Population Health Strategies Are Vital for Tackling, Improving CKD Care

Navdeep Tangri, MD, PhD, FRCP, University of Manitoba, explores the topic of risk stratification in chronic kidney disease (CKD), innovations in this area, and how the interplay of population health strategies and policy reformation can benefit patient care. With the belief that CKD risk stratification can optimize the quality of care that patients receive, Tangri shares insights into his experience, what is working, and what could be improved in these processes.

This subject, among others, was explored at the Institute for Value-Based Medicine event, “Optimizing Kidney Health: Advances in Proactive Care Models,” held in Park City, Utah, at the end of September.

This transcript has been lightly edited.

Transcript

What are the most promising innovations in CKD risk stratification that have the potential to influence early detection, intervention efforts, and patient outcomes?

There's innovation happening both in diagnostics and therapeutics, and risk stratification can help bridge the two. In diagnostics, we now have a lot of emphasis on home testing. We have home testing kits and solutions and companies that are all trying to make it as easy as possible for patients to get diagnosed. At the same time, we have 4 treatments—4 highly effective therapies for diabetic kidney disease and multiple other therapies for IgA nephropathy and other glomerular diseases that are coming to market. The biggest issue in my mind is: how do you connect the patients—the patients who have now screened positive, and some of them who are high risk—to the right treatment? And that's where risk stratification can come in, and we now have highly accurate models that can do exactly that. They can take data that's available at screening and figure out who of these patients is high risk and what therapies they benefit from, and make that connection that’s often been missing.

What roles do social determinants of health play in CKD risk stratification? How can population health strategies better account for these factors in at-risk communities?

I think population health approaches are essential when tackling a disease like chronic kidney disease, particularly because we know social determinants of health, difficult socioeconomic status, or low economic status are drivers of chronic kidney disease. Screening in these high-risk communities is essential, but probably equally important is enabling access to treatment as well as doing some sort of passive surveillance. Yes, there's an issue with patients in marginalized communities who don't get enough testing, but probably equally important is that they don't get good care or they get sort of disconnected care. Population health approaches that use the lab, in my opinion, as a safety net to catch high-risk disease and catch chronic kidney disease, undertreated or untreated, can help bridge this gap.

In what ways can CKD risk stratification contribute to more efficient allocation of health care resources?

I think in 2002 to 2015 we had a “desert” in the development of chronic kidney disease medications. We really had no advances in therapy. And then you fast forward to the last 10 years, and it's actually been amazing. We've had multiple therapies that are highly effective, that all slow the progression of kidney disease and prevent heart failure hospitalizations. Now, should every single patient with chronic kidney disease receive all 4 pillars of care? I think that's neither cost-effective nor practical in the real world. So, health systems and payers need a way to allocate the intensity of therapy to the patients who need it most, and risk stratification will play an instrumental role in this by finding high-risk patients who need high-intensity therapy.

What are the primary barriers to implementing risk-based care models for CKD and how can policymakers or health care leaders work to overcome them?

I think the biggest barrier in implementing a comprehensive population health strategy for CKD is too much of a focus on the later stages. A few years ago, we finally shifted our focus away from dialysis care to later stages of care, but still, we're very much stuck in an EGFR (estimated glomerular filtration rate) or CKD-stage model, where stage 4 is now spotlighted as the only stage that sort of matters pre-dialysis, whereas the reality is patients who are high risk, who are fast progressors, who are having heart failure events, are spread all across CKD stages. So, I think one of the big things that policymakers and payers need to get their head around is that is to get away from this EGFR-centered view. I think lab data can really help enable this. I think lab data, combined with risk-prediction models, can find those patients, no matter what stage of kidney disease they're in, and target them before they lose their kidney function.

What are the most significant takeaways you hope audiences have from your presentation and work in this area?

First, I wanted to emphasize to the audience that CKD risk prediction has arrived. It's here. It's accurate and actionable; you can use the lab data that's routinely available and routinely collected today to find patients who are going to progress and who are going to have heart failure events. Now, it's imperative for us to act on those patients because if we act on them early, rather than waiting till stage 4 or waiting until dialysis, we've missed the boat. And if we act on them early, we can actually change their entire trajectory; we can prevent a lifetime of dialysis. So, I delivered a message of optimism, a message that high-risk disease should be treated with high-intensity therapy and that that can be transformative for patients.