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| ID | Type | Description | Link |
|---|---|---|---|
| 1R34DK102166-01 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) | NIH |
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This study will build a population management system Simultaneous risk factor control using Telehealth to slOw Progression of Diabetic Kidney Disease STOP-DKD Application STOP-DKD APP and conduct a 6-month controlled trial to compare reduction of blood pressure. In addition, the study will evaluate the feasibility of future large-scale intervention to slow diabetic kidney disease (DKD) DKD progression.
Aim 1: Identify patients with moderate DKD and uncontrolled hypertension (HTN) using existing electronic health record data in an integrated data warehouse (Southeastern Diabetes Initiative- SEDI) to screen all patients within SEDI.
Aim 2: Implement an intervention designed to slow progression of DKD and treat associated conditions in a high-risk population with moderate DKD and uncontrolled HTN using the STOP-DKD APP
Aim 3: Evaluate the STOP-DKD APP Study to guide large-scale implementation & dissemination
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention Telehealth | Experimental | Using Telehealth to slow progression of diabetic kidney disease automated population program identifies patients and engages them to optimize DKD medication adherence and health behaviors using 2-way communication via patient-selected technology (mobile/web-based applications, text messaging, interactive voice response, or e-mail) backed by case management via the phone for suboptimal control or health status. The STOP-DKDAutomated Population Program will deliver a tailored, multi-factorial intervention to address medication self-management and modify multiple risk factors simultaneously through a combination of patient self-monitoring, behavioral therapies and education that optimize adherence and self-efficacy. |
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| Control/No Intervention | No Intervention | Group of subjects that will serve as a comparison group. These subjects will not be approached/enrolled for this study. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Telehealth | Behavioral | Using Telehealth to slow progression of diabetic kidney disease automated population program identifies patients and engages them to optimize DKD medication adherence and health behaviors using 2-way communication via patient-selected technology (mobile/web-based applications, text messaging, interactive voice response, or e-mail) backed by case management via the phone for suboptimal control or health status. The STOP-DKDAutomated Population Program will deliver a tailored, multi-factorial intervention to address medication self-management and modify multiple risk factors simultaneously through a combination of patient self-monitoring, behavioral therapies and education that optimize adherence and self-efficacy. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Blood Pressure | Baseline & 6months |
| Measure | Description | Time Frame |
|---|---|---|
| Change in estimated Glomerular filtration rate (eGFR) for kidney function | Baseline & 6months | |
| Change in dietary habits as measured by questionnaire | Baseline & 6month | |
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Potentially eligible patients will be identified using the existing SEDI (Southeastern Diabetes Initiative) data warehouse that pulls electronic health record data quarterly from ten different source systems in the four counties.
Exclusion Criteria:
Patients who meet any one of the exclusion criteria will be excluded:
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| Name | Affiliation | Role |
|---|---|---|
| Uptal Patel, MD, PhD | Duke University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Duke Clinical Research Institute | Durham | North Carolina | 27715 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30964439 | Derived | Lewinski AA, Patel UD, Diamantidis CJ, Oakes M, Baloch K, Crowley MJ, Wilson J, Pendergast J, Biola H, Boulware LE, Bosworth HB. Addressing Diabetes and Poorly Controlled Hypertension: Pragmatic mHealth Self-Management Intervention. J Med Internet Res. 2019 Apr 9;21(4):e12541. doi: 10.2196/12541. |
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| ID | Term |
|---|---|
| D003928 | Diabetic Nephropathies |
| ID | Term |
|---|---|
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
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| ID | Term |
|---|---|
| D017216 | Telemedicine |
| ID | Term |
|---|---|
| D003695 | Delivery of Health Care |
| D010346 | Patient Care Management |
| D006298 | Health Services Administration |
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| Change in weight |
| Baseline & 6month |
| Change in amount of physical activity as measured by questionnaire | Investigators will assess whether patients who receive the intervention will have improved behaviors that affect HTN control and cardiovascular risk ( physical activity) as compared to a control group after 6 months | Baseline & 6month |
| Change in taking medicine as prescribed | Investigators will assess whether patients who receive the intervention will have improved behaviors that affect HTN control and cardiovascular risk (medication adherence) as compared to a control group after 6 months | Baseline& 6month |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D048909 | Diabetes Complications |
| D003920 | Diabetes Mellitus |
| D004700 | Endocrine System Diseases |