Understanding the Correlates of Using CGM, with Lindsay Mayberry, PhD

The prospect of continuous glucose monitoring (CGM) has gone from science fiction to reality in less than a lifetime. Today, the role of CGMs in diabetes management is more pronounced than ever, but questions remain regarding the characteristics that make patients more likely to adopt and adhere to the use of CGMs.

At the 82nd Scientific Session of the American Diabetes Association (ADA), discussions and symposia put the use of CGM under the microscope to better understand and optimize its use, particularly in primary care settings. A pair of posters presented at the conference by Lindsay Mayberry, PhD, associate professor of medicine and bioinformatics at Vanderbilt University Medical Center, examined contemporary trends in CGM use in adults with type 2 diabetes. in primary care or endocrinology clinics within their healthcare system and further explore which patient characteristics were associated with an increased likelihood of primary care use.

Study results demonstrated that CGM use increased rapidly during the COVID-19 pandemic, with an average of 110.2 patients per month receiving newly prescribed CGM in 2021. The results of this study suggest an older age youth, insulin use and higher A1c, but not gender, race or ethnicity, which contradicts the findings of many previous studies. When assessing the correlates associated with the use of CGM in primary care, study results indicated that use was more common in younger patients (55 [IQR, 47-62] against 60 [IQR, 53-68]; p= 0.031), had a higher baseline A1c (9.1% [IQR, 8.1-10.4] against 8.3% [IQR, 7.5-9.5]; P= 0.048), used insulin (69% versus 36%, P= 0.002) and had higher baseline diabetes distress (45 [IQR, 25-55] against 30 [IQR, 15-50]; P=.09). As in the first study, there was no association between gender, duration of diabetes, race, ethnicity, and health literacy with increased use.

To learn more about the results of these studies and how they can inform efforts to optimize CGM adoption, Endocrinology Network sat down with Mayberry at ADA 2022 and that conversation can be found below.

Optimizing the Use of CGM with Lindsay Mayberry, PhD

Endocrinology Network: Can you describe the responsibility for these studies and what were your most important findings?

Mayberry: I’m a behavioral scientist. So I design and test interventions to help people make lifestyle changes for chronic conditions like diabetes. One of the areas I work most in is type 2 diabetes. What we’ve seen with our most recent intervention trial is that people are using CGM in numbers never seen before. I got really interested in how we should react to that, because it’s behavioral, isn’t it?

It is a health behavior to use a CGM effectively. So that becomes how do we understand what is going on here. One of the things I did to figure out what was to look at the impact of CGM use in people with type 2 diabetes in our healthcare system.

So we use data from electronic health records and we use a pre-validated algorithm to identify all people with type 2 diabetes who have been seen in primary care or endocrinology clinics. We said, “Okay, this is our patient population or our cohort, let’s look back to see if they’ve ever used a CGM? If yes, when did this happen?

What was really interesting was that we saw that an increase in CGM use started to appear for these patients in the spring of 2018. Then, just as it rapidly increased to the point that in 2021, the average rate of new CGM users was 110 patients per month. That’s a lot of people with type 2 diabetes who use CGM.

We are therefore interested in what characterizes the people who use it compared to those who do not use it. Using data from electronic health records, we examined demographic characteristics, insurance status, HbA1c, HbA1c when prescribed, and race/ethnicity.

Basically what we found was that the people who used CGM were younger and they were more likely to use insulin, but there was a pretty good proportion of them who didn’t didn’t use insulin at all, which was rather surprising. And we found no differences by race, ethnicity, or insurance status. And that was exciting because there may not be an unequal distribution, at least within our system, of this technology, by race or by insurance status.

Endocrinology Network: Is it encouraging to see that race, insurance type and gender didn’t really impact the adoption rate or are you worried that it doesn’t reflect experiences outside of your healthcare system? ?

Mayberry: I think both of those things are true. I think it’s really great that in our medical center we don’t see any disparities, I think that’s great. Our medical center is certainly not representative of what we would see in community health centers. So to assume that because we don’t see disparities means there aren’t any, that would be wrong.

I’m sure there are disparities, but maybe it happens depending on where people seek care and insurance probably plays a role, but, at least in our health care system, that was not the case, but maybe there weren’t as many people who were underinsured in our health care system as there might be elsewhere. I know that insurance plays a role and the adoption of CGM. So I don’t want to act like it’s not a factor, but it was to encourage that maybe it’s not as big a factor as we might have assumed.

About Mark A. Tomlin

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