically, at this clinic, people come back multiple times. So if they have the balance done over several weeks, then the provider can show that to the patient, say, “Look, you’re doing better. Your treatment is working, or at least this one measure.” 

I’m excited about this because we can now finally look at some different racial and ethnic groups to see if there are differences. When I did the last literature search, most gait studies or walking studies are in young people like college students, right? Because they’re on college campuses. I found one that had a population of African Americans — that was the first one I’ve ever seen. And so I’m excited to have a more diverse population, and to be able to now start looking at this, and then we can maybe come up with some clinical protocols or some guidelines or some suggestions.

Allison: Why is it hard to find a diverse group of participants for these studies?

Patterson: That’s a great question. Partly because I don’t know everybody —  maybe that’s part of it. We do word of mouth. And we try to recruit, especially for patient populations. We’ll go to support groups. But there are also different cultural barriers, some groups just don’t want to participate in research at all. Or maybe I’m not in the right place at the right time. And I’m not going into the community where I need to go. Because I’m one person and I can’t be everywhere. We try. But it’s not a perfect system.

Allison: Say someone is listening to this audio, and they would be interested in helping out. Is that something they could do? 

Patterson: So it’s not a research study right now. We’re just implementing it in the clinic to see if it’s feasible, right. So now, I’m thinking about, what if we took the same system and got all the research approvals that we need and take it to the community? Could we take it to a senior citizen living center? Could we take it to a church? And so that would mean more resources in person time. People to do that data collection. Things like that. But I think eventually, that’s sort of where I’m looking. What if we put this into an orthopedic hospital floor and test people before they get discharged and just start looking at that data to see, “Is there a minimum score they need to get before we should let them go?”

Allison: Why focus on falling?

Patterson: It’s a huge problem. You get a hip fracture, and many people don’t recover from that. And people don’t always report falls. “Did you fall in the last six months?” “I don’t remember.” Or maybe I had a near fall. So validating this dataset with “fallers” would be also huge. Another thing that I’m really looking to include is (providers) asking people, “Have you fallen?” and then adding that (information) to the database. So we’re learning as we go, actually.

Allison: Circling back to using physical therapy as a preventive tool, say a patient were to receive a balance score in a dangerous level. What could they then use that information for?

Patterson: Well, their provider could say, “Hey, I’m going to refer you to a full evaluation by a physical therapist,” or, “Hey, let me do a neuro exam or a musculoskeletal strength exam.” Because your family medicine doctor will do that.

And then if they see that you have some deficits, then maybe have you enroll in — there’s all kinds of community resources, too, like the SilverSneakers for older adults — programs in the city. There’s a lot of resources. Prescribe going walking more, or doing a couple exercises for your legs.

Allison: Is there anything else you’d like to add?

Patterson: For machine learning, you need 10,000 data points — you don’t need 500.

So, the more data we have, the more we can put people in bins that are similar, and then we have more data to analyze. But we have to start somewhere. So we bootstrap it up and work on it a little bit of time, and we’re getting there.

Alexis Allison is the health reporter at the Fort Worth Report. Her position is supported by a grant from Texas Health Resources. Contact her by email or via Twitter. At the Fort Worth Report, news decisions are made independently of our board members and financial supporters. Read more about our editorial independence policy here.

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