Diabetic kidney disease (DKD) is the major cause of end-stage renal disease (ESRD) in the US. Although many people with diabetes develop DKD, approximately one in five has DKD with uncontrolled hypertension that increases their risk of ESRD, cardiovascular events, and death. These risks are reduced by simultaneously improving control of multiple risk factors. However, prior interventions have largely: ignored low awareness of kidney disease limiting treatment; been conducted using costly face-to-face visits limiting widespread application; and included populations with limited generalizability. In addition, most studies have included those with early or late DKD but have not targeted moderate DKD and uncontrolled hypertension which would potentially optimize efficiency and impact by excluding those with stable disease and reducing the risks of ESRD, cardiovascular events and death before developing advanced DKD. For this planning grant, we propose to develop The STOP-DKD Automated Population Program (APP), a population management program that will: identify patients with moderate DKD and uncontrolled hypertension from an integrated data warehouse for a multi-state diabetes study in four underserved Southeastern counties; monitor adherence and self-management behaviors, providing e-reminders/messages to improve DKD medication adherence and health behaviors via patient-selected technology (mobile/web-based applications, text messaging, interactive voice response, or e-mail); and monitor outcomes with activation of engagement by a case manager through our existing telehealth platform for suboptimal control of blood pressure or health status. Our APP builds upon our prior work to deliver a tailored, multi-factorial intervention to address medication management and modify multiple risk factors simultaneously through a combination of patient self-monitoring, behavioral therapies and education that optimize adherence and self-efficacy. Intervention effectiveness will be evaluated among 320 individuals with moderate DKD in a six-month randomized trial to improve blood pressure control (primary outcome) and health behaviors that influence other cardiovascular risk factors (secondary outcome). To assess the feasibility of future large-scale implementation and dissemination, we will also conduct impact (using the RE-AIM framework) and economic evaluations (using the Archimedes model). For sustained adoption, this study will establish critical experience necessary for successful scale up in future effectiveness studies within this pre-identified dissemination channel and other health systems. To mitigate the growing burden of DKD in the US, this study is expected to fill a void in scalable treatment options by establishing the feasibility and efficacy of our evidence-based APP to identify and manage DKD in underserved high-risk patients.
The growing epidemic of diabetes will cause more people to suffer from kidney failure. Interventions that effectively identify and manage those with kidney disease are needed to help reduce the 50,000 new cases of diabetic kidney failure each year. A cost-effective, evidence-based, population management program that can be easily translated into practice may fill this void.
| Diamantidis, Clarissa J; Bosworth, Hayden B; Oakes, Megan M et al. (2018) Simultaneous Risk Factor Control Using Telehealth to slOw Progression of Diabetic Kidney Disease (STOP-DKD) study: Protocol and baseline characteristics of a randomized controlled trial. Contemp Clin Trials 69:28-39 |
| Zullig, Leah L; Diamantidis, Clarissa J; Bosworth, Hayden B et al. (2017) Racial differences in nocturnal dipping status in diabetic kidney disease: Results from the STOP-DKD (Simultaneous Risk Factor Control Using Telehealth to Slow Progression of Diabetic Kidney Disease) study. J Clin Hypertens (Greenwich) 19:1327-1335 |
| Stanifer, John W; Muiru, Anthony; Jafar, Tazeen H et al. (2016) Chronic kidney disease in low- and middle-income countries. Nephrol Dial Transplant 31:868-74 |
| Drawz, Paul E; Archdeacon, Patrick; McDonald, Clement J et al. (2015) CKD as a Model for Improving Chronic Disease Care through Electronic Health Records. Clin J Am Soc Nephrol 10:1488-99 |
