Improving Collaborative Care in Diabetes - Episode 8

Important Outcomes Measures in Diabetes Care

Troy Trygstad, PharmD, MBA, PhD; Dhiren Patel, PharmD; Steven Peskin, MD, MBA; Richard Wynn, MD; and Tripp Logan, PharmD, offer insight into important outcomes measures in type 2 diabetes that look beyond A1C.

Troy Trygstad, PharmD, MBA, PhD: Within your response, you brought up this idea of something that Dhiren touched on earlier. Hemoglobin A1C may be a great measure, but it’s not the only measure. So, let’s start at this end of the panel and go in this direction. What are 1 or 2 other measures that you think are really important in this arena that ought to get attention, that maybe aren’t?

Dhiren Patel, PharmD: I would say something around cardiovascular disease. If you think about how many patients with diabetes actually die of cardiovascular disease, it’s 8 out of 10. When we’re thinking about diabetes, all I hear is, “Fasting plasma glucose, postprandial glucose,” and “A1C.” I think if more emphasis was given to cardiovascular disease, there are probably things that could be done—through an ACE (angiotensin-converting enzyme) inhibitor, a statin, smoking cessation, and aspirin—that would arguably impact outcomes more so than glycemic management. We know that there’s some good data with microvascular complications. But if you look at the macrovascular complications, 8 out of 10 are dying from that. Why isn’t the focus more around that? It’s all tied to A1C. That’s why I say it’s an incomplete picture.

Troy Trygstad, PharmD, MBA, PhD: Good point.

Steven Peskin, MD, MBA: Yes. I’m going to say, “absence of” is one. “Absence of” is absence of emergency department visits, absence of hospitalizations, absence of stroke, absence of myocardial infarction, and absence of an amputation. And then, the second one is the person’s perception, how he or she perceives his or her quality of life. So, that would be my second one.

Richard Wynn, MD: One of the big things in all of this is the data being provided to the practitioners. The metrics are useless unless you know what your metrics are. If I don’t know how many of my patients are at goal, how many of my patients have a LDL (low-density lipoprotein) below 100, or how many have had their diabetic eye exam, it’s useless. Every doctor thinks he or she is doing well until you actually see the data and the comparisons to other providers. And so, in context, maybe I should pay more attention to this than I am.

Troy Trygstad, PharmD, MBA, PhD: And you’re in an information-rich environment.

Richard Wynn, MD: Yes. Are you looking at people’s feet? How many patients have you had show up with a toe that is about to fall off because you haven’t checked their foot this year?

Troy Trygstad, PharmD, MBA, PhD: Right. Tripp, you’re in a different information-rich environment where you may not have access to certain types of rich diagnoses data, care plan intention data, etc, etc. But you’re in a very rich social-determinant, patient-capable environment circumstance. What metrics become really important for you? When you engage a patient at the counter or when you’re doing a home visit with a patient like you do? What sort of assessment, and what sort of outcome metrics, become relative to diabetes that one might not think are part of diabetes measures, but are really important?

Tripp Logan, PharmD: Going back to your example, Troy, of the prescription coming through, metformin. “This is their A1C.” That’s an ideal world for us because that’s a whole different conversation. Since we don’t have access to that, we try to turn lemons into lemonade. We try to be a metric provider, information provider, or data provider. We try to be a patient voice, a social determinant. What we see is a patient is diagnosed with diabetes. They go for their follow-up visit or 5-year visit, or whatever it is, and they’re still not at goal.

We’ve adopted and done some testing with a PHQ-9 (Patient Health Questionnaire-9) on these patients. Most of my folks get diagnosed with diabetes and come out with diabetes and depression. If the patient is depressed and down, the likelihood of them sticking not only to their medication regimen but then to their care plan as a whole is way, way down. That’s often missed. And so, if we can capitalize and provide that back, that’s gotten us a little closer with our mental behavior health providers in the area.

If we said, “Hey, we’re going to test most of our diabetes patients. We’ve got a select group. If they meet these criteria, we’re going to do a PHQ-9 on them. Would you want the referral if we send him to you?” Absolutely they do. That opens up a line of communication that, all of a sudden, gets us more data. And so, we’re trying to turn us not having much data into, what data can we provide in order to get more data that will help us better care for these patients.

Steven Peskin, MD, MBA: Yes. I like what Tripp is saying: patient-reported outcomes. Or we can even call it person reported. We can even take away the label of patient.

Troy Trygstad, PharmD, MBA, PhD: It’s interesting. If you ask the lay policy person, or the person that has a superficial clinical understanding or practice understanding, you would say, “Hemoglobin A1C.” What I hear all of you saying is, “No, there’s a log of measures in and amongst parallel disease states. Really, this is a population of patients that is complex and multimodal.”

Steven Peskin, MD, MBA: Look at the whole person.

Troy Trygstad, PharmD, MBA, PhD: And looking at the whole person.